METHODS, SYSTEMS AND COMPOSITIONS FOR RESTORATION AND PRESERVATION OF INTACT ORGANS IN A MAMMAL

Abstract
The invention provides a system for hypothermic, restoration and preservation of organs in a mammal. In certain aspects, the system is capable of preserving organs, maintaining cellular integrity and cellular function for hours postmortem or after global ischemia. The invention also provides synthetic organ perfusate formulations, including a novel perfusate autologous blood mixture, which is able to reduce reperfusion injury, stimulate recovery from hypoxia, metabolically support the energy needs of organs and prevent rigor mortis.
Description
SUMMARY OF THE INVENTION

In one aspect, the invention provides an isolated perfusate mixture comprising: an inorganic salt solution; an artificial oxygen carrier; and autologous blood.


In another aspect, the invention provides a system for the hypothermic preservation of organs in a mammal, the system comprising:


a perfusion device for the perfusion of an isolated perfusate mixture into the mammal, the perfusion device comprising: a perfusion loop; and a controller programmed to regulate at least a perfusate temperature within the perfusion loop to maintain hypothermic conditions; and the isolated perfusate mixture as described elsewhere herein.


In yet another aspect, the invention provides a mammal perfused with the isolated perfusate composition as described elsewhere herein, wherein mammalian organs are perfused under hypothermic conditions.


In yet another aspect, the invention provides perfused organs in a diseased mammal, wherein the perfused organs maintain one or more properties selected from the group consisting of an in vivo level of cell function and viability, and an in vivo level of morphology


In certain embodiments, the one or more artificial oxygen carriers is selected from the group consisting of hemoglobin glutamer-250, isolated cell-free hemoglobin, cross-linked hemoglobin, polymerized hemoglobin, encapsulated hemoglobin, and perfluorocarbon oxygen carriers. In certain embodiments, the artificial oxygen carrier is hemoglobin glutamer-250.


In certain embodiments, the one or more inorganic salts are selected from the group consisting of sodium chloride, sodium bicarbonate, magnesium chloride, and calcium chloride.


In certain embodiments, the perfusate mixture comprises a priming solution containing one or more sugars. In certain embodiments, the one or more sugars are glucose or dextrane.


In certain embodiments, the isolated perfusate mixture further comprises one or more amino acids. In certain embodiments, the one or more amino acids are selected from the group consisting of glycine, L-alanyl-glutamine, L-arginine, L-cysteine, L-histidine, L-isoleucine, L-leucine, L-lysine, L-methionine, L-phenylalanine, L-serine, L-threonine, L-tryptophan, L-tyrosine, L-valine and salts and solvates thereof.


In certain embodiments, the perfusate mixture further comprises one or more vitamins.


In certain embodiments, the one or more vitamins are selected from the group consisting of choline, D-calcium pantothenate, folic acid, niacinamide, pyridoxine, riboflavin, thiamine, i-inositol and salts and solvates thereof.


In certain embodiments, the perfusate mixture further comprises, ferric nitrate, magnesium sulfate, potassium chloride, sodium phosphate, and derivatives thereof.


In certain embodiments, the perfusate mixture further comprises an anti-clotting agent. In certain embodiments, the anti-clotting agent is heparin.


In certain embodiments, the percentage of autologous blood in the mixture is between 10% and 50%. In certain embodiments, the percentage of autologous blood in the mixture is approximately 28%.


In certain embodiments, the mixture is dialyzed against a solution comprising inorganic salts. In certain embodiments, the mixture is dialyzed against plasma.


In certain embodiments, the mixture comprises electrolytes and oncotic agents at levels comparable to those in autologous blood. In certain embodiments, the perfusate further comprises cytoprotective agents.


In certain embodiments, the cytoprotective agents are selected from the group consisting of 2-Iminobiotin, Necrostatin-1, sodium 3-hydroxybutryate, glutathione, minocycline, lamotrigine, QVE-Oph, methylene blue, and/or any salts, solvates, tautomers, and prodrugs thereof.


In certain embodiments, the mixture further comprises antibiotics. In certain embodiments, the antibiotic is ceftriazone. In certain embodiments, the mixture comprises one or more anti-inflammatory agents.


In certain embodiments, the one or more the anti-inflammatory agents is dexamathazone or cetirizine.


In certain embodiments, the temperature of the mixture is approximately 28° C.


In certain embodiments, the perfusion loop further comprises at least one pulse generator programmed to generate a pressure pulse within the perfusate within the perfusion loop.


In certain embodiments, the perfusion loop comprises a venous loop, a filtration loop and an arterial loop, wherein:


the venous loop comprises at least one perfusion pump;


the filtration loop comprises at least one perfusion pump, and at least one hemodiafiltration unit adapted and configured to equilibrate the perfusate;


the arterial loop comprises at least one gas exchange source and at least one gas mixer adapted and configured to supply oxygen and carbon dioxide to the perfusate;


wherein the mammal, the venous loop, the filtration loop and the arterial loop are in fluidic communication such that the perfusate can be carried from the mammal, through the venous loop, through the filtration loop, through the arterial loop and back to the mammal.


In certain embodiments, the one or more components selected from the group consisting of the venous loop, the filtration loop and the arterial loop further comprise a reservoir containing excess perfusate.


In certain embodiments, the one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop further comprise one or more elements selected from the group consisting of:


one or more valves adapted and configured to regulate the flow of the perfusate;


one or more filters adapted and configured to filter the perfusate; and


one or more sensors for measuring one or more properties of the perfusate selected from the group consisting of pH, dissolved oxygen concentration, dissolved carbon dioxide concentration, dissolved metabolite concentration, temperature, pressure, and flow rate.


In certain embodiments, the one or more sensors measure the concentration of at least one dissolved metabolite selected from the group consisting of nitric oxide, lactate, bicarbonate, oxygen, carbon dioxide, total hemoglobin, methemoglobin, oxyhemoglobin, carboxyhemoglobin, sodium, potassium, chloride, calcium, glucose, urea, ammonia, and creatinine.


In certain embodiments, the mammal perfusion apparatus comprises one or more sensors for measuring one or more properties of the perfusate selected from the group consisting of a pressure and a flow rate.


In certain embodiments, the one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop comprise one or more heat exchange units comprising:


one or more heat exchangers;


one or more temperature regulation units;


one or more temperature regulating pumps;


a thermoregulation fluid; and


one or more pipes configured and adapted to transport the thermoregulation fluid, wherein the one or more pipes are in fluidic communication with the one or more heat exchangers, the one or more temperature regulation units and the one or more temperature regulating pumps.


In certain embodiments, the one or more components selected from the group consisting of the brain enclosure unit, the venous loop, the filtration loop and the arterial loop comprise one or more sensors adapted and configured to measure the temperature within the perfusion device.


In certain embodiments, the one or more sensors are adapted and configured to measure the temperature within the perfusion device, the one or more temperature regulation units and the one or more temperature regulating pumps are in electronic communication with a computer programmed to regulate the temperature of the thermoregulation fluid and the specified flow rate of the one or more temperature regulating pumps to maintain a specified temperature within the perfusion device.


In certain embodiments, the hemodiafiltration unit is adapted and configured to supply one or more nutrients to the perfusate, selected from the group consisting of Glycine, L-Alanyl-Glutamine, L-Arginine hydrochloride, L-Cystine, L-Histidine hydrochloride-H2O, L-Isoleucine, L-Leucine, L-Lysine hydrochloride, L-Methionine, L-Phenylalanine, L-Serine, L-Threonine, L-Tryptophan, L-Tyrosine, L-Valine, Choline chloride, D-Calcium pantothenate, Folic Acid, Niacinamide, Pyridoxine hydrochloride, Riboflavin, Thiamine hydrochloride, i-Inositol, Calcium Chloride (CaCl2)-2H2O), Ferric Nitrate (Fe(NO3)3 9H2O), Magnesium Sulfate (MgSO4-7H2O), Potassium Chloride (KCl), Sodium Bicarbonate (NaHCO3), Sodium Chloride (NaCl), Sodium Phosphate monobasic (NaH2PO4-2H2O), D-Glucose (Dextrose), Phenol Red, Sodium Pyruvate, free fatty acids, cholesterol and nucleic acid constitutes.


In certain embodiments, the system is configured to perfuse the mammal with the perfusate at a cardiac pulsatile pressure of about 20 mmHg to about 140 mmHg.


In certain embodiments, the system is configured to perfuse the organs in the mammal with the perfusate through the pulse generator at a rate of about 40 to about 180 beats per minute.


In certain embodiments, the system further comprises a controller in electronic communication with one or more elements of the system.


In certain embodiments, the mammal is a deceased mammal. In certain embodiments, the mammal is a human. In certain embodiments, the deceased mammal is deceased for longer than 1 hour. In certain embodiments, the deceased mammal has been deceased for longer than 4 hours. In certain embodiments, the mammal died of cardiac arrest.


In certain embodiments, the organs in the deceased mammal are ischemic prior to perfusion with the isolated perfusate mixture.


In certain embodiments, rigor mortis is prevented. In certain embodiments, rigor mortis is reversed.


In certain embodiments, the perfusate mixture flows into the ophthalmic artery.


In certain embodiments, the perfusate mixture flows into the renal intralobular arteries.


BACKGROUND OF THE INVENTION

Cells lack meaningful oxygen-storage capacity, leading to obligate oxygen-dependence. At the cellular level, in just minutes following ischemia, intracellular acidosis and edema develop, and cause secondary damage to cellular membranes, organelles, and ultimately cell death. At the whole-body scale, there is a systemic release of hormones and cytokines, and activation of autonomic nervous, immune, and coagulation systems, leading to end-organ injury and feedback onto cellular injury cascades that culminate in systemic metabolic acidosis and hyperkalemia.


Reperfusion of the whole-body with autologous blood has several deleterious issues, including coagulation, microvascular plugging, inflammation, and blood-intrinsic cellular dysfunction. These obstacles have limited whole-body reperfusion and recovery of large mammals to 20 minutes of warm ischemia. Appropriate interventions are needed for molecular and cellular recovery across all vital organs in the large mammalian body following prolonged warm ischemia. The present invention addresses this need.





BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description of preferred embodiments of the invention will be better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there are shown in the drawings embodiments which are presently preferred. It should be understood, however, that the invention is not limited to the precise arrangements and instrumentalities of the embodiments shown in the drawings.



FIGS. 1A-1G show overview of the OrganEx technology and experimental workflow. FIG. 1A shows connection of the porcine body to the OrganEx perfusion system (or ECMO, not shown) via cannulation of the femoral artery and vein. FIG. 1B is a simplified schematic view of the OrganEx perfusion device. The system is equipped with a centrifugal pump, pulse generator, hemodiafiltration gas infusion, drug delivery systems, and sensors to measure metabolic and circulation parameters. FIG. 1C is a schematic of the experimental workflow and conditions. FIG. 1D, the lid of the flow chamber that is connected to the electronic pressure regulator via an air line and the barb connector. FIG. 1E, the bottom view of the lid showing in green space occupied by air. FIG. 1F, the isometric view of the body, in green is the fluid path (fluid space) occupied by the mixture of autologous blood and the perfusate. FIG. 1G, the side view of the lid, body and the membrane that separates two parts.



FIGS. 2A-2E show circulation and blood/perfusate properties during the perfusion protocols. FIGS. 2A-2B are representative images of abdominal fluoroscopy (FIG. 2A, n=9) and ophthalmic and renal ultrasound (FIG. 2B, n=6) at 3h of perfusion. ECMO is depicted on upper and OrganEx on lower panels. FIGS. 2C-2E show changes in total flow rate, brachial arterial pressure (FIG. 2C), percentage of venous O2 saturation (FIG. 2D), K+ concentration, and pH in serum (FIG. 2E) throughout the perfusion protocols; n=6. Data presented are mean S.E.M. Two-tailed unpaired t-test was performed. **P<0.01, ***P<0.001, NS: not significant.



FIGS. 3A-3K show analysis of tissue integrity across experimental conditions and organs. FIG. 3A show representative confocal images of immunofluorescent staining for neurons (RBFOX3/NeuN), astrocytes (GFAP), and microglia (IBA1) counterstained with DAPI nuclear stain in hippocampal CA1 region; n=3. Quantification of NeuN immunoreactivity intensity (FIG. 3B), number of GFAP fragments (FIG. 3C), and microglia number in CA1 (FIG. 3D). FIG. 3E are representative images of H&E staining in heart, liver, and kidney. FIGS. 3F-3H are related to evaluation of histopathological criteria that include nuclear pyknosis (arrow), tissue integrity (*), hemorrhage/congestion (empty arrowhead), cell vacuolization (full arrowhead), and tissue edema (double arrow) in heart (FIG. 3F), liver (FIG. 3G) and kidney (FIG. 3H); n=5. FIGS. 3F-3H are representative confocal images of immunofluorescent staining for ACTB in kidney (FIG. 3I) and its quantification in glomerulus (FIG. 3J) and proximal convoluted tubule (PCT) (FIG. 3K); n=3. Scale bars, 40 m. Data presented are mean S.E.M. One-way ANOVA with post-hoc Dunnett's adjustments was performed. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 4A-4P show analysis of cell death across experimental conditions and organs. FIGS. 4A, 4F, 4K, and 4N, Representative confocal images of immunofluorescent staining for activated caspase 3 (actCASP3) and TUNEL assay in heart, liver, kidney, and brain. FIGS. 4B-4D, Quantification of actCASP3 immunolabeling signal intensity in heart (FIG. 4B), liver (FIG. 4C), and kidney (FIG. 4D). FIGS. 4G-4J, Normalized total intensity of TUNEL signal in heart (FIG. 4G), liver (FIG. 4H), and kidney (FIG. 4I). FIGS. 4L and 4M, Percentage of actCASP3 positively stained nuclei in the CA1 (FIG. 4L) and PFC (FIG. 4M). FIGS. 4O and 4P, Normalized total intensity of TUNEL signal in CA1 (FIG. 4O) and PFC (FIG. 4P). Scale bars, 50 m. Data presented are mean S.E.M. One-way ANOVA with post-hoc Dunnett's adjustments was performed. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIG. 5A-5K depict functional characterization and metabolic activity of selected organs. FIGS. 5A-5C, complexes in ECMO and OrganEx treated animals 3 hours into the perfusion (left); Chi-squared test was performed. Representative EKG trances in OrganEx and ECMO group 3 hours into the perfusion (right). FIG. 5E, Measurement of cardiomyocyte contraction velocity in acute heart slices in the Oh WIT, OrganEx, and ECMO groups (left), and cardiomyocyte contraction duration (right); n=5. FIG. 5F, Representative confocal images of immunolabeling for albumin in liver. Scale bars, 50 μm. FIG. 5G, Measurement of normalized immunolabeling signal intensity of albumin in liver demonstrating similar expression between OrganEx and Oh WIT groups; n=3. FIG. 5H, Representative images of organotypic hippocampal slices after 14 days in culture. Scale bar, 500 m. FIG. 5I, Quantification of hippocampal slice integrity; n=4-5. FIG. 5J, Representative confocal images of newly synthesized proteins (AHA, Click-iT chemistry) with DAPI counterstaining in the long-term organotypic hippocampal slice culture. Scale bar, 100 m. FIG. 5K, Quantification of AHA relative intensity in the CA1; n=3-5. Data presented are mean±S.E.M. One way ANOVA was performed with post-hoc Dunnett's adjustments was performed. *P<0.05, **P<0.01, ***P<0.001, NS: not significant. AU, arbitrary units.Measurement of 2-NBDG uptake in heart (FIG. 5A), kidney (FIG. 5B), and brain (FIG. 5C); n=3. FIG. 5D, Observed QRS.



FIGS. 6A-6D show organ and cell type-specific transcriptomic changes assessed by snRNA-seq across various warm ischemia intervals and different perfusion interventions. Upper panels: UMAP layout showing major t-types in the hippocampus (FIG. 6A), heart (FIG. 6B), liver (FIG. 6C), and kidney (FIG. 6D). Middle panels: comparison of averaged Augur AUC scores across t-types indicating which cell type underwent the most transcriptomic changes; Lower panels: dot plots depicting P values of gene set enrichment of gene sets important in cellular recovery and specific cellular functions in major respective t-types. **P<0.01, ***P<0.001.



FIGS. 7A-7E show analysis of circulation and blood/perfusate properties after 1 h of warm ischemia and perfusion interventions. FIG. 7A, Representative fluoroscopy images of autologous blood flow (ECMO intervention, up) or a mixture of autologous blood and the perfusate (OrganEx intervention, below) in the head captured after 3 and 6 hours respectively of perfusion, showing robust restoration of the circulation in the OrganEx group. A contrast catheter was placed in the left common carotid artery (CCA), except in the ECMO group at 6 hours timepoint where contrast catheter could not be advanced beyond aortic arch in to the left CCA due to pronounced vasoconstriction, thus resulting in bilateral CCA filling. n=6. FIG. 7B, Representative color Doppler images of the CCA demonstrating robust flow in OrganEx group. Ultrasound waveform analysis demonstrated that OrganEx produced pulsatile, biphasic flow pattern (lower panel). SCM, sternocleidomastoid muscle. n=6. FIG. 7C, Longitudinal change in arterial and venous cannula pressures throughout the perfusion demonstrating robust perfusion in OrganEx group. FIG. 7D, Time-dependent changes in oxygen delivery and consumption demonstrating increased oxygen delivery and stable oxygen consumption over the perfusion period in OrganEx group. FIG. 7E, Presence of classical signs of death (rigor and livor mortis) in ECMO as compared to OrganEx group at the experimental endpoint. Data presented are mean S.E.M. Two-tailed unpaired t-test was performed. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 8A-8L show Nissl staining and immunohistochemical analysis of the hippocampal CA1 region and the prefrontal cortex (PFC). FIG. 8A, Representative images of Nissl staining of the CA1 (up) and PFC (below). FIGS. 8B and 8C, Quantification of the number of cells per standardized area (FIG. 8B) and percentage of ellipsoid cells per area (FIG. 8C) in the CA1 between the experimental groups. FIGS. 8D and 8E, Quantification of the number of cells per standardized area (FIG. 8D) and percentage of ellipsoid cells per area (FIG. 8E) in the PFC between the experimental groups. FIGS. 8F and 8H, Representative confocal images of immunofluorescent staining for neurons (RBFOX3/NeuN), astrocytes (GFAP), and microglia (IBA1) counterstained with DAPI nuclear stain in CA1 (FIG. 8F) and PFC (FIG. 8H). FIG. 8G, Quantification of GFAP immunoreactivity in hippocampal CA1 region depicting comparable immunoreactivity between OrganEx and Oh WIT group, with a significant increase compared to the other groups. FIGS. 8I-8L Quantification of NeuN immunolabeling intensity (FIG. 8I), number of GFAP+ fragments (FIG. 8J), and number of GFAP+ cells (k) depict similar trends between the groups as seen in the CAL. Microglia number (FIG. 8L) shows comparable results between OrganEx and Oh WIT with different dynamics seen in the ECMO group. Scale bars, 50 m. Data presented are mean S.E.M. One-way ANOVA with post-hoc Dunnett's adjustments was performed. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 9A-9J show representative images of H&E staining across assessed peripheral organs and kidney periodic acid-Schiff (PAS) staining and immunolabeling for HACVR1 and Ki-67. FIG. 9A, Representative images of the H&E staining in heart, kidney, liver, pancreas, and lungs. Arrows point to nuclear damage, asterisks point to disrupted tissue integrity, empty arrowheads point to hemorrhage, full arrowheads point to cell vacuolization, double arrows point to tissue edema. FIGS. 9B and 9C, H&E histopathological scores in lungs (FIG. 9B) and pancreas (FIG. 9C). FIG. 9D, Representative images of PAS staining of the kidney. Arrows point to disrupted brush border, full arrowheads point to the presence of casts, asterisks point to tubular dilation, double arrows point to the Bowman space dilation. FIG. 9E, Kidney PAS histopathological damage score. FIG. 9F and FIG. 9H, Representative confocal images of immunofluorescent staining for HAVCR1 and Ki-67 in kidney, respectively. FIG. 9G, Quantification of HAVCR1 immunolabeling signal intensity. FIG. 9I and FIG. 9J, Quantification of the kidney Ki-67 positive staining. HACVR1 and Ki-67 immunolabeling quantification results follow a similar pattern seen with other organs with comparable results between Oh WIT and OrganEx group and significant decrease in the 7h WIT and ECMO groups. Scale bars, 100 μm. Data presented are mean±S.E.M. One-way ANOVA with post-hoc Dunnett's adjustments was performed. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, NS: not significant.



FIGS. 10A-10O show evaluation of different cell death pathways by immunohistochemical staining for important molecules in pyroptosis (IL1B), necroptosis (RIPK3) and ferroptosis (GPX4) across the experimental conditions. FIGS. 10A, 10F, 10K, Representative confocal images of immunofluorescent staining for pyroptosis marker IL1B, necroptosis marker RIPK3, and ferroptosis marker GPX4, each co-stained with DAPI nuclear stain in CA1, heart, liver, and kidney. FIGS. 10B-10E, Quantification of IL1B immunolabeling signal intensity in CA1 (FIG. 10B), heart (FIG. 1C), liver (FIG. OD), and kidney (FIG. 10E). FIGS. 10G-10J, Quantification of RIPK3 positive intranuclear co-staining in CA1 (FIG. 10G), and immunolabeling signal intensity heart (FIG. 10H), liver (FIG. 10I), kidney (FIG. 10J). FIGS. 10L-10O, Quantification of GPX4 immunolabeling signal intensity in CA1 (FIG. 10L), heart (FIG. 10M), liver (FIG. 10N), and kidney (FIG. 10O). Scale bars, 50 μm left and right panels. Data presented are mean S.E.M. One-way ANOVA with post-hoc Dunnett's adjustments was performed. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, ***P<0.001, NS: not significant, IN: intranuclear.



FIGS. 11A-11O EEG setup and recordings, click-iT chemistry and immunohistochemical analysis of factor V and troponin I. FIG. 11A, Placement of EEG electrodes on the porcine scalp. FIG. 11B, Representative snapshot of the EEG recordings after administration of anesthesia and before the induction of cardiac arrest by ventricular fibrillation. FIG. 11C, Representative snapshot of the EEG recordings immediately following the ventricular fibrillation. FIG. 11D, Representative snapshot of the EEG during ECMO intervention at around 2h of perfusion protocol. FIG. 11E, Representative snapshot of the EEG during OrganEx intervention at around 2h of perfusion protocol, showing a light pulsatile artefact. FIGS. 11F and 11G, Representative snapshot of the EEG recordings following contrast injection at 3h in ECMO and OrganEx animals, respectively. OrganEx EEG snapshot is consistent with a possible muscle-movement artefact. GND, ground electrode; REF, reference electrode. FIGS. 11H and 11I, Representative confocal images of AHA through Click-iT chemistry in newly synthesized proteins with DAPI nuclear stain in the long-term organotypic hippocampal slice culture in CA3 (FIG. 11H) and DG (FIG. 11AI) subregions. FIGS. 11J and 11K, Relative intensity of nascent protein around nuclei in hippocampal CA3 (FIG. 11J) and DG (FIG. 11K) region showing comparable protein synthesis between OrganEx and Oh WIT up to 14 days in culture. FIG. 11L, Representative confocal images of immunofluorescent staining for troponin I in the heart. FIG. 11M, Quantification of troponin I immunolabeling signal intensity in heart. A decreased trend in immunolabeling intensity was observed with ischemia time and a significant decrease in immunolabeling intensity in ECMO compared to the OrganEx group. FIG. 11N, Representative confocal images of immunofluorescent staining for factor V in liver. FIG. 11O, Quantification of factor V immunolabeling signal intensity in liver follows a similar pattern seen with other organs with comparable results between Oh WIT, 1h WIT, and OrganEx group and a significant decrease in 7h WIT and ECMO groups. Scale bars, 50 m. Data presented are mean S.E.M. For more detailed information on statistics and reproducibility, see methods. *P<0.05, **P<0.01, NS. not significant. AU, arbitrary units.



FIGS. 12A-12F Quality control of snRNA-seq data in healthy and varying ischemic conditions in the hippocampus, heart, liver, and kidney. Through transcriptomic integration and iterative clustering, a taxonomy of t-types in healthy organs and brain, heart, liver, and kidney that experienced ischemia (1h WIT, 7h WIT, ECMO and OrganEx) were generated, representing presumptive major cell types across organs of interest. These major t-types were further subdivided into high-resolution subclusters that were transcriptomically comparable to publicly available human and mouse single-cell datasets and that were marked by distinct expression profiles. FIG. 12A, Bar plot showing the number of cells/nuclei across organs and biological replicates. FIG. 12B, Violin plot showing the distribution of the number of unique molecular identifiers—UMIs (upper panel) and genes (lower panel) detected across all biological replicates.



FIGS. 12C-12F, respective analyses of snRNA-seq in the hippocampus (FIG. 12C), heart (FIG. 12D), liver (FIG. 12E), and kidney (FIG. 12F). The left upper corner depicts detailed UMAP layout showing all t-types in the respective organs. The right side depicts the expression of top t-type markers. The left lower corner depicts transcriptomic correlation between the t-type taxonomy defined in this study and that of previous human and mouse datasets.



FIGS. 13A-13D Single-nucleus transcriptome analysis in healthy and varying ischemic conditions in the hippocampus (FIG. 13A), heart (FIG. 13B), liver (FIG. 13C), and kidney (FIG. 13D). FIGS. 13A-13D, From left to right: UMAP layout showing major t-types; UMAP layout, colored by Augur cell type prioritization (AUC) between Oh WIT compared to 1h (up) and 7h WIT (down); statistical comparison of Augur AUC scores between Oh WIT and 1h (up) and 7h (down) of WIT; Volcano plot showing top DEGs in major annotated t-types between Oh and 1h WIT (up), or Oh and 7h WIT (down); GO terms associated with the genes up and downregulated in detected nuclei between Oh and 1h WIT (up), or Oh and 7h WIT (down) with their nominal P-value in respective major annotated t-types.



FIGS. 14A-14H show hippocampal single-nucleus transcriptome analysis comparing OrganEx to other experimental conditions. FIG. 14A, AUC scores of the Augur cell type prioritization between OrganEx and other groups. FIG. 14B, Volcano plot showing DEGs in hippocampal neurons between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. FIG. 14C, Trajectories of hippocampal neurons. Color indicates different experimental groups. FIG. 14D, Sankey plot showing perfusate components and violin plots showing their effects on hippocampal neurons between the OrganEx and ECMO groups. FIG. 14E, Hierarchical clustering of the top DEGs across experimental groups and derived functional gene modules (upper left). Eigengene average expression trends exhibit distinct trends between ECMO and OrganEx groups (upper right) of modules whose enriched GO terms are predominantly related to cellular function (below) (FIG. 34). FIG. 14F, Expression of the genes involved in cell-death pathways in neurons. FIG. 14G, Gene expression enrichment of the genes involved in cell-death pathways in neurons. FIG. 14H, Overall signaling patterns across all experimental conditions. Genes important in inflammation are highlighted gray. i, Stacked bar plot showing relative information flow for each signaling pa pathway across experimental group pairs. Significant signaling pathways were ranked based on differences in the overall information flow within the inferred networks between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. Genes important in inflammation are highlighted gray. Necro-1, necrostatin-1; Mino, minocycline; DEXA, dexamethasone; Met. B, methylene blue; GEE, Glutathione Ethyl Ester. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 15A-15H show heart single-nucleus transcriptome analysis comparing OrganEx to other experimental conditions. FIG. 15A, AUC scores of the Augur cell type prioritization between OrganEx and other groups. FIG. 15B, Volcano plot showing the DEGs in cardiomyocytes between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. FIG. 15C, Trajectories of hippocampal neurons. Color indicates different experimental groups. FIG. 15D, Sankey plot showing perfusate components and violin plots showing their effects on cardiomyocytes between the OrganEx and ECMO groups. FIG. 15E, Hierarchical clustering of the top DEGs across experimental groups and derived functional gene modules (upper left). Eigengene average expression trends exhibit distinct trends between ECMO and OrganEx groups (upper right) of modules whose enriched GO terms are predominantly related to cellular function (below) (FIG. 34). FIG. 15F, Expression of the genes involved in cell-death pathways in cardiomyocytes. FIG. 15G, Gene expression enrichment of the genes involved in cell-death pathways in cardiomyocytes. FIG. 15H, Overall signaling patterns across all experimental conditions. Genes important in inflammation are highlighted gray. i, Stacked bar plot showing relative information flow for each signaling pathway across experimental group pairs. Significant signaling pathways were ranked based on differences in the overall information flow within the inferred networks between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. Genes important in inflammation are highlighted gray. HIP, hippocampus; Necro-1, necrostatin-1; Mino, minocycline; DEXA, dexamethasone; Met. B, methylene blue; GEE, Glutathione Ethyl Ester. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 16A-16I show liver single-nucleus transcriptome analysis comparing OrganEx to other experimental conditions. FIG. 16A, AUC scores of the Augur cell type prioritization between OrganEx and other groups. FIG. 16B, Volcano plot showing DEGs in hepatocytes between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. FIG. 16C, Trajectories of hippocampal neurons. Color indicates different experimental groups. FIG. 16D, Sankey plot showing perfusate components and violin plots showing their effects on hepatocytes between the OrganEx and ECMO. FIG. 16E, Hierarchical clustering of the top DEGs across experimental groups and derived functional gene modules (upper left). Eigengene average expression trends exhibit distinct trends between ECMO and OrganEx groups (upper right) of modules whose enriched GO terms are predominantly related to cellular function or cell death (below) (Table 23). FIG. 16F, Expression of the genes involved in cell-death pathways in hepatocytes. FIG. 16G, Gene expression enrichment of the genes involved in cell-death pathways in hepatocytes. FIG. 16H, Overall signaling patterns across all experimental conditions. Genes important in inflammation are highlighted gray. FIG. 16A I, Stacked bar plot showing relative information flow for each signaling pathway across experimental group pairs. Significant signaling pathways were ranked based on differences in the overall information flow within the inferred networks between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. Genes important in inflammation are highlighted gray. Necro-1, necrostatin-1; Mino, minocycline; DEXA, dexamethasone; Met. B, methylene blue; GEE, Glutathione Ethyl Ester. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.



FIGS. 17A-17I show kidney single-nucleus transcriptome analysis comparing OrganEx to other experimental conditions. FIG. 17A, AUC scores of the Augur cell type prioritization between OrganEx and other groups. FIG. 17B, Volcano plot showing DEGs in PCT between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. FIG. 17C, Trajectories of hippocampal neurons. Color indicates pseudotime progression and different cell states, respectively. FIG. 17D, Sankey plot showing perfusate components and violin plots showing their effects on PCT between the OrganEx and ECMO groups. FIG. 17E, Hierarchical clustering of the top DEGs across experimental groups and derived functional gene modules (upper left). Eigengene average expression trends exhibit distinct trends between ECMO and OrganEx groups (upper right) of modules whose enriched GO terms are predominantly related to cellular function or cell death (below) (FIG. 34). FIG. 17F, Expression of the genes involved in cell-death pathways in PCT. FIG. 17G, Gene expression enrichment of the genes involved in cell-death pathways in PCT. PCT, proximal convoluted tubule. FIG. 17H, Overall signaling patterns across all experimental conditions. Genes important in inflammation are highlighted gray. FIG. 17I, Stacked bar plot showing relative information flow for each signaling pathway across experimental group pairs. Significant signaling pathways were ranked based on differences in the overall information flow within the inferred networks between OrganEx and Oh WIT, 1h WIT, 7h WIT, and ECMO. Genes important in inflammation are highlighted gray. PCT, proximal convoluted tubules; DCT, distal convoluted tubules; Necro-1, necrostatin-1; Mino, minocycline; DEXA, dexamethasone; Met. B, methylene blue; GEE, Glutathione Ethyl Ester. *P<0.05, **P<0.01, ***P<0.001, NS: not significant.





DETAILED DESCRIPTION OF THE INVENTION

The invention provides a novel system for restoration and preservation of an intact mammalian organs. In certain aspects, the system is capable of preserving organs in the mammalian body and restoring and maintaining cellular integrity and cellular function for hours post mortem or after global ischemia. The invention also provides novel synthetic organ perfusate formulations, and methods of mixing the perfusate with blood, for example, autologous blood, derived from the mammal.


The invention includes surgical methods and procedures to connect the mammal to the OrganEx system. In combination, the system, perfusate, and surgical method attenuate organ cell death, preserve anatomical and cellular integrity and restore cellular function as indicated by active metabolism. The invention also provides means to reduce reperfusion injury, stimulate recovery from hypoxia, and metabolically support the energy needs of organ function. The invention further provides methods of using the system and blood perfusate mixture, to prevent the collapse of organ vasculature and to allow for better perfusion of the organs. In addition, the invention provides methods to prevent the onset of rigor mortis.


Definitions

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, exemplary methods and materials are described. As used herein, each of the following terms has the meaning associated with it in this section.


The instant invention is most clearly understood with reference to the following definitions.


As used herein, the singular form “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.


Unless specifically stated or obvious from context, as used herein, the term “about” is understood as within a range of normal tolerance in the art, for example within 2 standard deviations of the mean. “About” can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from context, all numerical values provided herein are modified by the term about.


As used herein, the term “hypoxic” refers to a concentration of dissolved oxygen less than about 13%, corresponding to a partial pressure of about 100 mmHg, the physiologic partial pressure of oxygen in the alveoli of the lung.


As used herein, the term “cellular hypoxia” refers to a cellular response to exposure to a hypoxic environment, often resulting in apoptosis, or cellular death.


As used herein, the term “anaerobic metabolism” refers to the cellular consumption of glucose to produce two molecules of lactate, with the lactate remaining in dissolved in solution. The ratio of lactate produced to glucose consumed will be 2:1.


As used herein, the term “aerobic metabolism” refers to the cellular consumption of glucose to produce two molecules of lactate, both of which will be consumed through the Krebs cycle in the presence of sufficient levels of oxygen. The ratio of lactate produced to glucose consumed will be 0:1.


As used herein, the term “hypothermic” refers to a body temperature substantially below normal bounds. Hypothermic temperatures include, but are not limited to, temperatures between 10° and 32° C., between 20° C. and 30° C., and about 28° C.


As used herein, the term “salt” embraces addition salts of free acids or free bases that are compounds useful within the invention. Suitable acid addition salts may be prepared from an inorganic acid or from an organic acid. Examples of inorganic acids include hydrochloric, hydrobromic, hydriodic, nitric, carbonic, sulfuric, phosphoric acids, perchloric and tetrafluoroboronic acids. Appropriate organic acids may be selected from aliphatic, cycloaliphatic, aromatic, araliphatic, heterocyclic, carboxylic and sulfonic classes of organic acids, examples of which include formic, acetic, propionic, succinic, glycolic, gluconic, lactic, malic, tartaric, citric, ascorbic, glucuronic, maleic, fumaric, pyruvic, aspartic, glutamic, benzoic, anthranilic, 4-hydroxybenzoic, phenylacetic, mandelic, embonic (pamoic), methanesulfonic, ethanesulfonic, benzenesulfonic, pantothenic, trifluoromethanesulfonic, 2-hydroxyethanesulfonic, p-toluenesulfonic, sulfanilic, cyclohexylaminosulfonic, stearic, alginic, b-hydroxybutyric, salicylic, galactaric and galacturonic acid. Suitable base addition salts of compounds useful within the invention include, for example, metallic salts including alkali metal, alkaline earth metal and transition metal salts such as, for example, lithium, calcium, magnesium, potassium, sodium and zinc salts. Acceptable base addition salts also include organic salts made from basic amines such as, for example, N,N′-dibenzylethylenediamine, chloroprocaine, choline, diethanolamine, ethylenediamine, meglumine (N-methyl-glucamine) and procaine. All of these salts may be prepared by conventional means from the corresponding free base compound by reacting, for example, the appropriate acid or base with the corresponding free base.


As used in the specification and claims, the terms “comprises,” “comprising,” “containing,” “having,” and the like can have the meaning ascribed to them in U.S. patent law and can mean “includes,” “including,” and the like.


Unless specifically stated or obvious from context, the term “or,” as used herein, is understood to be inclusive.


Ranges provided herein are understood to be shorthand for all of the values within the range. For example, a range of 1 to 50 is understood to include any number, combination of numbers, or sub-range from the group consisting 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, or 50 (as well as fractions thereof unless the context clearly dictates otherwise).


As described herein, rigor mortis refers to process that sets in upon the death of a mammal. Rigor mortis is characterized by stiffening of the muscles. Stiffening occurs as a result of ATP depletion. ATP is depleted in ischemic tissues where there is insufficient oxygen available for mitochondria to drive ATP formation. As a result, the bridges between actin and myosin fibers are no longer broken, causing muscle stiffness.


As used herein, OrganEx refers to a system that consists of a perfusion system and synthetic perfusate. The perfusion system consists of a computer driven custom-made pulse generator connected to a centrifugal pump, which enables reproduction of physiological pressure and flow waveforms, together with automated hemodiafiltration, gas mixer, and drug delivery systems which allow control of blood coagulation and supplementation of the perfusate. To ensure homeostasis and maintain the targeted perfusion parameters, the perfusion system is also equipped with sensors for electrolytes, blood gases, metabolic parameters, hemoglobin, vessels and cannulas pressures, and total circulatory flow rate. In the OrganEx system, prior to the initiation of the perfusion protocol, autologous blood of the mammal is drained into the OrganEx system and mixed with the perfusate, which is then used to perfuse the animal.


As used herein, ECMO refers to a clinical standard of a heart-and-lung substitution perfusion device—extracorporeal membrane oxygenation system (ECMO). In the ECMO system, the animals are perfused with autologous blood.


The following abbreviations are used herein:

    • ABG arterial blood gasses
    • ACT activated clotting time
    • actCASP3 activated caspase 3
    • AHA azidohomoalanine amino acid
    • AUC Augur cell type prioritization
    • CA1 hippocampal subregion
    • CA3 hippocampal subregion
    • CCA common carotid artery
    • CYP cytochrome microsomal
    • DAPI 4′,6-diamidino-2-phenylindole
    • DEG Differentially expressed genes
    • DG hippocampal subregion
    • DMEM Dulbecco's Modified Eagle Medium
    • DNA deoxyribonucleic acid
    • ECMO extracorporeal membrane oxygenation system
    • EEG electroencephalogram
    • EKG electrocardiogram
    • GFAP Glial fibrillary acidic protein
    • GO Gene ontology
    • HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid
    • IBA-I marker for microglia
    • IL Interlobular artery
    • 2-NBDG glucose analog
    • OA Ophthalmic Artery
    • PBS Phosphate buffered saline
    • PCT proximal convoluted tubule
    • PCA principal component analysis
    • PFC prefrontal cortex
    • PMI post-mortem intervals
    • RA right atrium
    • RBFOX3/NeuN marker for mature neurons
    • RC Renal cortex
    • RM Renal medulla
    • RO Retro orbital
    • ROI region of interest
    • RT room temperature
    • SCM sternocleidomastoid muscle
    • SCT subcutaneous tissue
    • TUNEL Terminal deoxynucleotidyl transferase dUTP Nick End Labeling
    • UMAP uniform manifold approximation and projection
    • UMI unique molecular identifier
    • VFib ventricular fibrillation
    • WIT warm ischemia time


OrganEx Perfusate and Uses

The invention provides a novel OrganEx technology and its experimental application that has the potential for recovery of key molecular and cellular processes in multiple porcine organs after prolonged warm ischemia.


The data presented herein demonstrate that mammalian cells are more resilient to ischemic injury than previously understood. Further, the data establish that cellular deterioration is a more protracted process that is not scripted within narrowly-defined sequences or timeframes.


In one embodiment, the application of the OrganEx technology can halt the process of cell demise. In another embodiment, the application of the OrganEx technology can shift cellular states towards recovery at molecular and cellular levels. In another embodiment, the application of the present invention can shift cellular states towards recovery, even following prolonged warm ischemia. In another embodiment, the invention provides a comprehensive single-cell transcriptomic analysis of the brain and vital peripheral organs over varying warm ischemic intervals. In another embodiment, the comprehensive single-cell transcriptomic analysis of the brain and vital peripheral organs over varying warm ischemic intervals is obtained utilizing perfusion with either autologous blood, the OrganEx perfusate, or a mixture of autologous blood and the OrganEx perfusate.


In some embodiments, the invention provides a transcriptome dataset and a unique resource for future basic and translational studies on cell-types, organs and ischemia.


In one embodiment, the OrganEx platform and acellular perfusate, connected to an intact dead mammal, provides a solution to the problem of ischemic stress in tissue culture and isolated organs.


The invention provides a means to reinstate circulation and systemic metabolic parameters across multiple organs in an intact animal. In one embodiment, the invention provides for the removal of deleterious processes and lack of oxygen, crucial for the control of multiple non-specific injury mechanisms affecting end-organ recovery and overall prognosis after global ischemia.


In one embodiment, the invention facilitates or enables repair responses at the molecular and cellular level in several or all organs. In another embodiment, the repair at the molecular and cellular level translate to processes supporting recovery of organs. In another embodiment, recovery of organs last for an extended period of time. In another embodiment, rigor mortis can be prevented in an animal following warm ischemia. In another embodiment, rigor mortis can be reversed. In another embodiment, dead spots in the heart can be prevented. In another embodiment, electrical activity can be measured in the heart. In another embodiment, contractile activity can be measured in the heart. In another embodiment, electrical activity can be measured in the brain. In another embodiment, the movements can be initiated in the animal. In another embodiment, the animal may regain consciousness. In another embodiment, the animal may regain the ability to move.


In one embodiment, enduring effects on cellular recovery post perfusion occurs in slices from the tissue most susceptible to ischemia, the hippocampus. In another embodiment, long term in vivo recovery of the hippocampus, and other organs is observed at the organ level.


In one embodiment, long OrganEx perfusions of the whole-body can prevent organs from undergoing ischemic injury. In another embodiment, long OrganEx perfusion can lead to recovery of vital organs, including the brain, the hearth, the kidney, the pancreas, or the liver.


In another embodiment, the OrganEx technology can be used in combination with mammals that are still alive. In one embodiment, the live mammal is a human. In one embodiment, the live mammal being treated has experienced a stroke or a heart attack prior to perfusion with the blood perfusate mixture. In one embodiment, the human recovers and/or recovers more quickly from the stroke or the heart attack. In one embodiment, the invention preserves and recovers brain function. In one embodiment, the recovery from ischemic injury in the brain is measurable by magnetic resonance imaging (MRI). In one embodiment, long OrganEx perfusion can be applied to the mammal, e.g., a human, following a cardiac event, e.g., a heart attack. In one embodiment, the invention preserves and recovers heart function. In one embodiment, the mammal recovers and/or recovers more quickly from the heart attack. In one embodiment, the recovery from ischemic injury in the heart is measurable with an electrocardiogram (EKG). In another embodiment, death of a mammal may be reversed.


In one embodiment, the technology provides for new avenues for whole-body global ischemia research. In another embodiment, the invention provides a means to conduct clinical resuscitation science or transplantation medicine. In one embodiment, the invention provides for larger donor organ pools by recovering previously marginalized organs.


The invention includes a novel perfusion composition for the preservation of organs in the mammalian body. In certain embodiments, the perfusion composition can be used to preserve organs in a mammal after warm ischemia. In certain embodiments, the blood perfusate mixture can preserve the brain, the liver, lung, heart, pancreas, kidney, and the like.


In certain embodiments, the perfusion composition is a perfusate comprising a solution comprising one or more artificial oxygen carrier compounds and one or more compounds selected from the group consisting of anti-cytotoxic compounds, antioxidants, anti-inflammatory compounds, antiepileptic compounds, anti-apoptotic compounds, antibiotics, cell death inhibitors, neuroprotectants and oxidative/nitrosative stress inhibitors.


In certain embodiments, the perfusate comprises priming solution. In certain embodiments, the priming solution comprises sodium chloride, sodium bicarbonate, magnesium chloride, calcium chloride, glucose and dextrane. In certain embodiments, the concentrations of the components in the priming solutions is as shown in Table 1.


In certain embodiments, the perfusate comprises hemodiafiltration exchange solution. In certain embodiments, the hemodiafiltration exchange solution comprises one or more amino acids selected from the group consisting of glycine, L-alanyl-glutamine, L-arginine, L-cysteine, L-histidine, L-isoleucine, L-leucine, L-lysine, L-methionine, L-phenylalanine, L-serine, L-threonine, L-tryptophan, L-tyrosine, L-valine and salts and solvates thereof; one or more vitamins selected from the group consisting of choline, D-calcium pantothenate, folic acid, niacinamide, pyridoxine, riboflavin, thiamine, i-inositol and salts and solvates thereof; and one or more inorganic salts selected from the group consisting of calcium chloride, ferric nitrate, magnesium sulfate, potassium chloride, sodium bicarbonate, sodium chloride, sodium phosphate and salts and solvates thereof. In certain embodiments, the concentration of the components in the hemodiafiltration solution is as shown in Table 2.


In certain embodiments, the perfusate contains hemoglobin glutamer-250 (Hemopure @(HBOC-250)) or an alternative oxygen carrier, one or more cytoprotective agents selected from Hexahydro-2-imino-1H-thieno[3,4-d]imidazole-4-pentanoic acid (2-Iminobiotin), 5-(1H-Indol-3-ylmethyl)-3-methyl-2-thioxo-4-Imidazolidinone (Necrostatin-1), Sodium 3-Hydroxybutyric Acid, Glutathione Monoethyl Ester, Minocycline, Lamotrigine, 5-(2,6-Difluorophenoxy)-3-[[3-methyl-I-oxo-2-[(2-quinolinylcarbonyl)amino]butyl]amino]-4-oxo-pentanoic acid hydrate (QVD-Oph), Methylene Blue, and one or more antibiotics and anti-inflammatory agents selected from Ceftriaxone, Dexamethasone, and Cetirizine. In certain embodiments, the concentrations of the components recited above is listed in Table 3.


In certain embodiments, the perfusate comprises one or more artificial oxygen carrier compounds. In certain embodiments, the one or more artificial oxygen carrier compounds are hemoglobin derivatives. The hemoglobin derivatives can be one or more compounds selected from the group consisting of isolated, cell-free hemoglobin, cross-linked hemoglobin, polymerized hemoglobin, encapsulated hemoglobin and functionalized hemoglobin. In certain embodiments, the artificial oxygen carrier compound can be hemoglobin glutamer-250 (HEMOPURE®), a cross-linked hemoglobin tetramer comprising two alpha hemoglobin and two beta hemoglobin subunits cross-linked by a carbon linker. In other embodiments, the one or more artificial oxygen carrier compounds can be artificial red blood cell substitutes, such as ERYTHROMER™, PolyHeme, Oxyglobin, PolyHb-SOD-CAT-CA, PolyHb-Fibrinogen, Hemspan or MP4. In other embodiments, the artificial oxygen carrier compound can be any blood substitute compound known in the art.


In certain embodiments, the perfusion composition comprises one or more compounds selected from the group consisting of anti-cytotoxic compounds, antioxidants, anti-inflammatory compounds, antiepileptic compounds, anti-apoptotic compounds, antibiotics, cell death inhibitors, neuroprotectants and nitrite stress inhibitors. In certain embodiments, the perfusion composition comprises at least one imaging contrast agent. In other embodiments, the perfusion composition further comprises one or more ultrasound contrast agents, that also can be used under certain ultrasound settings as clot disintegrator and blood-brain barrier opener. In some embodiments, the one or more ultrasound contrast agents can be micrometer-sized air-filled polymeric particles. In yet other embodiments, the perfusion composition comprises at least one MRI contrast agent or CT contrast agent. In other embodiments, the perfusion composition comprises one or more compounds selected from the group consisting of the compounds of Tables. 1-3, or salts, solvates, tautomers, and prodrugs thereof.


Perfusion System

The invention provides a novel system for in situ hypothermic preservation of organs in a mammalian body.


In certain embodiments, the invention provides a system for the hypothermic, in situ preservation system, the system comprising: a perfusion device for the perfusion of a mammalian body, comprising a means for regulating the temperature, flow, pressure, dissolved gases, and concentration of metabolites in the system; and the perfusate composition of the invention. In certain embodiments, the means for regulating the temperature of the system comprises a controller programmed to regulate at least a perfusate temperature within the system to maintain hypothermic conditions. In certain embodiments, the means for regulating the flow, pressure, dissolved gases, and metabolite concentrations in the system comprises a controller programmed to regulate these parameters within the system to maintain constant or alterable levels/concentrations.


In certain embodiments, the system is configured to introduce oxygen to a perfusate of the invention and circulate the perfusate through mammal. In certain embodiments, the perfusion unit is adapted and configured to introduce oxygen and carbon dioxide to the perfusate. In other embodiments, the perfusion unit is adapted and configured to dialyze the perfusate.


In certain embodiments, the system comprises an intrarenal arterial cannula, an animal input line, a pressure sensor, a flow sensor, a pulse generator, an arterial oxygenator, an exchange solution, one or more roller pumps, a hemodiafiltration membrane, one or more reservoirs with perfusate drugs, one or more perfusate reservoirs, a pressure senor, a centrifugal pump, a hemoglobin sensor a return line from the mammal.


In certain embodiments, the electronic components of the perfusion system are built in a modular manner. Each sensor, motor or electronic component that requires external control has a separate logical controller built on Arduino Uno platform, local circuits and software. Each logical controller has a serial output and input and is connected via com port to the computer. In certain embodiments, the computer has modulus, scripts and functions written in Python that either control or collect data from these logical controllers.


In certain embodiments, the pulse generator consists of (1) 3D printed flow chamber (fluid space for blood/perfusate passage, and air space that is separated by a membrane from the fluid space and can change volume against fluid space) connected to the main circuit, downstream from the centrifugal pump, (2) high resolution electronic pressure regulator (0-10 PSI) which is connected to the air source on one end and to the flow chamber on the opposite end, (3) logical controller regulating electronic pressure regulator, (4) and a computer with control software. The Logical controller is made out of Arduino Uno microprocessor board and has a DAC converter (MCP 4725) with an operational amplifier (LT1215 CN8); it produces continuous analog output (0-10V) for electronic pressure regulator. Logical controller has a script which runs the electronic pressure regulator, based on sinusoidal function, and it can receive input from a computer via serial port to regulate variables within sinusoidal function (e.g. amplitude, iteration/looping speed, baseline value). In certain embodiments, continuous output is produced and sent to the electronic pressure regulator which then controls flow chamber volume, by moving a membrane which separates fluid space from the air space, thus producing pulsatility and oscillations in venous and arterial pressures throughout the perfusion system. Computer is connected to the logical controller, and custom-made scripts in Python allow for manual or automatic control. In certain embodiments, the software also monitors flow and pressure in the arterial and venous cannula and stores the data.


In certain embodiments, the automated hemodiafiltration system consists of (1) two peristaltic pumps which have separate logical controllers and are connected via serial ports to the computer, (2) liquid level solid-state sensor with a resistive output (0-5V), in a clear, elliptical polycarbonate tube integrated with logical controller, for monitoring fluid level in exchange solution canister, connected to the computer. Logical controllers for peristaltic pumps and level sensor have custom made scripts which allow for higher-order language control. In certain embodiments, the computer governs two peristaltic pumps and collects data from the sensor via Python script. The script performs proportional control over peristaltic pumps and allows for continuous dialysis while keeping the animal euvolemic.


Perfused Organs in the Mammalian Body

The invention provides methods of preserving organs in the mammalian body. In some embodiments, the organs are perfused with a solution comprising a priming solution, a hemodialysis solution and a solution comprising pharmacological components. The constituents and concentrations of the components in the priming solution, hemodialysis solution and solution comprising the pharmacological components are as shown in Tables 1-3. In certain embodiments, the mammalian body is perfused with a mixture of the perfusate and autologous blood. In some embodiments, the autologous blood is mixed with any of the components of the perfusate solution before perfusion of the mammalian body. In some embodiments, one or more artificial oxygen carriers are present in the mixture.


In some embodiments, the mammalian organs maintain morphofunctional integrity under hypothermic conditions after perfusion with the blood perfusate mixture.


In certain embodiments, the organs in the mammal are ischemic prior to perfusion with the blood perfusate mixture.


In certain embodiments, the organs are perfused while the mammal is still alive. In other embodiments, the organs are perfused immediately upon death of the mammal. In other embodiments, there is a 20 minute delay between death and perfusion of the organs. In other embodiments, the time between death and perfusion is at least one hour. In other embodiments, the time between death and perfusion is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12 hours.


In certain embodiments, the perfused organs are organs that can be transplanted from one mammal to another, including, but not limited to the kidney, the pancreas, the heart, the lung, the intestine, the corneas, the middle ear, bone, bone marrow, heart valves, connective tissue, skin, uterus, muscles, blood vessels, nerves and connective tissue. In some embodiments, the organs are removed from the mammal following perfusion with the blood perfusate mixture.


In certain embodiments, perfusion with the blood perfusate mixture helps maintain an in vivo rate of cellular metabolism and preserves functional responses of cells. The blood perfusate perfused organs can maintain longer viability than organs perfused with the ECMO system.


In certain embodiments, the perfused organs belong to any mammal. Non-human mammals include, for example, livestock and pets, such as ovine, bovine, porcine, canine, feline and murine mammals. Mammals can also include primates, including humans. In certain embodiments, the perfused mammal is a human.


In some embodiments, rigor mortis is prevented by perfusion of the deceased mammal. In one embodiment, perfusion of the deceased mammal with the technologies described herein prevents stiffening of the muscles. In another embodiment, the tissues in the perfused mammal continue or regain the consumption of. In another embodiment, the tissues in the perfused mammalian continue or regain the ability to produce ATP.


EXPERIMENTAL EXAMPLES

The invention is further described in detail by reference to the following experimental examples. These examples are provided for purposes of illustration only, and are not intended to be limiting unless otherwise specified. Thus, the invention should in no way be construed as being limited to the following examples, but rather, should be construed to encompass any and all variations which become evident as a result of the teaching provided herein.


Without further description, it is believed that one of ordinary skill in the art can, using the preceding description and the following illustrative examples, make and utilize the compounds of the present invention and practice the claimed methods. The following working examples therefore, specifically point out the preferred embodiments of the present invention, and are not to be construed as limiting in any way the remainder of the disclosure.


The materials and methods employed in practicing the following examples are here described:


Materials and Methods
Overview of the OrganEx Perfusion System and Perfusate
Overview of the OrganEx Perfusion System

The perfusion system consists of the main closed-loop circuit directly connected to an animal, and it includes a centrifugal pump (Medtronic Bio-Console 560, Medtronic, Minneapolis, MN) that drives the mixture of autologous blood and OrganEx perfusate through the oxygenator (Affinity Fusion, Medtronic), and custom-made pulsatility generator into animal arterial system. The oxygenator is connected to a refrigerated bath (Polystat, Cole-Parmer, Niles, IL) for temperature control and the gas blender (Sechrist Industries, Anaheim, CA), for control of dissolved gases and anesthesia infusion. The perfusion system has a fluid reservoir, which is used to prime the system and hold the supplement fluid. In parallel, an automated hemodiafiltration system and a reservoir are connected to the main circuit (FIG. 1). The automated hemodiafiltration system is used to exchange plasma fraction against custom-made dialysis exchange solution. The hemodiafiltration system consists of a roller-pump (Cobe Shiley, Stockert, Lakewood, CO), dialyzer (Diacap Pro 13H, Braun, Melsungen, Germany) and two peristaltic pumps (Masterflex L/S, Cole-Parmer) integrated with level sensor (eTape, Milone Technologies, Sewell, NJ) and custom-made logical controller. Two infusion pumps (Sigma Spectrum, Baxter Healthcare Corporation, Deerfield, IL) are connected to the arterial side of the main circuit supplementing heparin and pharmacological compounds of the perfusate. The CDI blood parameter module and the hematocrit/oxygen saturation probe (Terumo Cardiovascular Systems Corp., Elkton, MD) are connected on the arterial and venous side, respectively, along with pressure (PendoTECH, Princeton, NJ) and flow sensors (Bio-Probe TX50, Medtronic). OrganEx perfusion system components, logical controllers and sensors are connected to a computer for automated control and data gathering. Detailed schematics available upon request.


Preparation and Application of the OrganEx Perfusate

The OrganEx perfusate is a final mixture of a custom-made priming solution (Table 1), Hemopure (HbO2 Therapeutics, Waltham, MA), custom-made dialysis exchange solution (Table 2) and the solution of pharmacological compounds (Table 3).









TABLE 1







Components of the priming solution


Exchange Solution













Concen-
Concen-




M.W.
tration
tration
Volume


Components
(g/mole)
(g/L)
(mM)
(mL)














Sodium Chloride
58.44
5.844
140
N/A


Sodium Bicarbonate
84.007
3.36
40
N/A


Magnesium Chloride
203.3
0.305
1.5
N/A


Calcium Chloride
147.01
0.147
1
N/A


Glucose
180.156
0.9
5
N/A


Dextrane
504.4
25
100
N/A
















TABLE 2







Components of the hemodiafiltration exchange solution:


Exchange Solution












Concen-
Concen-



M.W.
tration
tration


Components
(g/mole)
(mg/L)
(mM)










Amino Acids










Glycine
75
18
0.24


L-Alanyl-Glutamine
217
350.4
1.614746544


L-Arginine hydrochloride
211
50.4
0.238862559


L-Cystine
313
37.5
0.119808307


L-Histidine hydrochloride-H2O
210
25.2
0.12


L-Isoleucine
131
63
0.480916031


L-Leucine
131
63
0.480916031


L-Lysine hydrochloride
183
87.6
0.478688525


L-Methionine
149
18
0.120805369


L-Phenylalanine
165
39.6
0.24


L-Serine
105
25.2
0.24


L-Threonine
119
57
0.478991597


L-Tryptophan
204
9.6
0.047058824


L-Tyrosine
181
62.274
0.344055249


L-Valine
117
56.4
0.482051282







Vitamins










Choline chloride
140
2.4
0.017142857


D-Calcium pantothenate
477
2.4
0.005031447


Folic Acid
441
2.4
0.005442177


Niacinamide
122
2.4
0.019672131


Pyridoxine hydrochloride
206
2.4
0.011650485


Riboflavin
376
0.24
0.000638298


Thiamine hydrochloride
337
2.4
0.007121662


i-Inositol
180
4.32
0.024







Inorganic Salts










Calcium Chloride
147
120
0.816326531


Ferric Nitrate
404
0.06
0.0001485


Magnesium Sulfate
246
58.602
0.238219512


Potassium Chloride
75
240
3.2


Sodium Bicarbonate
84
2220
26.42857143


Sodium Chloride
58
3840
66.20689655


Sodium Phosphate monobasic
156
65.4
0.419230769
















TABLE 3





Pharmacological components of OrganEx Perfusate







Organ Ex Perfusate













Concen-
Concen-




M.W.
tration
tration
Volume


Components
(g/mole)
(mg/L)
(mM)
(mL)










Gas-Exchange











Hemopure ® (HBOC-250)
250k
130k
0.52
750



(average)










Cytoprotective Agents













Concen-
Concen-




M.W.
tration
tration
Volume



(g/mole)
(mg/kg)
(mM)
(mL)





Hexahydro-2-imino-1H-thieno[3,4-d]imidazole-
243
0.303
N/A
N/A


4-pentanoic acid (2-Iminobiotin)






5-(1H-Indol-3-ylmethyl)-3-methyl-2-thioxo-4-
259
1.515
N/A
N/A


Imidazolidinone (Necrostatin-1)






Sodium 3-Hydroxybutyric Acid
126
43.636
N/A
N/A


Glutathione Monoethyl Ester
335
6.061
N/A
N/A


Minocycline
494
6.061
N/A
N/A


Lamotrigine
256
18.182
N/A
N/A


5-(2,6-Difluorophenoxy)-3-[3-methyl-1-oxo-2-
513
0.758
N/A
N/A


[(2-quinolinylcarbonyl)amino]butyl]amino]-4-






oxo-pentanoic acid hydrate (QVD-Oph)






Methylene Blue
320
1.515
N/A
N/A







Antibiotics and Anti-inflammatory











Ceftriaxone
661
121.212
N/A
N/A


Dexamethasone
392
10.606
N/A
N/A


Cetirizine
388
3.03
N/A
N/A









In detail, prior to connecting an animal, the OrganEx perfusion system is flooded and primed with 2200 mL of custom-made priming solution (5000 mL), followed by infusion of 1000 mL of Hemopure into the system. These solutions are left to mix and equilibrate throughout the perfusion system, after which 600 mL is extracted from the perfusion system to achieve desired concentrations of electrolytes and oncotic agents in the perfusion system and prepare it for addition of the autologous blood.


Prior to initiation of the perfusion protocol, animal femoral vessels are cannulated and connected to the main circuit. At 30 minutes of WIT, 5 000 USP units of heparin (Sigma-Aldrich, St Louis, MO) is administered into the system, followed by approximately 1000 mL of venous blood from the dead animal, which is drained into the perfusion system. At this point, circulatory volume in the OrganEx perfusion system is approximately 3600 mL, out of which 2600 mL is the priming solution and 1000 mL of autologous blood. Next, the mixture of the perfusate and autologous blood is left to equilibrate, and counter dialyzed against the residual priming solution over 30 minutes to allow for correction of metabolic derangements in the drained venous blood. In parallel, approximately 1600 mL of fluid is filtered out of the perfusion system over 30 minutes while the residual fluid is cooled to 28° C., yielding a final volume of 2000 mL in the OrganEx perfusion system. Next, at 1h of WIT, 1000 mL of the perfusate and autologous blood mixture is infused back into the animal, ensuring circulatory system filling following venous drainage, and the perfusion protocol is initiated. The remaining 1000 mL of the mixture is stored in the reservoir and used for fluid supplementation, if required. Following infusion of the perfusate and autologous blood mixture, pharmacological compounds and dialysis exchange solution, containing amino acids, vitamins and inorganic salts, are continuously infused into the main perfusion circuit by infusion pump and hemodiafiltration system, respectively. The OrganEx perfusion system utilizes automated hemodiafiltration circuit which corrects and maintains certain metabolic and electrolyte parameters by performing 1:1 (vol:vol) exchange of solutes and particles smaller than 40 kDa against a custom dialysis exchange solution (20,000 mL), while maintaining euvolemia. Hemodiafiltration flux was kept at 30-35 mL/kg/hr throughout 6-hour perfusion.


Overview of the ECMO Perfusion System

The ECMO perfusion system was assembled according to clinical standard. ECMO perfusion system has the main closed-loop circuit directly connected to an animal and consists of a centrifugal pump (Bio-Console 560, Medtronic) that drives autologous blood through the oxygenator (Affinity Fusion, Medtronic) into animal arterial system. The oxygenator is connected to a refrigerated bath (Polystat, Cole-Parmer) for temperature control and the gas blender (Sechrist Industries), for control of dissolved gases and anesthesia infusion. The perfusion system has a fluid reservoir, which is used to prime the system and hold the supplement fluid. Furthermore, ECMO perfusion system contained the CDI blood parameter module, and the hematocrit/oxygen saturation probe (Terumo Cardiovascular Systems Corp.) are connected on the arterial and venous side, respectively, along with pressure (PendoTECH) and flow sensors (Bio-Probe TX50, Medtronic). All probes and sensors from the ECMO perfusion system are connected to a computer to allow data gathering. Detailed schematics available upon request.


The ECMO perfusion system is primed with 1000 mL 0.9% Sodium Chloride (Baxter Healthcare Corporation, Deerfield, IL) and 5000 USP units of heparin (Sigma-Aldrich). Upon initiation of the perfusion protocol, the reservoir is taken out of the main circuit and the residual priming solution is stored for later supplementation.


Animal Anesthesia and Surgical Protocol

This research project was approved and overseen by Yale's Institutional Animal Care and Use Committee (IACUC) and guided by an external advisory and ethics committee. Experimental animals were procured from the local farm breeder, female domestic pigs (Sus scrofa domesticus; ˜30-35 kg). All animals were housed at Yale School of Medicine Division of Animal Care's facilities at a minimum of 3 days before the experiment.


Prior to experimental protocol, all animals received a Fentanyl patch, 50 ug/hr (Duragesic, Henry Schein, Melville, New York, NY, USA) for sedation. To induce anesthesia, 6 mg/kg of Telazol (Henry Schein) and 2.2 mg/kg of Xylazine (Henry Schein) were administered. Next, animals were intubated and connected to the ventilator utilizing FiO2 of 40% and FiN2 of 60% with standard parameters of tidal volume 10-15 ml/kg and frequency of 14-16 breaths per minute, along with 1-2% isoflurane (Henry Schein). Following ventricular fibrillation and induction of cardiac arrest, ventilation was stopped for 1h. Upon initiation of the perfusion protocol, in ECMO and OrganEx groups, ventilation was continued utilizing a tidal volume of 3-4 ml/kg, frequency 5 breaths per minute, positive end-expiratory pressure (PEEP) of 10 cm H2O, low inflation pressure, FiO2 50%, FiN2 50%. During the 6-hour perfusion protocol, 0.5% isoflurane was administered through the vaporizer connected to the gas blender.


Cardiac arrest and subsequent circulatory collapse were induced by ventricular fibrillation through the substernal window by applying a 9V battery to the myocardial wall. Prior to the ventricular fibrillation, animals received 7 000 USP units of heparin (Sigma-Aldrich). In order to connect the circulatory system of the animal to ECMO or OrganEx perfusion system, an incision was made in the right inguinal region exposing femoral artery and vein (FIGS. 1A-1G). Both, arterial and venous cannulas were inserted into femoral artery and vein, respectively. Artery was cannulated with 14 Fr and the vein with 19 Fr cannula (Edwards Lifesciences LLC, Irvine, CA). The tip of the venous cannula was placed in the inferior vena cava opening of the right atrium, and arterial cannula was positioned inferior to renal arteries.


Perfusion Protocol and Monitoring of Physiologic and Metabolic Parameters

At the start of the perfusion protocol in the OrganEx group, a mixture of the perfusate and autologous blood was slowly infused over 5 minutes resulting in an average flow rate of 600 mL/min at the end of infusion. Following this step, the flow rate was gradually increased over the next 20 minutes to a targeted flow rate of 80-100 mL/kg/min or highest possible flow rate without introducing overspinning of the centrifugal pump. Throughout the flow rate ramping-up process, pulsatility was set to oscillate around the mean flow rate at approximately ±10% of the given total flow rate. Residual mixture of the synthetic perfusate and autologous blood which was stored in the reservoir was used for fluid supplementation at 1-2 mL/kg/hr. Targeted arterial pressure was set to 50-80 mmHg, and it was controlled with phenylephrine, not more than 2 mg/hr. Similarly, in the ECMO group, flow rate was gradually increased over 25 minutes, targeting flow rates and arterial pressures as in the OrganEx group. Ringer's lactate (Baxter Healthcare Corporation) was used as a supplementation fluid at 3-4 ml/kg/hr. In both, ECMO and OrganEx group hypothermic perfusion protocol at 28° C. was utilized throughout the entire 6-hours of the perfusion protocol.


The animals in both, ECMO and OrganEx groups received 50 mL of 8.4% sodium bicarbonate (Henry Schein) during the first hour of perfusion. Glucose was supplemented according to the blood levels with the goal of maintaining euglycemia. Protamine, 25 mg, was administered immediately following initiation of the perfusion protocol to control activated clotting time, which was maintained between 180 and 220 seconds with titrated heparin administration. In both perfusion groups, partial pressure of arterial CO2 and O2 were targeted to 35 and 250 mmHg via gas blender, respectively.


Electrocardiogram (EKG) assessment was done with 4 leads placed at each corner of the trunk. Real time arterial and central venous pressure monitoring was done through cutdown of the brachial artery and jugular vein, respectively. Urine output was measured via Foley catheter. Animal core temperature was continuously monitored with a rectal probe. Monitoring of EKG, pressure and temperature was done utilizing Philips IntelliVue MP50 (Philips, Eindhoven, NL). During the preoperative procedure temperature was kept at 37° C. using a heating pad, which was turned off following ventricular fibrillation. Electroencephalogram (EEG) was monitored with Natus long-term monitoring (LTM) system and EMU40 breakout box (Natus Medical Inc., San Carlos, CA). Six electrodes were placed subcutaneously along the scalp (FIG. 11A) at the start of the sedation. EEG monitoring was conducted throughout the entire 6-hour perfusion protocol. Baseline and hourly arterial and venous samples were collected from the arterial and venous cannulas respectively. Sixty microliters of each sample were immediately analyzed using the GEM4000 clinical blood analyzer system (Instrumentation Laboratory, Bedford, MA). Continuous monitoring of blood electrolytes and hemoglobin concentration and saturation were done with CDI-500 (Terumo Cardiovascular Systems Corp.).


Radiographic and Ultrasound Imaging of Circulation
Fluoroscopy

Imaging of the abdominal and head blood vessels was performed using Philips Allura Xper FD20 system. In selected animals that underwent fluoroscopy, baseline physiological imaging was performed prior to the induction of ventricular fibrillation in both ECMO and OrganEx experimental protocol. The contrast-injecting catheter was introduced through the femoral artery cutdown and positioned in suprarenal aorta for renal and in the common carotid artery for brain imaging. Omnipaque Contrast 350 mg/mL (General Electric Inc., Boston, MA), 24 mL and 45 mL were introduced utilizing Medrad power injector (Bayer Vital GmbH, Leverkusen, Germany) for brain and kidney imaging acquisition. Following baseline imaging, all animals underwent additional fluoroscopy at hour 3 of perfusion. In both, ECMO and OrganEx group, imaging of abdominal blood vessels was modified by placing the contrast-injecting catheter in the infrarenal aorta due to the reversal of arterial flow direction, a consequence of femoral artery/vein perfusion approach in both, ECMO and OrganEx groups. The reconstructed images were saved in DICOM format and further post-processed using RadiAnt DICOM Viewer software (Medixant; Poznan, Poland).


Ultrasonography

Perfusion dynamics were monitored via Triplex Ultrasonography (Spectral Doppler, Colour Doppler, and B-mode) using the LOGIQe portable ultrasound system (General Electric) and an 8L-RS linear array probe (General Electric). In all assessed animals, left ophthalmic artery, common carotid artery and intrarenal arteries were used to profile perfusion dynamics. Power waveform analysis was done using Frq 4.4 MHz, Gn 17, SV 2 and DR 40.


Cell Nuclei Isolation

Following the appropriate experimental workflow, regions of interest were extracted 30 from each organ and frozen at −80° C. To ensure consistency between the specimens, all dissections were performed by the same person. Cell nuclei isolation from each organ (brain, heart, liver, kidney) were treated the same according to our already established protocol with some modifications in order to acknowledge each organ's specific structural qualities and to have identical buffers to enable inter-organ comparison within the same experimental animal. To avoid experimental bias nuclei isolation was done by the same person blinded for the replicates of experimental conditions. Furthermore, to randomly and fully represent the full tissue section, each tissue was pulverized to fine powder in liquid nitrogen with mortar and pestle (Coorstek, Golden, CO). All reagents were molecular biology grade and sourced from Sigma unless stated otherwise. Small amounts of pulverized tissue (5-10 mg) were then added into 1 ml of ice-cold lysis buffer (“Buffer A” is 250 mM sucrose, 25 mM KCl, 5 mM MgCl2, 10 mM NaCl, 10 mM Tris-HCl (pH 7.4), protease inhibitors w/o EDTA (Roche), RNAse inhibitor (80 U/ml) (Roche), 1 mM DTT, 1% BSA (m/v) (Gemini Bio-Products, Woodland, CA), 0.1% NP-40 (v/v), 0.1% Tween-20 (v/v) (Bio-Rad), 0.01% Digitonin (m/v) (Thermo-Fisher, Cleveland, OH). For lysis of heart, 0.1% TX-100 (v/v) was additionally added. DTT, RNAse Protector, protease inhibitors, and all detergents were added immediately before use. The suspension was transferred to 2 ml Dounce tissue homogenizer and lysed with constant pressure and without introduction of air with pestle A (30×) and pestle B (30×). The homogenate was strained through pre-wetted 40 μm tube top cell strainer (Thermo-Fisher). All subsequent centrifugation was performed in a refrigerated, bench-top centrifuge with swing-out rotor (Eppendorf, Hamburg, Germany). Heart lysate was centrifuged at 100 g for 5 min at 4° C., pellet of myofibrils and non-dissociated connective tissue was discarded, and supernatant saved. All lysates (brain, liver, kidney) and heart supernatant (post 100 g) were centrifuged at 1000 g, 10 min, 4° C., pellets were saved, and resuspended in 0.4 ml resuspension buffer (“Buffer B” is “Buffer A” w/o detergents). Final 0.4 ml of solution was mixed with 0.4 ml (1:1) of Optiprep solution (Buffer “C” is iodixanol 50% (v/v), 25 mM KCl, 5 mM MgCl2, 10 mM NaCl, 10 mM Tris-HCl (pH 7.4), protease inhibitors w/o EDTA, RNAse inhibitor (80U/ml), 1 mM DTT, 1% BSA (m/v)). The suspension (25% iodixanol final) was mixed 10× head over head and overlayed on 0.6 ml of 29% iodixanol cushion (appropriate mix of Buffer “B” and “Buffer “C”). The tubes were then centrifuged at 3000 g, for 30 min at 4° C. Following centrifugation, the supernatant was removed and total of 1 ml of wash buffer (“Buffer D” is 25 mM KCl, 5 mM MgCl2, 10 mM NaCl, 10 mM Tris-HCl (pH 7.4), RNAse inhibitor (80 U/ml), 1 mM DTT, 1% BSA (m/v), 0.1% Tween 20 (v/v), in DPBS (w/o Ca2+ and Mg2+) (Gibco)) was added in tubes and centrifuged at 1000 g, for 10 min at 4° C. Supernatants were then completely removed, pellets were gently dissolved by adding 100 ul of resuspension buffer (“Buffer E” is “Buffer D” w/o detergent) and pipetting 30× with lml pipette tip, pooled and filtered through 20 micrometer cell strainer. Finally, nuclei were counted on hemocytometer and diluted to 1 million/ml.


Single Nuclei Microfluidic Capture and cDNA Synthesis


Extracted nuclei samples were placed on ice and processed in the laboratory within 15 minutes for single nucleus RNA sequencing with targeted nuclei recovery of 10000 nuclei, respectively, on microfluidic Chromium System (10× Genomics, Pleasanton, CA) by following the manufacturer's protocol (CG000315_ChromiumNextGEMSingleCell3′_GeneExpression_v3.1 (DualIndex)_RevA), with Chromium Single Cell 3′ GEM, Library & Gel Bead Kit v3.1, (PN-1000268, 10×Genomics) and Chromium Single Cell G Chip Kit (PN-1000120, 10× Genomics), Dual Index Kit TT Set A (PN-1000215, 10×Genomics) on Chromium Controller (10×Genomics). Since the input material were nuclei, cDNA was amplified for 14 cycles.


Single-Nucleus RNA-Seq Library Preparation and Sequencing

Post cDNA amplification cleanup and construction of sample-indexed libraries and their amplification followed manufacturer's directions (CG000315_ChromiumNextGEMSingleCell3′_GeneExpression_v3.1 (DualIndex)_RevA), with the amplification step directly dependent on the quantity of input cDNA.


In order to reach sequencing depth of 20000 raw reads per nucleus, single nucleus libraries were run using paired end sequencing with single indexing on the NovaSeq 6000 S4 (Illumina) by following manufacturer's instructions (Illumina, San Diego, CA; 10× Genomics). To avoid lane bias, multiple uniquely indexed samples were mixed and distributed over several lanes.


Single-Nucleus Transcriptome Analysis
Quality Control and Analysis of Single Nuclei Transcriptome Data

Sequencing reads were aligned to the reference pig genome (susScr11) with the combined exon-intron gene annotations from NCBI RefSeq using CellRanger 5.0.1. pipeline, which also performed UMI counting, barcode counting and distinguishing true cells from background. The filtered count matrices were then moralized by library size using the “NormalizeData” function in Seurat. To compare cellular and transcriptomic changes across conditions, feature selection was first performed for each batch and the features from the same conditions were summarized using “SelectIntegrationFeatures”. The union of the highly variable genes across conditions were then passed to the data integration pipeline in Seurat to generate a batch-corrected expression matrix. To reveal the cellular diversity among the cells, we scaled the integrated data followed by dimension reduction using principal component analysis (PCA) and selecting principal components via elbow plot. The cell clusters in the k-nearest neighbor graph were then identified and visualized clustering results by Uniform Manifold Approximation and Projection (UMAP). The initial clustering analysis revealed some low-quality clusters with low number of unique molecular identifiers (UMIs), and normally high mitochondria percentage and no meaningful cluster markers, which were all removed for downstream analysis. To annotate the identity of the cell clusters, the pig data was then integrated with published human data from the same organ using the same data integration pipeline described above. The cluster markers were calculated using “FindMarkers” function and manually removed the doublet clusters that showing high expression of markers of two different type of cells. To gain more accurate cell annotations and clearer UMAP visualizations, the same pipelines of data integration, dimension reduction and cell clustering were reperformed on the filtered data.


Global Transcriptomic Comparisons with Public Datasets.


To validate the cluster annotation of the data, global transcriptomic comparison with public reference datasets for the four organs was performed. For each organ, the log-transformed average expression for each cell clusters was calculated followed by performing pairwise Pearson correlation between the clusters in the present dataset and the corresponding dataset using the highly variable genes. The resulted correlation coefficients were visualized on gradient heatmaps (FIGS. 12C-12F).


Cell Type Annotations.

The cell type classification for hippocampus data (FIG. 12C) was based on the gene markers derived from recent data in adult human hippocampus and entorhinal cortex. The cells were initially classified into several major groups based on marker gene expression: excitatory neurons (SLCI7A7+), inhibitory neurons (GAD1+), oligodendrocyte progenitor cells (PDGFRA+), oligodendrocytes (PLP1+), astrocytes (AQP4+), microglia (PTPRC+), vascular cells (COL1A1+). Because of the high heterogeneity present in excitatory and inhibitory neuron populations, these two populations were further subclustered. For excitatory neurons, they were classified to mature granule cells (PROX1+), mossy cells (ADCYAP1+), CA2-4 excitatory neurons (FREM1+/GALNT3+), CA1 and subiculum excitatory neurons (SATB2+/BCL11B+/TLE−), entorhinal cortex upper layer (CUX2+) and deep layer (TLE4+) excitatory neurons. For inhibitory neurons, they were classified based on their developmental origins, either derived from medial ganglionic eminence (MGE, LHX6+) and caudal ganglionic eminence (CGE, ARADB2+). For a small group of cells connecting granule cells on the UMAP that are devoid of all these markers but marked by DCX and CALB2 expression, they were annotated as neuroblast cells, intermediate cell populations in pig adult neurogenesis.


The heart data (FIG. 12D) was annotated based on the gene markers derived from recent data in adult human heart. We classified the cells based on marker expression: cardiomyocyte (MYH7+/FHL2+), immune cells (PTPRC+), pericytes (RGS5+/ABCC9+), smooth muscle cells (MYH11+/ACTA2+), endothelial cells (CDH5+/PECAM1+), fibroblast-like cells (DCN+/GSN+) and neuronal cells (NRX7N+/XKR4+). The endothelial cells have two subgroups that have differential expression of VWF and TBXJ. Immune cells were further classified to myeloid cells (BANK1+/C1QA+) and lymphoid cells (SKAP1+/CD8A+).


The kidney data (FIG. 12E) was annotated based on the gene markers derived from recent data in adult human kidney. We classified the cells based on marker expression: proximal tubule (CUBN+/LRP2+), connecting tubule and principal cells (SAMD5+/LINGO2+), loop of Henle (NHSL2+/UMOD2+), intercalated cells (HEPACAM2+/SLC26A7+), podocyte (PTPRQ+/PTPRO+), immune cells (PTPRC+), endothelium (CHRM3+/PTPRB+) and fibroblasts (PRKGI+/FBLN5+). Immune cells were further classified to myeloid cells (BANK1+/MARCHJ+) and lymphoid cells (SKAP1+/THSD7B+).


The liver data (FIG. 12F) was annotated based on the gene markers derived from recent data in adult mouse liver. The cells were classified based on marker expression: hepatocytes (APOB+/PCK1+), stellate cells (RELN+/ACTA2+), cholangiocytes (CFTR+/PKHDI+), immune cells (PTPRC+), endothelial cells (FLT1+/PECAM1+). The immune cells were further classified to multiple subgroups: B cells (MS4A1+), plasma cells (JCHAIN+/MZBI+), natural killer cell and T cells (SKAP1+), myeloid cells (CD163+/EMR4+, which are predominantly Kupffer cells).


Heterogeneity of Cells.

FindMarkers function from Seurat was used to determine marker genes for high resolution clusters. P-value adjustment is performed using Bonferroni correction with the cutoff set at 0.05. Top 10 genes for each cluster were ranked by fold changes and were visualized on a heatmap by using DoHeatmap function (Seurat). The dataset was randomly sampled to have 1000 cells per condition for each t-type prior to differential expression analysis.


Cell Type Prioritization Using Augur

In order to find the cell populations that exhibit high degree of transcriptomic changes, Augur was applied to prioritize the cell types between each pair of conditions. Since there are three samples per condition, the Augur analysis was performed on all of the nine sample pairs in each condition pair using the high-resolution cell clusters identified via Seurat. The median of the calculated area under curve (AUC) scores of each cluster were then visualized on the UMAP layout. Comparison of the AUC scores for each specific cell type and a given condition pair were done by comparing the specific cell type of interest AUC score and AUC scores of all the other cell types in that given condition pair by using Wilcoxon Rank Sum test (one tailed).


Differential Expression Analysis and Gene Ontology Analysis

In order to find differentially expressed genes (DEGs) between OrganEx and other conditions (0h PMI, 1h PMI, 7h PMI, ECMO) in major cell-types for each organ Seurat “FindMarkers” function was used. DEGs were defined at cut-off criteria of adjusted P-value (Bonferroni)<0.05, expression ratio greater than 0.1 in one condition and average log 2 fold change (log 2FC) greater than 0.2 in the same condition. Top 15 DEGs ranked by absolute values of log 2FC, were visualized using Bioconductor EnhancedVolcano package. Top 100 DEGs were used for HumanBase Functional Module Detection. Gene symbols starting with ma and LOC were excluded since HumanBase Functional Module Detection does not recognize those gene symbols. Identifying enriched biological pathways between OrganEx and all other groups in major cell-types for each organ, was performed using “enrichGO” function from clusterProfiler. Multiple testing was adjusted by false discovery rate (FDR) with the cutoff set at 0.2. Top 15 biological processes ranked by P-value were visualized by in-house made ggplot2 script.


Gene Set Enrichment Analysis

In order to assess whether gene sets of interest are upregulated in a specific condition (e.g., 0h WIT, 1h WIT, 7h WIT, ECMO and OrganEx), gene set enrichment analysis was performed in hippocampal neurons, astrocytes and microglial cells, cardiomyocytes in the heart, hepatocytes in the liver and proximal convoluted tubule cells in the kidney. This method is commonly used in Gene Ontology enrichment analysis and has been widely applied in multiple published studies. Specifically, all the expressed genes (expressed in at least one cell) were set as the gene universe and considered each set of condition-enriched genes as a sampling from the gene universe. The gene set enrichment, performed by Hypergeometric test (also named one-tailed Fisher's Exact test), is an assessment of whether genes from a given gene sets are overrepresented in condition-enriched genes than drawing from the gene universe by chance. To identify condition-enriched genes in the above-mentioned t-types, differential expression (DE) analysis was performed using Seurat FindMarkers function. In brief, one condition group was taken, its expression profiles were compared with the rest of the conditions using Wilcoxon Rank Sum test. For any given comparison, genes with false discovery rate (FDR) smaller than 0.01 were considered statistically significant and were kept. Because Wilcoxon Rank Sum test can be biased by the differences of cell numbers, that is, more cells lead to more differentially expressed genes, the datasets were randomly sampled to have 1000 cells per condition in each t-type prior to differential expression. With the condition-enriched genes and certain selected gene sets downloaded from GeneOntology (http://geneontology.org/), it was possible to assess the significance of gene set enrichment in a given condition. P-value of less than 0.05 was considered significant. Significance of the enrichment was visualized in a dot plot where size and color of the dot shows significance as −log 10(p-value). As shown in the FIG. 6A-6I), enrichment in all conditions in all organs was tested for positive regulation of DNA repair (GO:0045739), negative regulation of apoptotic process (GO:0043066), positive regulation of cytoskeleton organization (GO:0051495) and ATP metabolic process (GO:0046034). The same approach was used in assessment of functional enrichment analysis for each organ. Therefore, in hippocampus microglial cells were tested in enrichment for pro-inflammatory markers, and in astrocytes for pan-reactive markers as shown in FIG. 6A. Cardiomyocytes in heart were tested for Cardiac Muscle Cell Action Potential (GO:0086001), Fatty Acid Beta-Oxidation (GO:0006635) and Glycolysis (GO:0006096) as can be seen in FIG. 6B. In the liver, Hepatocytes enrichment of acute phase reactants and all expressed CYP isoforms (FIG. 6C) were tested in, and at last, proximal tubule cells in the kidney were tested for injury molecule genes and PCT transporter genes (FIG. 6D).


Gene Set Expression Enrichment Analysis.

The expression dynamics of selected cell death-related gene set across conditions was also evaluated. For each gene of the given gene set, its expression enrichment was tested in each condition by comparing its expression in the given condition to that of other conditions. Similarly, Wilcoxon Rank Sum test was used to measure the significance. The resulted log-transformed P-values (−log 10[P-value]) across conditions were visualized in a bar plot.


Hierarchical Clustering for Top DEGs.

To acquire the dynamic changes of transcriptome among different conditions and time points for each tissue, the top differential expressed genes for all the paired conditions were identified: 0h vs 1h, 0h vs 7h, 0h vs ECMO, 0h vs OrganEx, 1h vs 7h, 1h vs ECMO, 1h vs OrganEx, 7h vs ECMO, 7h vs OrganEx, and ECMO vs OrganEx using FindMarkers( ) function in Seurat. For hippocampus, significant DEG was selected with average log 2FC greater than 0.5 or less than −0.5. The top 50 upregulated genes were merged with 50 downregulated differentially expressed genes (DEGs, in total 100 genes) from each paired condition for the following analysis. To identify gene expression patterns, the average expression of the merged DEGs across t-types and experimental groups was calculated and the correlation coefficients subtracted from 1 as gene-gene distances was defined, which was passed to hierarchical clustering using the hclust function in R with ward.D2 algorithm. To define gene modules (clusters), the genes were parcellated using the cutreeDynamic function from R WGCNA package with a setting minClusterSize=45, sensitivity=2. The scaled eigengenes were the plotted, the first principal component of the expression matrix of each module to show the expression trend of the genes in each module. Using TopGO, the gene ontology analysis was performed for the genes in each module, and used fisher's exact test to calculate the P values. For heart, kidney and liver, the same methods with hippocampal data to select the genes were used. To keep the numbers of selected gene are comparable with hippocampus samples, significantly DEG with average log 2FC greater than 0.75 or less than −0.75 in heart data, significantly DEG with average log 2FC greater than 1.00 or less than −1.00 in kidney data and selected significantly DEG with average log 2FC greater than 1.75 or less than −1.75 in liver data. Then the same setting was used to build the gene expression network using hierarchical clustering. The scaled eigengenes of each module was plotted and used the same method (TopGO) for gene ontology analysis.


Evaluation of the Perfusate Components Effects.

To evaluate the effects of the perfusate components on OrganEx, the expression enrichment of the related pathways (cell death, inflammation, and oxidative response) between OrganEx and ECMO conditions (Tables 4, 5, and 6) were compared. Specifically, the AUC (area under curve) scores were calculated using the AUCell package and a one-sided Wilcoxon Rank-Sum test was performed to evaluate the significance of the pathway enrichment.


Trajectory Analysis.

The monocle2 was used and in-house R scripts to conduct pseudotime analysis for hippocampus, heart, liver, and kidney. The recommended analysis protocol was followed, except using FindMarkers function from Seurat package to perform pairwise comparison across different conditions to find the statistically significant up- and down-regulated genes. To reduce false positive results, some parameters were customized based on computational permutation. For examples, it was required that minimum percentage of expressed cells for each gene in either condition is larger than 0.1, and fold change larger than 1.25. Maximum number of cells in either condition was down sampled to 1000 cells to balance the comparison. Consequently, the identified differentially expressed genes by Seurat were used as the informative genes to order cells using setOrderingFilter function from monocle2, and the advanced nonlinear reconstruction algorithm called DDRTree was chosen to execute data dimensional reduction.


Cell-Cell Communication Analysis.

Cell-cell interactions based on the expression of known ligand-receptor pairs in different t-types were inferred using CellChat (v.1.1.3). The official CellChat workflow was followed for analyzing multiple datasets (0h WIT, 1h WIT, 7h WIT, ECMO and OrganEx). each dataset was first randomly down sampled to 1000 cells per t-type to to balance the comparison. Next, normalized counts were loaded into CellChat. After that, CellChatDB human database was selected for cell-cell communication analysis. The preprocessing was then applied as functions identifyOverExpressedGenes and identifyOverExpressedInteractions with standard parameters set. Next, communication probability was computed between interacting cell groups with truncated mean set at 0.1. After that filterCommunication, computeCommunProbPathway, and aggregateNet were applied using standard parameters. To identify conserved and context-specific signaling pathways rankNet function was applied on the netP data slot which showed in a stacked bar plot overall information flow of each signaling pathway. To determine strength of the reactions and t-types involved in each signaling pathway, netAnalysis_signalingRole_heatmap was performed and visualized overall signaling by aggregating outgoing and incoming signaling together.


Pseudotime Analysis

The monocle2 and in-house R scripts were used to conduct pseudotime analysis for all major organs, including hippocampus, heart, liver, and kidney. The recommended analysis protocol was followed, except using FindMarkers function from Seurat package to perform pairwise comparison across different conditions to find the statistically significant up- and down-regulated genes. To reduce false positive results, some parameters were customized based on computational permutation. For examples, it was required that minimum percentage of expressed cells for each gene in either condition is larger than 0.1, and fold change larger than 1.25. Maximum number of cells in either condition was down sampled to 1000 cells to balance the comparison. Consequently, the identified differentially expressed genes by Seurat were used as the informative genes to order cells using setOrderingFilter function from monocle2, and the advanced nonlinear reconstruction algorithm called DDRTree was chosen to execute data dimensional reduction.


Tissue Processing and Histology
Tissue Preparation

Following the completion of each experimental protocol brain, heart, lungs, kidney, liver, and pancreas were extracted and immersion-fixed in a solution containing 10% (w/v) neutral buffered formalin with gentle shaking. After fixation each tissue piece was processed and embedded into a paraffin block using the Excelsior tissue processor (Thermo Scientific, Waltham, MA).


Tissue Staining with Hematoxylin and Eosin (H&E) and TUNEL Assay


Heart, lungs, kidney, liver and pancreas paraffin blocks were trimmed on the Shandon Finesse 325 microtome (Thermo Scientific) to 5 μm sections. Sections were mounted on TruBond 380 adhesive slides and allowed to dry overnight at room temperature. All slide were then stained simultaneously for H&E using the automatic Shandon Linistain slide stainer (Thermo Scientific).


For Nissl staining, brain sections (hippocampus and prefrontal cortex) were stained with 0.1% cresyl violet solution (Abcam, ab246816) for 5 min and were rinsed quickly in 1 change of distilled water. Then these sections were dehydrated quickly in absolute alcohol and later cleared in Histo-Clear II and finally cover-slipped with Prolong Gold Antifade Mountant (ThermoFisher, P36934).


All slides for the TUNEL Assay (Millipore, S7101, 3542625) were processed simultaneously. They were fist deparaffinized, rehydrated and incubated with proteinase K (20 g/mL in PBS) for 30 min at 37° C. Slides were rinsed with PBS and incubated with 3% H2O2 in PBS for 10 min at room temperature to block endogenous peroxidase activity, followed by PBS washing and incubation in 0.1% Triton X-100 in 0.1% sodium citrate for 2 min on ice (4° C.). Sections were incubated with a mixture of TdT solution and fluorescein isothiocyanate dUTP solution in a humidified chamber at 37° C. for 60 min. This was followed by washings with PBS and incubation with antifluorescein antibody Fab fragments conjugated with horseradish peroxidase in a humidified chamber at 37° C. for 30 min. After washing with PBS, methyl green counterstain was applied to stain for nuclei.


Immunohistochemistry

All slides used for a specific immunohistochemistry staining were processed simultaneously. Slides containing formalin-fixed paraffin-embedded histological sections were first deparaffinized in 2 changes of Histo-Clear II (64111-04, Electron Microscopy Sciences, Hatfield, PA) for 10 minutes each. Slides were then transferred to 100% alcohol, for two changes, 10 minutes each, and then transferred once through 95%, 70%, and 50% alcohol respectively for 5 minutes each. Slides were then rinsed in water and washed in wash buffer (0.05% Tween 20 in 1×PBS) for 10 minutes. Slides were then placed into a chamber filled with antigen retrieval buffer (lOX R-Buffer A diluted to 1× by water, pH 6, 62706-10, Electron Microscopy Sciences). Slides then underwent heat-mediated antigen retrieval in the Unique Retriever system (Electron Microscopy Sciences). After antigen retrieval, slides were washed in wash buffer and blocked for 1 hour in 10% normal goat serum diluted in wash buffer at room temperature. Slides were then incubated in primary antibodies at 4 degrees C. overnight at the following dilutions: rabbit anti-NeuN (1/1000, Abcam, ab177487, GR3275112-10), mouse anti-GFAP (1/1000, Sigma-Aldrich, G3893-100UL, 0000082460), rabbit anti-Iba1 (1/500, Wako, 019-19741, PTR2404), mouse anti-albumin (1/500, Abcam, 4A1C11, GR3215248-15), mouse anti-beta actin (1/500, Invitrogen, AC-15, 01003256), rabbit cleaved caspase-3 (1/50, R&D Systems, MAB835, KHK0821021). The next day, slides were washed and then incubated with fluorescently tagged secondary anti-rabbit (Cell Signaling Technology, 8889S, 12) and anti-mouse (Abcam, ab150113, GR3370569-1) antibodies at a dilution of 1/500 for 1 hour at room temperature. After staining with secondary antibodies, slides were washed and incubated in DAPI (1/1000 for 5 minutes) at room temperature. Finally, slides were washed and mounted with coverslips using Prolong Gold Antifade Mountant (P36934, ThermoFisher).


Microscopy and Image Processing

Tissue sections were imaged using an LSM880 confocal microscope (Zeiss; Jena, Germany) equipped with a motorized stage using 10× (0.3 NA) or 20× (0.8 NA) objective lenses with identical settings across all experimental conditions. Lasers used: argon 458, 488, and 514; diode 405; and DPSS 561-10. The DPSS 561-10 laser intensity was increased during imaging of the control perfusate samples for the intravascular hemoglobin fluorescence study in order to obtain a background signal comparable to other groups. Images were acquired at either 1,024×1,024 or 2,048×2,048-pixel resolution. Images are either representative confocal tile scans, high-magnification maximum intensity Z-stack projections (approximately 7-9-μm stacks; −1 μm per Z-step), or high magnification confocal images. Alternatively, histological images were acquired using an Aperio CS2 Pathology Slide Scanner (Leica; Wetzlar, Germany) as described above. Image adjustments were uniformly applied to all experimental conditions in Zeiss Zen. Digitized images were assembled in Zeiss Zen, ImageScope, and Adobe Illustrator.


Histological Data Analysis and Quantification
H&E Staining—Pathology Injury Score

All H&E slides were scanned. Four images were randomly selected from each slide and from the corresponding areas. Blinded observers scored each image accordingly. Criteria for heart were nuclear damage, myocyte vacuolization, widened spaces between myofibers and edema. Criteria for lungs were nuclear damage, pneumocyte vacuolization and hemorrhage. Criteria for kidney were nuclear damage, tubule vacuolization, hemorrhage, and tubule damage. Criteria for liver were nuclear damage, tissue vacuolization, hepatocyte vacuolization, and congestion. Criteria for pancreas were nuclear damage, cell vacuolization, hemorrhage, edema.


Cresyl Violet (Nissl) Staining Injury Score.

Two images were taken per region of interest (hippocampal CA1 region or PFC) and were evaluated by blinded observer using the cell counter function in ImageJ according to already established criteria.


Kidney Periodic Acid-Schiff (PAS) Staining—Pathology Injury Score.

All kidney PAS-stained slides were examined by blinded kidney pathologist. Score (0-3) was assigned depending on the severity of the damage which included: Bowman space dilation, tubular dilation, tubular vacuolization, brush border disruption and presence of the casts.


Brain Immunofluorescence Cell Analysis and Quantification

All images were normalized to the regions of interests (hippocampal CA1, CA3 and DG) using ImageJ and randomized. The number of labeled astrocytes (GFAP+ cells), microglia (IBA1+ cells) cells were quantified manually by a blinded observer using the cell counter plugin and averaged based on the acquired area/cells. The particle analysis of astrocytes was performed using a custom pipeline in the open-source software, CellProfiler56, where a uniform threshold was set on GFAP to identify GFAP+ skeleton objects. The number of GFAP+ fragments in each area were then auto-counted and averaged according to the number of the astrocytes. The mean intensity of NeuN per neuron were quantified by a custom pipeline where neurons were identified based on the DAPI segmented objects expressing NeuN. Data were analyzed and plotted in GraphPad Prism9 software. All data are shown as mean±SEM. “n” refers to the number of biological replicates.


Kidney, Liver, and Heart Immunofluorescence Analysis.

In the kidney, three images were taken randomly of the kidney cortex. All images were randomized and analyzed by a blinded observer. Glomerulus and the proximal convoluted tubule were manually selected as the regions of interest in the four same-size circles respectively in corresponding regions across images. The mean intensity of ACTB and TIMI was calculated using ImageJ software. The number of Ki-67 positive cells were manually counted.


In the liver, immunolabelling quantification was done the same for albumin and factor V. Three images were randomly taken from the same region of the liver. The mean intensity of albumin and factor V was automatically quantified using ImageJ across the whole slide.


In the heart, three images were taken randomly from the left ventricle just slightly below the epicardium. All images were randomized, after which a blinded observer selected cardiac muscle tissue as a region of interest. The amount of cytoplasmic troponin I was then quantified using mean intensity function in ImageJ.


Cell Death Pathway Quantification and Analysis (actCASP3, IL1B, RIPK3, and GPX4).


For kidney, liver, heart, and pancreas, three images were taken randomly from each slide and from the corresponding areas of each organ. actCASP3+ cell intensity was quantified manually by a blinded observer using ImageJ. Mean immunolabelling intensity of IL1B, RIPK3 and GPX4 in kidney, liver and heart was quantified using ImageJ with background subtraction and measure functions. In the brain, the number of actCASP3+ and RIPK3+ cells were counted manually in the hippocampal CA1 region and prefrontal cortex. Expression of ILIB and GPX4 in hippocampal CA1 was measured in cells that were manually selected in the granule cell layer using ImageJ measure function.


TUNEL Quantification and Analysis.

All images were taken with a bright field microscope followed by a random same-size snapshots of the slides. A blinded observer analyzed randomized images using Fiji to separate channels of nuclei staining (hematoxylin) and DNA fragments (DAB). Total DNA fragments were quantified based on the total DAB intensity using CellProfiler.


Functional Organ Assessments
Heart Contractility Measurements

Small piece of the apical portion of the hearts' left ventricle was excised and placed in the carbonated Tyrode's solution (140 mM NaCl, 6 mM KCl, 10 mM glucose, 10 mM HEPES, 1 mM MgCl2, 1.8 mM CaCl2), pH=7.4). The tissue was then dissected into 1-2 cm3 cubes and placed on a holder with the epicardium facing down so the cutting align with the cardiac myofibril orientation. Using a vibratome, the heart was sliced at 150 μm thickness at 4° C. After slicing, spontaneous rate and rhythm of heart contraction were characterized and recorded using a slice microscope with temperature control set to 37° C. (Scientifica SliceScope, Uckfield, UK). Beating frequency was quantified within the time course of 30 seconds.


Glucose Assays

At the end of each perfusion, two identical tissue samples with 5 mm length were acquired from each organ (kidney, heart, and cerebral cortex) using a 3 mm biopsy punch (Miltex, Integra, York, PA) and were placed in cold PBS (fresh) and PFA (fix overnight) solutions respectively. The fresh tissues and the fixed controls were incubated in 2-NBDG working solution (Cayman 11046, 100 μM, Ann Arbor, MI) for 30 min at 37° C. followed by 15 min of wash in PBS. The images were acquired immediately using widefield microscope (Zeiss) under 2.5× objective (Ex: 465-495 nm, Em: 5210-560 nm) with exposure time of 295 ms (kidney and heart) and 50 ms (cerebral cortex). Images were analyzed using ImageJ to quantify the mean intensity of the ROI with normalization based on the fixed controls.


Organotypic Hippocampus Culture and Nascent Protein Synthesis Assay

Hippocampus was isolated at the end of appropriate experimental protocol and sectioned with a vibratome at 250 μm thickness in carbonated NMDG-HEPES aCSF solution (92 mM NMDG, 2.5 mM KCl, 1.25 mM NaH2PO4, 30 mM NaHCO3, 20 mM HEPES, 25 mM glucose, 2 mM thiourea, 5 mM Sodium ascorbate, 3 mM Sodium pyruvate, 0.5 mM CaCl2)·2H2O, and 10 mM MgSO4·7H2O, pH=7.3). Hippocampal slices were then collected and transferred onto culture membranes (Falcon culture insert, 0.4 m) and cultured in a six-well culture dish with 1.5 ml medium (48% DMEM/F-12 (Gibco), 48% Neurobasal (Gibco), 1× N−2 (Gibco), 1×B−27 (Gibco), 1× Glutamax (Gibco), 1×NEAA (Gibco), 1× Pen Strep (Gibco). The plates were maintained in an incubator at 37° C. with 5% CO2 for up to 2 weeks. The amino acid methionine analog, azidohomoalanine (AHA, ThermoFisher), was added to the hippocampal slice at a final concentration of 50 μM in HEPES buffered solution (HBS) followed by the incubation of 6 hours at 37° C. Slices were washed with PBS and immediately fixed in 4% paraformaldehyde at 4° C. overnight. Detection of nascent protein synthesis was performed with the modified Click-iT 1-azidohomoalanine (AHA) Alexa Fluor 488 Protein Synthesis HCS Assay kit (ThermoFisher). To visualize neurons simultaneously, the slices were then blocked with 5% NDS for 1 hour at room temperature, and incubated with Rabbit anti-NeuN antibody (abcam, 1:1000) overnight at 4° C. followed by the incubation of anti-rabbit AlexaFluor647 (1:500) for 1 hour at room temperature. The slices were then co-stained with DAPI to visualize nuclei. Images were acquired using Zeiss LSM800 confocal microscope with 20× objective. The combined Z-stack images of DAPI, AlexaFluor 488 and AlexaFluor 647 channels were acquired with optical slice thickness of around 20 μm and images of maximum projection are shown. Proteins detected around the nucleus (perinuclear) are the most abundant newly synthesized proteins in cells28, and were quantified using ImageJ intensity measurement function.


Image Visualization

Depiction of the pig in FIG. 1A, and pig's head in FIG. 11A, were adapted from BioRender.com with postprocessing in Adobe Illustrator and Adobe Photoshop.


Statistical Analysis and Reproducibility

All data are reported as mean±standard error of mean with data analysis being conducted using one-way ANOVA with Dunnett's post hoc multiple comparisons in reference to the OrganEx perfusion group, or unpaired t-test for comparisons between two groups. Fisher's exact test was used to compare occurrence of QRS complexes in OrganEx and ECMO groups during the perfusion protocol. For the number of replicates in each experimental group together with appropriate statistical analyses please see below. Significance was set at P<0.05. All statistical analysis and plotting were done in GraphPad 9 (GraphPad Software, San Diego, CA) or in Python. All figures were created using Adobe Illustrator (Adobe Systems, San Jose, CA).


Further Information on Statistical Analyses

Further information regarding statistical values and reproducibility of the results is given below.


In FIGS. 2C-2E, the results are taken at the baseline (where applicable) and every hour throughout the perfusion experiment from ECMO and OrganEx perfusion groups. Each group consisted of n=6 biological replicates. In FIG. 2C, Total flow rate: P values for hours 1-6, 1h: <0.0001, 2h: <0.0001, 3h: <0.0001, 4h: <0.0001, 5h: <0.0001, 6h: <0.0001; t values for hours 1-6, 1h: 12.34, 2h: 8.120, 3h: 8.869, 4h: 9.683, 5h: 17.64, 6h: 22.96. Brachial arterial pressure: P values for hours 0-6, 0h: 0.9704, 1h: <0.0001, 2h: 0.0002, 3h: 0.0003, 4h: 0.0006, 5h: 0.0027, 6h: <0.0001; t values for hours 0-6, 0h: 0.03807, 1h: 12.24, 2h: 5.645, 3h: 5.480, 4h: 4.890, 5h: 3.953, 6h: 7.590. In FIG. 2D, Mixed venous 02 saturation: P values for hours 0-6, 0h: 0.8996, 1h: 0.0837, 2h: 0.0002, 3h: 0.0003, 4h: 0.0015, 5h: <0.0001, 6h: 0.0036; t values for hours 1-6, 0h: 0.1295, 1h: 1.920, 2h: 5.582, 3h: 5.453, 4h: 4.338, 5h: 7.691, 6h: 3.781. In FIG. 2E, Serum K+: P values for hours 0-6, 0h: 0.8365, 1h: 0.0001, 2h: 0.0008, 3h: <0.0001, 4h: <0.0001, 5h: <0.0001, 6h: <0.0001; t values for hours 0-6, 0h: 0.2118, 1h: 6.156, 2h: 4.707, 3h: 7.224, 4h: 12.24, 5h: 7.401, 6h: 9.358. Serum pH: P values for hours 0-6, 0h: 0.3489, 1h: <0.0001, 2h: <0.0001, 3h: <0.0001, 4h: <0.0001, 5h: <0.0001, 6h: <0.0001; t values for hours 0-6, 0h: 0.9827, 1h: 6.285, 2h: 9.256, 3h: 9.668, 4h: 8.427, 5h: 7.056, 6h: 7.034.


In FIGS. 3B-3D, data points are from a representative brain per condition; the experiment was repeated in n=3 independent brains per condition. In FIG. 3B, One-way ANOVA (P=0.0001, F[4, 10]=19.12) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.009; OrganEx vs ECMO: P=0.003. In FIG. 3C, One-way ANOVA (P=0.0098, F[4, 10]=6.035) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0059; OrganEx vs ECMO: P=0.0356. In FIG. 3D One-way ANOVA (P=0.0076, F[4, 10]=6.495) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0109.


In FIGS. 3F-3H, data points are from a representative organ (heart, liver and kidney) per condition, the experiment was repeated in n=5 independent organs per condition. In FIG. 3F, One-way ANOVA (P<0.0001, F[4, 20]=52.16) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0429; OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P<0.0001. In FIG. 3G, One-way ANOVA (P<0.0001, F[4,20]=50.79) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.006; OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P=0.0009. In FIG. 3g, One-way ANOVA (P<0.0001, F[4,20]=50.79) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.006; OrganEx vs 7h WIT: P<0.0001. OrganEx vs ECMO: P=0.0009; In FIG. 3H, One-way ANOVA (P<0.0001, F[4,20]=17.79) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0001; OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P=0.0022.


In FIGS. 3J-3K, data points are from a representative kidney per condition, the experiment was repeated in n=3 independent kidneys per condition In FIG. 3J, One-way ANOVA (P=0.0262, F[4,10]=4.398) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0103. In FIG. 3K, One-way ANOVA (P=0.0057, F[4,10]=7.082) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0023.


In FIGS. 5A-5C, data points are from a representative organ (brain, heart, and kidney) per condition, the experiment was repeated in n=3 independent organs per condition. In FIG. 5A, One-way ANOVA (P=0.003, F[2,6]=17,73) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0024. In FIG. 5B, One-way ANOVA (P=0.0033, F[2,6]=17,07) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0033. In FIG. 5C, One-way ANOVA (P=0.0033, F[2,6]=6.453) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0320.


In FIG. 5D, each data points are from representative perfusion experiment per condition, the experiment was repeated in n=5. Two-sided Fisher's exact t test was used: P=0.0476.


In FIG. 5F, each data point is from the representative liver per condition, the condition was repeated in n=3 times. One-way ANOVA (P<0.0001, F[4,10]=15.52) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0002; OrganEx vs 7h WIT: P=0.0005; OrganEx vs ECMO: P=0.0007.


In FIGS. 5H, 5J, each data point is from the representative hippocampal slice per condition, the experiment was repeated n=3-5 times per condition. In FIG. 5H, for day 1: One-way ANOVA (P=0.0352, F[2,10]=4.766) with post-hoc Dunnett's adjustment was performed; for day 14: One-way ANOVA (P=0.0027, F[2,10]=11.35) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0026. In FIG. 5J, for day 1: One-way ANOVA (P=0.0077, F[2,10]=8.246) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0216; for day 14: One-way ANOVA (P=0.0270, F[2,9]=5.544) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.027.


In FIG. 7C-7D, each data point is from the representative perfusion experiment per condition, the experiment was repeated in n=6. In FIG. 7C, Arterial cannula pressure: P values for hours 1-6, 1h: <0.0001, 2h: <0.0001, 3h: <0.0001, 4h: <0.0001, 5h: <0.0001, 6h: <0.0001; t values for hours 1-6, 1h: 12.34, 2h: 8.120, 3h: 8.869, 4h: 9.683, 5h: 17.64, 6h: 22.96. In FIG. 7C, Venous cannula pressure: P values for hours 1-6, 1h: <0.0001, 2h: =0.0306, 3h: =0.0237, 4h: =0.0003, 5h: =0.0069, 6h: =0.0027; t values for hours 1-6, 1h: 9.058, 2h: 2.516, 3h: 2.665, 4h: 5.516, 5h: 3.386, 6h: 3.946. In FIG. 7D, O2 delivery: P values for hours 1-6, 1h: <0.0001, 2h: <0.0001, 3h: <0.0001, 4h: <0.0001, 5h: <0.0001, 6h: <0.0001; t values for hours 1-6, 1h: 10.44, 2h: 6.957, 3h: 8.578, 4h: 9.462, 5h: 14.32, 6h: 18.56. In FIG. 7D, O2 consumption: P values for hours 1-6, 1h: =0.8432, 2h: =0.1815, 3h: =0.3195, 4h: =0.3667, 5h: =0.2152, 6h: =0.0394; t values for hours 1-6, 1h: 0.2030, 2h: 1.436, 3h: 1.048, 4h: 0.9455, 5h: 1.323, 6h: 2.368.


In FIGS. 8B-8E, data points are from a representative brain per condition, the experiment was repeated in n=3 independent brains per condition. In FIG. 8B, One-way ANOVA (P=0.0008, F[4,10]=11.95) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0097; In FIG. 8C, One-way ANOVA (P=0.0003, F[4,10]=14.64) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0006. In FIG. 8D, One-way ANOVA (P<0.001, F[4,10]=44.47) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P<0.001; OrganEx vs ECMO: P<0.001. In FIG. 8E, One-way ANOVA (P<0.001, F[4,10]=60.70) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 0h WIT: P=0.0024; OrganEx vs 1h WIT: P<0.001; OrganEx vs 7h WIT: P<0.001; OrganEx vs ECMO: P=0.0159.



FIGS. 8G-8L data points are from a representative brain per condition, the experiment was repeated in n=3 independent brains per condition. In FIG. 8G, One-way ANOVA (P=0.011, F[4,10]=5.819) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0287; OrganEx vs 7h WIT: P=0.0045; OrganEx vs ECMO: P=0.0149. In FIG. 8I, One-way ANOVA (P<0.0003, F[4,10]=32.20) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 0h WIT: P=0.0243; OrganEx vs 7h WIT: P=0.0157; OrganEx vs ECMO: P=0.0001. In FIG. 8J, One-way ANOVA (P=0.0231, F[4,10]=4.590) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0137. In FIG. 8K, One-way ANOVA (P=0.0002, F[4,10]=17.45) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.09338; OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P=0.0157. In FIG. 8L, One-way ANOVA (P=0.0032, F[4,10]=8.285) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0198.


In FIGS. 9B, 9C, 9E, data points are from a representative organ (lung, pancreas, kidney) per condition, the experiment was repeated in n=5 independent organs per condition. In FIG. 9B, One-way ANOVA (P<0.0001, F[4,20]=45.78) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P<0.0001. In FIG. 9C, One-way ANOVA (P<0.0001, F[4,20]=19.80) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0009; OrganEx vs 7h WIT: P<0.0001; OrganEx vs ECMO: P=0.0009. In FIG. 9E One-way ANOVA (P<0.001, F[4,20]=1.915) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0410.


In FIGS. 9G-9J, data points are from a representative kidney per condition, the experiment was repeated in n=5 independent kidneys per condition. In FIG. 9G, One-way ANOVA (P<0.01, F[4,10]=7.983) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0159; OrganEx vs ECMO: P=0.0118. In FIG. 9I, One-way ANOVA (P<0.01, F[4,10]=8.286) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0092; OrganEx vs ECMO: P=0.0084. In FIG. 9J, One-way ANOVA (P<0.01, F[4,10]=11.12) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.002; OrganEx vs ECMO: P=0.0022.


In FIGS. 4B-4E, data points are from a representative organ (heart, liver, kidney, and pancreas) per condition, the experiment was repeated in n=3 independent organs per condition. In FIG. 4B, One-way ANOVA (P<0.0001, F[4,10]=22.48) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0018; OrganEx vs ECMO: P<0.0001. In FIG. 4C, One-way ANOVA (P=0.0020, F[4,10]=9.392) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.004; OrganEx vs ECMO: P=0.001. In FIG. 4D, One-way ANOVA (P<0.0001, F[4,10]=23.50) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0022; OrganEx vs 7h WIT: P=0.0002; OrganEx vs ECMO: P<0.0001. In FIG. 4E, One-way ANOVA (P=0.0008, F[4,10]=12.10) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO WIT: P=0.0008.


In FIG. 4J-4M, data points are from a representative organ (heart, liver, kidney, and pancreas) per condition, the experiment was repeated in n=5 independent organs per condition In FIG. 4J, One-way ANOVA (P<0.0001, F[4,20]=14.35) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P<0.0001. In FIG. 4K, One-way ANOVA (P<0.0001, F[4,20]=13.26) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P<0.0001. In FIG. 4L, One-way ANOVA (P=0.0002, F[4,20]=9.110) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0012. In FIG. 4M, One-way ANOVA (P=0.0387, F[4,20]=3.102) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0216.


In FIG. 4G, 4H, each data points are from a representative brain per condition, the experiment was repeated in n=3 independent brains per condition. In FIG. 4G, One-way ANOVA (P<0.0001, F[4,10]=37.55) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 0h WIT: P=0.0083; OrganEx vs 1h WIT: P=0.0002; OrganEx vs 7h WIT: P=0.016. In FIG. 4H, One-way ANOVA (P<0.0001, F[4,10]=66.81) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 0h WIT: P=0.0001; OrganEx vs 1h WIT: P<0.0001.


In FIGS. 4O, P, each data points are from a representative brain per condition, the experiment was repeated in n=5 independent brains per condition. In FIG. 4O, One-way ANOVA (P=0.0547, F[4,20]=2.784) with post-hoc Dunnett's adjustment was performed. In FIG. 4P, One-way ANOVA (P=0.1005, F[4,20]=2.244) with post-hoc Dunnett's adjustment was performed.


In FIGS. 10, each data point is from the representative brain specimen per condition, the experiment was repeated n=3 times per condition. In FIG. 10B, One-way ANOVA (P=0.0013, F[4,10]=10.52) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.002; OrganEx vs ECMO: P=0.0418. In FIG. 10C, One-way ANOVA (P=0.0002, F[4,10]=17.06) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0386; OrganEx vs 7h WIT: P=0.0302. In FIG. 10D, One-way ANOVA (P<0.0001, F[4,10]=23.67) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0001. In FIG. 10E, One-way ANOVA (P=0.0003, F[4,10]=14.74) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0006. In FIG. 10F, One-way ANOVA (P=0.0264, F[4,10]=4.389) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0301; OrganEx vs ECMO: P=0.0270. In FIG. 10H, One-way ANOVA (P=0.0082, F[4,10]=6.365) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0082; OrganEx vs 7h WIT: P=0.005; OrganEx vs ECMO: P=0.0124. In FIG. 10I, One-way ANOVA (P=0.0012, F[4,10]=10.81) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.001; OrganEx vs ECMO: P=0.0012. In FIG. 10J, One-way ANOVA (P=0.0001, F[4,10]=18.96) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0048; OrganEx vs ECMO: P=0.0049. In FIG. 10L, One-way ANOVA (P=0.0264, F[4,10]=7.430) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0437; OrganEx vs 7h WIT: P=0.0437; OrganEx vs ECMO: P=0.0437. In FIG. 10M, One-way ANOVA (P=0.0082, F[4,10]=6.365) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0082; OrganEx vs 7h WIT: P=0.005; OrganEx vs ECMO: P=0.0124. In FIG. 10N, One-way ANOVA (P=0.0002, F[4,10]=16.23) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0013; OrganEx vs ECMO: P=0.044. In FIG. 10O, One-way ANOVA (P=0.0024, F[4,10]=9.035) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 1h WIT: P=0.0019; OrganEx vs 7h WIT: P=0.0062; OrganEx vs ECMO: P=0.0034.


In FIGS. 11J, 11K, each data point is from the representative hippocampal slice per condition, the experiment was repeated n=3-5 times per condition. In FIG. 11J, for day 1: One-way ANOVA (P=0.0078, F[2,9]=8.749) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in OrganEx vs ECMO: P=0.0245; for day 7: One-way ANOVA (P=0.0126, F[2,10]=6.995) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0086; for day 14: One-way ANOVA (P=0.005, F[2,9]=10.12) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0037. In FIG. 11K, for day 1: One-way ANOVA (P=0.0406, F[2,9]=4.670) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in OrganEx vs ECMO: P=0.0375; for day 7: One-way ANOVA (P=0.0278, F[2,9]=5.476) with post-hoc Dunnett's adjustment was performed, Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.0406; for day 14: unpaired two-tailed t-test was performed: P=0.8691, t=0.1735.


In FIG. 11M, 11O, data points are from a representative organs (heart, liver) per condition, the experiment was repeated in n=3 independent organs per condition. In FIG. 11M, One-way ANOVA (P=0.0207, F[4,10]=4.760) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs ECMO: P=0.00434. In FIG. 11O, One-way ANOVA (P=0.0063, F[4,10]=6.863) with post-hoc Dunnett's adjustment was performed; Dunnett's multiple comparisons test resulted in: OrganEx vs 7h WIT: P=0.0064; OrganEx vs ECMO: P=0.0163.


Example 1: Overview of OrganEx Technology

The OrganEx technology consists of a perfusion system and synthetic perfusate (FIG. 1A, FIG. 1). The perfusion system consists of a computer driven custom-made pulse generator connected to a centrifugal pump, which enables reproduction of physiological pressure and flow waveforms, together with automated hemodiafiltration, gas mixer, and drug delivery systems which allow control of blood coagulation and supplementation of the perfusate. To ensure homeostasis and maintain the targeted perfusion parameters, the perfusion system is also equipped with sensors for electrolytes, blood gases, metabolic parameters, hemoglobin, vessels and cannulas pressures, and total circulatory flow rate. The perfusate is optimized for whole-body compatibility. The OrganEx perfusate is a final mixture of a custom-made priming solution (Table 1), Hemopure (HbO2 Therapeutics, Waltham, MA), custom-made dialysis exchange solution (Table 2) and the solution of pharmacological compounds (Table 3).


To evaluate OrganEx technology in large mammals, a porcine global warm ischemia model induced by cardiac arrest on anesthetized and heparinized animals (FIG. 1A) was implemented. Following cardiac arrest and cessation of the systemic circulation, animals were left dead for one hour, allowing warm ischemic damage to ensue at core temperature of 36-37° C. Subsequently, animals were connected to one of the two perfusion systems via a femoral artery/vein approach with the goal of reinstating systemic circulation and nutritive rather than functional circulation of heart and lungs (FIG. 1A). Overall, this study consisted of five groups. Three different, unperfused, control groups corresponding to important experimental timepoints and distinct warm ischemia intervals were used: (1) healthy control group with minimal (up to 10 minutes) warm ischemia time (WIT) following cardiac arrest (0h WIT), (2) an hour of warm ischemia to investigate molecular and cellular damage prior to perfusion intervention (1h WIT), and (3) seven hours of warm ischemia to investigate damage extent that happens without any intervention (7h WIT). Additionally, in two perfusion intervention groups, following one hour of warm ischemia, perfusion was performed for six hours under hypothermic conditions (28° C.) either with: (4) a clinical standard, heart-and-lung substitution perfusion device—extracorporeal membrane oxygenation system (ECMO), or (5) perfusion technology (OrganEx). Animals in ECMO group were perfused with autologous blood. In OrganEx, prior to the initiation of the perfusion protocol, autologous blood was drained into the OrganEx system and mixed with the perfusate (in for example, effective 1:1 ratio), which was then used to perfuse the animal.


Example 2: Systemic Circulation and Metabolic Parameters

Since systemic circulation assures supply of oxygen, metabolites and potential therapeutic agents during recovery from ischemia, it was first queried whether circulation could be restored with external perfusion following one hour of warm ischemia. Perfusion of the whole-body with ECMO system invariantly resulted in low or no flow states due to circulatory collapse. In particular, utilizing fluoroscopic angiography, ECMO perfusion exhibited limited arterial filling of major conduit arteries and organs, such as kidney, liver and brain (FIG. 2A, FIG. 7A). Consistent with this finding, ECMO interventions yielded inadequate organ perfusion as indicated by Color Doppler assessment (FIG. 2B). Furthermore, systemic perfusion parameters revealed collapse of circulation as shown by extremely negative venous perfusion pressure and low arterial pressures (FIG. 2C, FIG. 7C-7D).


In contrast, robust whole-body perfusion in the OrganEx treated animals was observed, as indicated by contrast enhancement of major conduit arteries and organs, demonstrating patent circulation (FIG. 2A, FIG. 7A). In addition, Color Doppler analysis demonstrated pulsatile flow throughout the whole-body in the OrganEx group (FIG. 2B). In particular, flow in the ophthalmic artery, a proxy indicator of cerebral perfusion, was present in the OrganEx, but not in ECMO perfusion group, when analyzed at hour three of the perfusion protocols (FIG. 2B). Similar findings were observed in renal intralobular arteries (FIG. 2B), while reduced flow was detected in carotid arteries as compared to OrganEx (FIG. 7B). These data were further supported with the data from the OrganEx perfusion system sensors showing restoration of physiologic flow rates and arterial pressures (FIG. 2C).


Following successful restoration of circulation, the extent that OrganEx is capable of recovering metabolic parameters was assessed. By measuring mixed venous oxygen saturation of blood returning to the venous circulation from peripheral tissues and organs, it was confirmed that the OrganEx technology was able to deliver adequate levels of oxygen to the whole body throughout the perfusion (FIG. 2D). This was coupled by stabilization of tissue expenditure (FIG. 7E-7F) and correction of physiologic imbalances in the blood that occur during prolonged ischemia, most notably hyperkalemia and metabolic acidosis (FIG. 2F-2G). In addition, postmortem rigidity and lividity observed in ECMO animals were absent after OrganEx perfusion (FIG. 7E). Taken together, these observations indicate that following one hour of warm ischemia, OrganEx could reinstate and maintain circulation, and restore observed physiologic and metabolic parameters on a whole-body scale.


Example 3: Histological Analysis of Tissue Integrity

Upon restoration of systemic circulation and certain key metabolic parameters following OrganEx perfusion, next investigated was its effects on organ structural integrity and cytoarchitecture. The brain's three major cell types, neurons, astrocytes, and microglia in two regions most vulnerable to ischemia, the hippocampal CA1 subregion and the prefrontal cortex (PFC) were analyzed. The intensity of immunostaining for RBFOX3 (NeuN), a pan-neuronal marker, which has previously been shown to decrease in hypoxia, was lower in the ECMO and 7h WIT groups in both regions, as compared to OrganEx (FIG. 3A, FIG. 8F, 8H). While there were no observed differences in CA1 subregion between OrganEx and 0h and 1h WIT groups, we did observe reduced immunolabeling in OrganEx and 1h WIT group compared to 0h WIT in PFC (FIGS. 8H, 8I). This finding could be a result of more pronounced protein degradation in PFC or incomplete recovery due to short OrganEx intervention time. In addition, the number of astrocytes immunolabeled for GFAP was comparable between OrganEx and 0h WIT but was decreased in other experimental groups, in both, CA1 and PFC (FIGS. 8F, 8G, 9B, 9E). The analysis of GFAP immunolabeling fragmentation was increased in the 7h WIT and ECMO groups compared to OrganEx, which was similar to the 1h, and 0h WIT groups, suggesting loss of astrocytic integrity (FIGS. 3A, 3B, FIG. 8B, 8H, 8K). A similar trend was observed in PFC, with increased fragmentation in 7h WIT and ECMO groups, but failed to demonstrate statistical significance due to increased variance in 7h WIT group (FIGS. 8H, 8J). The density of microglial populations noted by IBA1 immunolabeling was comparable among OrganEx, 0h and 1h WIT groups in both CA1 and PFC, and differed from the ECMO group (FIGS. 3A, 3D, FIGS. 8F, 8H, 8L). Collectively, these findings indicate that across different analyzed brain regions and cell types, both tissue and cellular integrities were preserved and did not sustain additional observable damage following perfusion with OrganEx, consistent with previous study in the isolated porcine brain.


After assessing highly oxygen-sensitive brain structures and cell types, next investigated were the effects of OrganEx on tissue and cellular integrity in essential peripheral organs, including heart, lungs, liver, kidney, and pancreas. Utilizing hematoxylin and eosin (H&E) staining, hemorrhage, tissue edema, nuclear pyknosis, cell vacuolization, and cellular integrity were evaluated and were combined into a cumulative damage score according to the standard pathologic criteria. Notably, the OrganEx group showed a decrease in the H&E damage score, as compared to 7h WIT and ECMO groups (FIG. 3E-3H, FIGS. 9A-9J). Furthermore, organs treated with OrganEx perfusion exhibited signs of reduced hemorrhage and tissue edema when compared to the 1h WIT group. These results are indicative of the absence of injury promotion and cytoarchitectural damage as compared to ECMO, and more importantly, a reduction of H&E damage scores towards the 0h WIT state with OrganEx perfusion.


To further assess recovery of cytoarchitecture in the OrganEx intervention group compared with possible injury promotion in ECMO group, the cytoskeletal features of the kidney that are well-studied in this regard were investigated. Expression of renal cytoskeletal 3-actin is known to be upregulated in ischemic states. However, the reintroduction of autologous blood causes risk for cell injury and cytoskeletal disruption leading to protein loss. This analysis revealed reduced 3-actin immunoreactivity in the ECMO, as compared to OrganEx and other groups, which exhibited preserved immunoreactivity (FIG. 3J-3K). These data indicate that unlike OrganEx perfusion, the ECMO perfusion with autologous blood following prolonged warm ischemia may cause risk for further tissue damage through reperfusion.


Example 4: Analysis of Cell Death Processes

Because the OrganEx perfusate contains pharmacological suppressors of cell death and decreased cellular demise based on the histopathological analysis in the OrganEx group (FIG. 3E-3H, FIGS. 9A-9J) was observed, key proteins of key cell death pathways were next investigated by immunohistochemistry analysis. For apoptosis, immunolabeling intensity of activated caspase3 (actCASP3) and TUNEL assay was measured, and an increase was observed across peripheral organs such as heart, liver, kidney, and pancreas in the ECMO compared to the OrganEx group. Furthermore, the respective intensities of actCASP3 and TUNEL in the OrganEx were comparable to the 0h WIT group, which did not sustain ischemic injury, indicating that OrganEx perfusion diminished caspase3 activation and decreased apoptosis (FIG. 4A-4P).


The analysis of the CA1 and PFC revealed that the intensity of actCASP3 immunolabeling in the OrganEx group was lower than in the 0h and 1h WIT groups (FIGS. 4K-4M). Conversely intensity of TUNEL assay had lower trend in OrganEx group compared to the 7h WIT and ECMO groups (FIGS. 4N-4P). Thus, it is conceivable that the weak brain immunolabeling of actCASP3 in the OrganEx group can be explained by active suppression of actCAPS3 by the pharmacological compounds in the perfusate as previously reported, rather than cellular or protein destruction, as also supported by other evaluations (FIGS. 3A-3D, 6A, 8A-8L, 11H-11K, 14F,14G).


Next, to investigate pyroptosis, the cell death pathway triggered by proinflammatory signals, interleukin 1 beta (IL1B) immunohistochemistry was utilized. Across all investigated peripheral organs such as heart, liver, and kidney, IL1B immunolabeling intensity was comparable in 0h WIT and increased in ECMO when compared to OrganEx. In the brain, immunolabeling intensity was decreased in ECMO when compared to OrganEx group (FIGS. 10A-10E). Trends in both peripheral organs, and the brain are similar to the observed actCASP3 results (FIG. 4A-4E).


Finally, necroptosis and ferroptosis, two distinct cell death pathways were investigated by utilizing immunohistochemistry of their important proteins in the pathways, the receptor-interacting ser/thr kinase 3 (RIPK3) and the glutathione peroxidase 4 (GPX4), respectively. The results were consistent between the two cell death pathways and between all the organs evaluated such as brain, heart, liver, and kidney. Compared to OrganEx, immunolabeling intensity was comparable in 0h WIT and significantly decreased in 7h WIT and ECMO groups (FIGS. 10F-100).


Example 5: Metabolic and Functional Assessment of Organs

After observing improvements in metabolic function, tissue cytoarchitecture and cell death outcomes using OrganEx, cellular energy balance was next investigated in detail. The glucose uptake was measured in highly metabolic organs (brain, heart, kidney) using the fluorescent glucose analog, 2-NBDG23. This showed comparable levels of glucose uptake in the OrganEx and 0h WIT groups in all assessed organs and reduced cellular glucose capture in the ECMO group that may indicate impaired glucose utilization of cellular leakage (FIGS. 5A-5C). Such findings imply that recovery of cellular metabolism may have a reciprocal relationship with the restoration of systemic metabolic parameters (FIGS. 2D, 2E, 7D).


Indicators of cell- and tissue-level recovery in relevant organs were next tested. Cardiac assessment with electrocardiography (ECG) demonstrated spontaneous reemergence of QRS complexes during OrganEx perfusion, indicating ventricular depolarization (FIG. 5D). However, no QRS reemergence was observed in the ECMO group. To further evaluate recovery of ventricular activity, cardiomyocyte contractility was examined using bright-field microscopy of left ventricle tissue slices acquired at the experimental endpoint. Contractions in OrganEx and 0h WIT samples were observed, but complete absence in the ECMO group (FIG. 5E). Finally, investigated were cardiomyocyte biomarkers whose immunolabeling decreases with ischemia22. Left ventricle immunohistochemistry staining for biomarker troponin I revealed decreased immunolabeling with prolonged ischemia, and significantly lower immunolabeling intensity in the ECMO vs OrganEx group (FIGS. 11L, 11M).


Liver cellular recovery was assessed using immunostaining for albumin and factor V, which are non-structural liver-synthesized proteins with great abundance and short half-life, respectively. Compared to OrganEx group, immunolabeling intensities of both proteins were comparable in 0h WIT and significantly diminished in 7h WIT and ECMO groups (FIGS. 5F, 5G, 11N, 11O).


In the kidney, although many cellular features were preserved similar to 0h WIT in OrganEx groups, including tissue integrity (FIGS. 3H, 9D,9E), cell death (FIGS. 4A-4P, 10A-100), molecular and proliferative injury responses (FIGS. 9F-9J), and cellular metabolic indicators (FIG. 5C), the primary kidney functional metric, urine output, was minimal. Yet hypothermic perfusion is known to slow kidney function in patients with healthy organs and extracorporeal perfusion circuits can perturb endocrine, humoral, and neural factors regulating glomerular filtration even when renal perfusion and cellular health is adequate. Longer recovery time also may be required since low urine output often follows shock resuscitation.


Next, continuous electroencephalography (EEG) of the brain in OrganEx and ECMO groups was conducted, and no signs of global network activity were detected (FIGS. 11A-11E). In OrganEx group, we hypothesize this could be due to either inadequate brain recovery, requirement for longer recovery duration, perfusates' neuronal activity antagonists, anesthesia, hypothermic perfusion protocol, or their combined effects. Interestingly, while receiving carotid injection of contrast for cerebrovascular fluoroscopic imaging, OrganEx-perfused animals exhibited complex, non-purposeful, non-stereotyped movements of the head, neck, and torso from coordinated agonist/antagonist actions across multiple joints and muscle units. This was not observed during imaging of sedated alive or ECMO-treated animals (FIG. 11F). EEG patterns during these movements were not interpretable due to movement-induced artifacts but were flat immediately before and after the movements (FIG. 11G). Whether these movements are initiated from preferential interruption of cerebral descending inhibition of motor patterns or from positive action at subcortical, spinal, peripheral nerve, or neuromotor unit levels is difficult to determine. However, the ability for them to be executed does indicate the preservation of efferent motor output function at least at the level of the spinal cervical cord or its roots.


Next, it was sought to investigate the longer-term actions of OrganEx perfusion on cellular viability. Yet because of regulatory constraints and inability to extend the perfusion protocol beyond 6h, organotypic hippocampal brain slice cultures (BSCs) were utilized, to monitor features of tissues previously exposed to different perfusion interventions. BSCs were prepared at the beginning of experiments (0h WIT), at the end of ECMO and OrganEx perfusions, and from time-matched 7h WIT controls, and were cultured for 14 days while assessing tissue integrity and protein synthesis using Click-iT assay screening. BSCs from the 7h WIT group failed these measures due to severe tissue degradation. Based on visual inspection and DAPI staining, BSCs from the ECMO group were more fragile than OrganEx samples, and most disintegrated by day 14 (FIGS. 5H, 5I). BSC tissue integrity was preserved through day−14 in the OrganEx group equal to 0h WIT despite having had one additional ischemic exposure (1× during initial 1h warm ischemia, 1×during brain extraction, 5-10 mins). Similarly, protein synthesis was comparable through day-14 in the OrganEx and 0h WIT groups and decreased in ECMO across different hippocampal regions (FIGS. 5J, 5K, 11H-11K).


Example 6: Analysis of Cell Type-Specific Transcriptomic Changes

To investigate transcriptomic responses to distinct ischemic exposures and the effects of the OrganEx intervention, single-nucleus RNA-sequencing (snRNA-seq, see Methods) was performed. The computational analysis of snRNA-seq data revealed major transcriptomically-defined cell types (t-types) that were comparable to publicly available human and mouse single-cell datasets (FIGS. 12A-12F). Yet prominent transcriptomic distinctions were also identified between the same t-types across all experimental groups (FIGS. 14A-17I). This extensive cellular taxonomic resource expands upon previous studies and allows for systematic investigation of transcriptomic changes in multiple porcine organs and cell-types exposed to distinct WITs and reperfusion conditions ((FIGS. 13A-13D, 14A-17B), (Tables: 7-23) http://resources.sestanlab.org/OrganEx)).


To compare cell type responsiveness to ischemia based on transcriptomic changes across experimental groups, Augur prioritization was performed and t-types with the greatest transcriptomic divergence were highlighted. This identified prominent changes in neurons, cardiomyocytes, hepatocytes, and proximal convoluted tubule (PCT) cells, consistent with t-types validated in earlier studies and prompting detailed sub-analysis (FIG. 6A-6D). First, it was evaluated whether patterns of transcriptomic changes within OrganEx versus other groups reflect molecular and cellular changes observed in previous studied by assessing for transcriptomic enrichment of corresponding gene sets (Methods). Comparisons between OrganEx and other groups revealed significant enrichment of gene sets facilitating cytoskeletal assembly, DNA repair, ATP metabolism, and suppression of apoptosis and other major cell death pathways across all major cell types in the organs investigated (FIGS. 6A-6D, FIGS. 14A-17I). These data corroborate earlier findings by demonstrating that OrganEx both inhibited progression of cellular injury (e.g., cytoarchitecture, cell death, DNA fragmentation) and promoted repair by modulating cellular pathways on a transcriptomic level. Likewise, genes encoding proteins involved in cell-death, oxidative injury and inflammatory signaling (Tables. 4, 5, 6) are broadly regulated in favor of cell survival in the OrganEx group compared with ECMO in all organs studied. This correlates with choices of pharmacological compounds in the OrganEx perfusate, which had been included using a hypothesis-based, rational-polytherapy approach to modulate these pathways (FIGS. 14A-17D)


Further investigation of OrganEx actions upon glial inflammatory responses underlying brain injury progression after ischemia showed that hippocampal microglial pro-inflammatory transcriptional enhancement was absent in the OrganEx group. Conversely, microglial inflammatory and astrocytic pan-reactive transcriptomic signatures were upregulated in ECMO and 1h WIT groups, respectively. (FIG. 5A). Combined with immunofluorescence analyses of microglial IBA1 and astrocytic GFAP staining (FIGS. 3A-3D, FIGS. 8F-8L), these findings demonstrate that OrganEx intervention modulates the glial inflammatory response.


The transcriptomic signatures of tissue and cellular functioning in heart, liver, and kidney specimens were then evaluated. Cardiomyocytes in the OrganEx group exhibited enrichment of genes orchestrating action potential formation and the well-described shift28 toward glycolytic metabolism following ischemia signifying cardiomyocyte viability (FIG. 6B). In the liver and kidney, hepatocytes and PCT cells were enriched for cytochrome P450 and PCT transporter genes, respectively, in OrganEx versus other groups-though not quite to levels of 0h WIT controls-suggesting preservation of organ-specific functions (FIGS. 6C, 6D). Liver acute-phase reactant and kidney injury marker genes also were notably lower following OrganEx reperfusion than after ECMO or 7h WIT (FIGS. 6C,6D). These data corroborate earlier findings on tissue integrity and cellular activity (FIGS. 3E-3H, FIGS. 5B, 5G; FIGS. 9A-9J; FIGS. 11A-11O).


To identify transcriptomic patterns across experimental groups more systematically, and to determine functional gene modules, we performed co-expression analysis on differentially expressed genes across groups. Eigengenes of each module designated key gene expression trends, with subsequent gene ontology (GO) analyses highlighting relevant biological pathways (FIGS. 14A-17E, FIG. 34). Herein, OrganEx and ECMO had divergent trends across different modules. Gene modules having eigengene increases in the OrganEx group featured GO terms related to cellular upkeep and organ-specific functions. Conversely, modules having increased eigengenes in the ECMO group had GO terms related to cell death (liver and kidney). Finally, analysis of ligand/receptor pairings of t-types showed reduced interactions related to inflammatory pathways (e.g., IL1, IL6, ICAM, VCAM) in OrganEx versus ECMO groups (FIGS. 14A-17I). This mirrors earlier findings that OrganEx reperfusion following ischemia diminishes markers of inflammation, associated with overall decreased cellular injury and augmented repair/protection processes when compared to ECMO (FIGS. 10A-10E, FIGS. 14A-17D). Taken together, snRNA-seq analysis supports cellular and tissue-level findings of decreased cellular injury and the initiation of certain molecular and cellular repair processes following OrganEx intervention.









TABLE 4





Genes involved in cell death

















APAF1



BCL2



BID



BIRC2



BIRC3



CASP10



CASP3



CASP6



CASP7



CASP8



CASP9



CFLAR



CHUK



DFFA



DFFB



FADD



GAS2



LMNA



MAP3K14



NFKB1



NFKBIA



RELA



RIPK1



SPTAN1



TNFRSF25



TNFSF10



TRADD



TRAF2



XIAP
















TABLE 5





Genes involved in oxidative stress

















ABCA1



ADAMTS13



ADIPOQ



AGER



AKR1C2



APP



BMP6



CASP3



CFTR



CLCN3



CP



CXCL8



CYBB



CYP2E1



EDN1



EGFR



ELANE



F3



FPR1



G6PD



GCLC



GPX1



GSTM1



HMOX1



HP



HSD17B10



HSPA4



HSPB1



HTATIP2



IL11



IL13



ITGA2B



ITGB3



JAK2



KPNA2



MAP2K3



MAPK1



MAPK14



MAPK3



MPO



MUC1



MUC5AC



NCF4



NFE2L2



NOS1



NOS2



NOS3



NQO1



NUP153



NUP88



OLR1



PAOX



PEPD



PLA2G7



PLD1



PON1



PRDX1



PRDX2



PRDX3



PRDX4



PRKCB



PRKCD



PRKCZ



PSEN2



PTGER4



PTK2B



RECQL4



SERPINF1



SFTPD



SMPD3



SOD1



SOD3



STAT3



STIM1



TFRC



TGFB1



THG1L



TLR4



TP53



TXN



TXN2



VCAN



VWF

















TABLE 6





Genes involved in inflammation

















ABCC1



ABCD2



ABHD12



ABI3BP



ABR



ACE



ACER3



ACKR1



ACKR2



ACOD1



ACP5



ADA



ADAM8



ADAM17



ADAMTS12text missing or illegible when filed



ADCY1



ADCY7



ADCY8



ADCYAP1



ADIPOQ



ADORA1



ADORA2A



ADORA2B



ADORA3



ADRA2A



ADRB2



AFAP1L2



AGER



AGT



AGTR1A



AGTR1B



AGTR2



AHCY



AHCYL



AHSG



AIM2



AIMP1



AK7



AKNA



AKT1



ALDH2



ALOX5



ALOX5AP



ALOX15



ANKRD42



ANO6



ANXA1



APOD



APP



APPL1



APPL2



AREL1



ASH1L



ATM



ATRN



AXL



B4GALT1



BAP1



BCL6



BCL6B



BCR



BDKRB1



BDKRB2



BRD4



BST1



C1QTNF3



C1QTNF12



C2CD4A



C2CD4B



C3



C5AR1



C5AR2



CALCA



CALCRL



CAMK1D



CAMK4



CAMP



CARD9



CASP1



CASP4



CASP6



CASP12



CCL1



CCL2



CCL3



CCL4



CCL5



CCL6



CCL7



CCL8



CCL9



CCL11



CCL12



CCL17



CCL19



CCL20



CCL21A



CCL21B



CCL21C



CCL22



CCL24



CCL25



CCL26



CCN3



CCN4



CCR1



CCR1L1



CCR2



CCR3



CCR4



CCR5



CCR6



CCR7



CCRL2



CD5L



CD6



CD14



CD24A



CD28



CD40



CD40LG



CD44



CD47



CD68



CD81



CD96



CD163



CD180



CD200



CD200R1



CD200R2



CD200R3



CD200R4



CD276



CD300A



CDH5



CDK19



CEBPA



CEBPB



CELA1



CELF1



CERS6



CFH



CHID1



CHIL1



CHIL3



CHIL4



CHIL5



CHIL6



CHRNA7



CHST1



CHST2



CHST4



CIITA



CLCF1



CLEC10A



CLOCK



CMA1



CMKLR1



CNR1



CNR2



CNTNAP2text missing or illegible when filed



CR2



CRH



CRHBP



CRLF2



CRP



CSF1



CSF1R



CSPG4



CSRP3



CST7



CTLA2A



CTNNBIP1text missing or illegible when filed



CTSC



CTSS



CUEDC2



CX3CL1



CX3CR1



CXCL1



CXCL2



CXCL3



CXCL5



CXCL9



CXCL10



CXCL13



CXCL15



CXCL17



CXCR2



CXCR3



CXCR6



CYBA



CYBB



CYLD



CYP19A1



CYP26B1



CYSLTR1



DAB2IP



DAGLA



DAGLB



DDT



DDX3X



DHX9



DICER1



DNASE1



DNASE1L3



DPEP1



DROSHA



DUOXA1



DUOXA2



DUSP10



ECM1



EDNRA



EDNRB



EIF2AK1



ELANE



ELF3



ENPP3



EPHA2



EPHB2



EPHB6



EPHX2



ETS1



EXT1



EZH2



F2



F2R



F2RL1



F3



F8



F12



F630003A1text missing or illegible when filed



FABP4



FANCA



FANCD2



FCER1A



FCER1G



FCGR1



FCGR2B



FCGR3



FEM1A



FEM1AL



FFAR2



FFAR3



FFAR4



FGFR1



FN1



FNDC4



FOXF1



FOXP1



FOXP3



FPR1



FPR2



FPR3



FPR-RS3



FPR-RS4



FPR-RS6



FPR-RS7



FUT7



GAL



GATA3



GBP5



GGT1



GGT5



GHRL



GHSR



GIT1



GJA1



GM5849



GPER1



GPR4



GPR17



GPR31B



GPR33



GPRC5B



GPS2



GPSM3



GPX1



GPX2



GPX4



GRN



GSDMD



GSTP1



H2BC1



HAMP



HAVCR2



HC



HCK



HDAC5



HDAC7



HDAC9



HGF



HIF1A



HK1



HMGB1



HMGB2



HMOX1



HNRNPA0



HP



HPS1



HRH4



HSPD1



HYAL1



HYAL2



HYAL3



ICAM1



IDO1



IER3



IF135



IFNG



IGF1



IGH-7



IGH-8



IGHG1



IGHG2A



IGHG2B



IL1A



IL1B



IL1F10



IL1R1



IL1R2



IL1RAP



IL1RL1



IL1RL2



IL1RN



IL2



IL2RA



IL4



IL4RA



IL5RA



IL6



IL10



IL12B



IL13



IL16



IL17A



IL17B



IL17C



IL17D



IL17F



IL17RA



IL17RB



IL17RC



IL17RE



IL18



IL18R1



IL18RAP



IL20RB



IL22



IL22RA2



IL23A



IL23R



IL25



IL27



IL31RA



IL33



IL34



IL36A



IL36B



IL36G



IL36RN



IRAK2



IRF3



IRF5



ISL1



ITGA2



ITGAM



ITGAV



ITGB1



ITGB2



ITGB2L



TGB6



ITIH4



JAK2



JAM3



KARS



KDM6B



KIT



KL



KLK1B1



KLKB1



KLRH1



KNG1



KPNA6



KRT1



KRT16



LACC1



LAT



LBP



LDLR



LEP



LGALS9



LIAS



LILRA5



LILRB4A



LILRB4B



LIPA



LOXL3



LPCAT3



LPL



LRFN5



LRRC19



LRRK2



LTA



LTB4R1



LTB4R2



LXN



LY86



LY96



LYN



MACIR



MAP2K3



MAPK8



MAPK14



MAPKAPK2



MAS1



MCPH1



MDK



MECOM



MEFV



MEP1B



METRNL



MFHAS1



MGLL



MIF



MIR21A



MIR147



MIR155



MIR301



MIR324



MIR883B



MIR7116



MIR7578



MMP8



MRGPRA3



MS4A2



MSMP



MTOR



MUC19



MVK



MYD88



MYLK3



MYO5A



NAIP1



NAIP2



NAIP5



NAIP6



NAIP7



NAPEPLD



NCF1



NDFIP1



NDST1



NDUFC2



NDUFS4



NFE2L1



NFE2L2



NFKB1



NFKBIA



NFKBIB



NFKBID



NFKBIZ



NINJ1



NKIRAS2



NLRC3



NLRC4



NLRP1A



NLRP1B



NLRP3



NLRP4A



NLRP4B



NLRP4C



NLRP4E



NLRP4F



NLRP6



NLRP9A



NLRP9B



NLRP9C



NLRP10



NLRP12



NLRX1



NMI



NOD2



NOS2



NOTCH1text missing or illegible when filed



NOTCH2text missing or illegible when filed



NPPA



NPY



NPY5R



NR1D1



NR1D2



NR1H3



NR1H4



NRROS



NT5E



NUPR1



ODAM



OLR1



ORM1



ORM2



OSM



OTULIN



P2RX1



P2RX7



PARK7



PARP4



PBK



PBXIP1



PDCD4



PDE2A



PDE5A



PER1



PF4



PGLYRPtext missing or illegible when filed



PGLYRPtext missing or illegible when filed



PIK3AP1



PIK3CD



PIK3CG



PJA2



PLA2G2text missing or illegible when filed



PLA2G2text missing or illegible when filed



PLA2G3



PLA2G4Atext missing or illegible when filed



PLA2G5



PLA2G7



PLA2G10text missing or illegible when filed



PLAA



PLCG2



PLD3



PLD4



PLGRKTtext missing or illegible when filed



PLP1



PMP22



PNMA1



POLB



PPARA



PPARD



PPARG



PPBP



PRCP



PRDX2



PRKCA



PRKCQ



PRKCZ



PRKD1



PROC



PSEN2



PSMA1



PSMB4



PSTPIP1



PTAFR



PTGDR



PTGER1



PTGER2



PTGER3



PTGER4



PTGES



PTGFR



PTGIR



PTGIS



PTGS1



PTGS2



PTN



PTPN2



PXK



PYCARD



RABGEF1



RARRES2text missing or illegible when filed



RASGRP1



RB1



RBPJ



REG3A



REG3B



REG3G



REL



RELA



RELB



RHBDD3



RICTOR



RIPK1



RORA



RPS6KA4



RPS6KA5



RPS19



RTN4



S1PR3



S100A7A



S100A8



S100A9



SAA1



SAA2



SAA3



SAA4



SBNO2



SCGB1A1



SCN9A



SCNN1B



SCYL1



SCYL3



SDC1



SEH1L



SELE



SELENOS



SELP



SEMA7A



SERPINA1B



SERPINA3N



SERPINB1A



SERPINB9



SERPINE1



SERPINF1



SERPINF2



SETD4



SGMS1



SHARPIN



SHPK



SIGIRR



SIGLECE



SIGLECG



SIRPA



SLAMF1



SLAMF8



SLC7A2



SLC11A1



SLIT2



SMAD3



SMPDL3B



SNAP23



SNCA



SNX4



SOCS3



SOCS5



SOD1



SPATA2



SPHK1



SPN



STAB1



STAP1



STARD7



STAT3



STAT5A



STAT5B



STING1



STK39



SUCNR1



SYK



SYT11



TAC1



TAC4



TAFA3



TARM1



TBC1D23



TBXA2R



TCIRG1



TFF2



TGFB1



THBS1



THEMIS2



TICAM1



TICAM2



TIMP1



TIRAP



TLR1



TLR2



TLR3



TLR4



TLR5



TLR6



TLR7



TLR8



TLR9



TLR11



TLR12



TLR13



TNF



TNFAIP3



TNFAIP6



TNFAIP8L2



TNFRSF1A



TNFRSF1B



TNFRSF4



TNFRSF11A



TNFSF4



TNFSF11



TNFSF18



TNIP1



TNIP2



TOLLIP



TPSB2



TRADD



TRAF3IP2



TREM1



TREM2



TREX1



TRIL



TRIM55



TRP73



TRPV1



TRPV4



TSLP



TSPAN2



TTBK1



TTC39AOS1



TUSC2



TYRO3



UACA



ULK4



UMOD



UNC13D



VAMP7



VAMP8



VNN1



VPS35



WDR83



WFDC1



WNT5A



XCL1



YWHAZ



ZBP1



ZC3H12A



ZFP35



ZFP36



ZFP580



ZP3








text missing or illegible when filed indicates data missing or illegible when filed














TABLE 7







Upregulated modules in the hippocampus








0 h PMI
UPREGULATED MODULES












vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PM
M1
protein homotetramerization
0.00130534
6
7




protein tetramerization
0.00166205






protein homooligomerization
0.00399511






cellular response to organonitrogen
0.00437743






compound cellular response to nitrogen
0.00604231






compound protein complex
0.00604231






oligomerization
0.00609269






response to organonitrogen compound






M2
purine-containing compound metabolic
0.00399511
5
1




process





7 h PM
M1
regulation of nervous system development
0.01547127
11
7




neuron development
0.01547127






central nervous system development
0.01547127






neuron differentiation
0.01627243






cellular component morphogenesis
0.0166483






generation of neurons
0.0166483






neurogenesis
0.0166483





M2
transmembrane receptor protein
0.01547127
10
2




tyrosine kinase signaling pathway







actin cytoskeleton organization
0.01547127


















TABLE 8







Downregulated modules in the hippocampus


DOWNREGULATED MODULES













MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PM
M1
transport along microtubule
0.00984952
20
11




microtubule-based transport
0.00984952






organelle transport along
0.00984952






microtubule
0.00996313






cytoskeleton-dependent
0.01121427






intracellular transport
0.01612674






microtubule-based movement
0.01680074






regulation of phosphatase
0.01744301






activity
0.01744301






regulation of dephosphorylation
0.02451






establishment of organelle







localization







glycoprotein metabolic process







organelle localization






M2
positive regulation of chemotaxis
0.00984952
9
18




regulation of chemotaxis
0.01058596






positive regulation of response to
0.01058596






external stimulus







endothelial cell migration
0.01121427






taxis
0.01407071






chemotaxis
0.01407071






epithelial cell migration
0.01407071






tissue migration
0.01407071






epithelium migration
0.01407071






ameboidal-type cell migration
0.01506690






taxis
0.01058596
7
4



M3
chemotaxis
0.01058596






transmembrane receptor protein
0.01121427






tyrosine kinase signaling
0.01407071






pathway







tube development






M4
protein secretion
0.01680074
13
10




regulation of peptide secretion
0.01680074






regulation of protein secretion
0.01680074






translation
0.01744301






peptide secretion
0.01744301






peptide biosynthetic process
0.01744301






amide biosynthetic process
0.01935849






regulation of secretion by cell
0.01935849






regulation of secretion
0.02104555






peptide metabolic process
0.02246823





M5
regulation of growth
0.01710375
14
2




growth
0.01744301





M6
positive regulation of secretion by cell
0.01744301
20
5




positive regulation of secretion
0.01744301






transmembrane receptor protein
0.02379342






tyrosine kinase signaling pathway







regulation of secretion by cell
0.03027594






regulation of secretion
0.0332764




7 h PM

cytoplasmic translation
0.00025664






peptide metabolic process






M1
translation
0.00307113
4
5




amide biosynthetic process
0.00307113






peptide biosynthetic process
0.00307113







0.00307113





M2
regulation of response to external stimulus
0.00819095
8
1
















TABLE 9







Upregulated modules in the heart









UPREGULATED MODULES












0 h PMI vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PMI
M1
Heart process
0.00029963
24
26




Heart contraction
0.00029963






Muscle contraction
0.00060022






Muscle system process
0.00068257






Circulatory system process
0.00070174






Blood circulation
0.00070174






Cardiac muscle contraction
0.00122338






Striated muscle contraction
0.00190513






Regulation of system process
0.00510668






Regulation of striated muscle
0.00533685






contraction






M2
viral RNA genome replication
0.00117626
10
32




viral genome replication
0.00575265






positive regulation of
0.00608795






endopeptidase activity
0.00608795






positive regulation of
0.00729271






peptidase activity
0.00735398






I-kappaB kinase/NF-kappaB
0.00753531






signaling
0.00786995






endothelial cell migration
0.00786995






protein localization to plasma
0.00825285






membrane







peptidyl-serine







phosphorylation







protein localization to cell







periphery







peptidyl-serine modification






M3
tRNA aminoacylation for
0.00190513
14
10




protein translation
0.00190513






tRNA aminoacylation
0.00190513






amino acid activation
0.00608795






tRNA metabolic process
0.00789626






cellular amino acid metabolic
0.01634324






process
0.01835367






ncRNA metabolic process
0.01931046






translation
0.02409173






peptide biosynthetic process
0.02884619






amide biosynthetic process







peptide metabolic process






M4
regulation of cell cycle G1/S
0.00354947
8
23




phase transition
0.0036058






regulation of heart contraction
0.00398175






regulation of blood circulation
0.00406808






heart process
0.00406808






heart contraction
0.00406808






negative regulation of cell
0.00496187






growth
0.00496187






cell cycle G1/S phase
0.00496187






transition
0.00533685






negative regulation of growth







regulation of phosphatase







activity regulation of







dephosphorylation






M5
positive regulation of protein
0.00510668
6
15




secretion
0.00533685






establishment of organelle
0.00533685






localization
0.00575265






positive regulation of peptide
0.00608795






secretion
0.00608795






cell division
0.00608795






organelle localization
0.00608795






positive regulation of secretion
0.00608795






by cell
0.00616309






positive regulation of secretion







positive regulation of protein







transport







regulation of protein secretion







regulation of peptide secretion





7 h PMI
M1
response to muscle stretch
0.00251036
18
6




heart process
0.01122943






heart contraction
0.01122943






response to mechanical
0.01122943






stimulus
0.01447972






circulatory system process
0.01447972






blood circulation






M2
regulation of myosin-light-
0.00251036
19
83




chain-phosphatase activity
0.00891652






regulation of phosphatase
0.01122943






activity
0.01122943






epithelial to mesenchymal
0.01122943






transition
0.01122943






response to hormone
0.01122943






angiogenesis
0.01122943






blood vessel morphogenesis
0.01122943






blood vessel development
0.01122943






vasculature development







cardiovascular system







development







ameboidal-type cell migration






M3
sensory perception
0.00891652
15
47




skeletal system development
0.01122943






cartilage development
0.01122943






connective tissue development
0.01122943






positive regulation of
0.01122943






angiogenesis
0.01122943






positive regulation of
0.01122943






vasculature development
0.01122943






nervous system process
0.01122943






sensory perception of sound
0.01122943






sensory perception of







mechanical stimulus







cell cycle arrest






M4
response to hormone
0.01122943
6
2




cellular response to hormone
0.01122943






stimulus



















TABLE 10







Downregulated modules in the heart


DOWNREGULATED MODULES













MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PMI
M1
muscle cell proliferation
0.01672329
21
11




smooth muscle cell
0.01672329






proliferation







regulation of smooth muscle
0.01672329






cell proliferation







negative regulation of cell
0.02238411






adhesion







second-messenger-mediated
0.03629741






signaling







purine-containing compound
0.03629741






metabolic process







response to organonitrogen
0.04567474






compound







regulation of response to
0.04567474






external stimulus







cell-cell adhesion
0.04567474






negative regulation of cell
0.04567474






proliferation






M2
brain development
0.01672329
18
9




head development
0.01846202






central nervous system development
0.02238411






negative regulation of locomotion
0.03629741






transmembrane receptor protein tyrosine
0.04567474






kinase signaling pathway







response to hormone
0.04567474






cellular response to hormone stimulus
0.04567474






amide biosynthetic process
0.04567474






tube development
0.04821183





M3
positive regulation of cytokine production
0.01672329
4
1



M4
cell-matrix adhesion
0.02238411
20
3




cell-substrate adhesion
0.03629741






membrane organization
0.04567474




7 h PMI
M1
muscle tissue morphogenesis
0.00001171
15
28




cardiac muscle tissue morphogenesis
0.00001171






muscle organ morphogenesis
0.00001171






circulatory system process
0.00007087






blood circulation
0.00007087






cardiac muscle tissue development
0.00009565






heart morphogenesis
0.00010493






striated muscle tissue development
0.00014682






muscle organ development
0.00014682






muscle tissue development
0.00015933





M2
carbohydrate metabolic process
0.00147773
4
9




purine-containing compound metabolic process
0.0015631






nucleobase-containing compound catabolic
0.00171625






process







heterocycle catabolic process
0.00185306






aromatic compound catabolic process
0.00185306






cellular nitrogen compound catabolic process
0.00185306






organic cyclic compound catabolic process
0.00198857






nucleobase-containing small molecule
0.00215788






metabolic process







drug metabolic process
0.00238158
















TABLE 11







Upregulated modules in the liver









UPREGULATED MODULES












0 h PMI vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PM
M1
positive regulation of protein kinase B
0.00078186
2
11




signaling
0.00080542






protein kinase B signaling
0.00080542






regulation of protein kinase B signaling
0.00129131






regulation of Wnt signaling pathway
0.00129131






canonical Wnt signaling pathway
0.00129131






regulation of canonical Wnt signaling pathway
0.00129131






positive regulation of cellular protein
0.00140713






localization
0.00140713






Wnt signaling pathway
0.00153183






cell-cell signaling by wnt







cell surface receptor signaling pathway involved







in cell-cell signaling






M2
alpha-amino acid metabolic process
0.00136955
23
23




cellular amino acid metabolic process
0.00203971






lipid localization
0.00348064






phospholipid transport
0.004241






organophosphate ester transport
0.00645779






cellular modified amino acid metabolic process
0.0066749






regulation of lipid localization
0.0089595






reactive oxygen species metabolic process
0.01777175






sulfur compound metabolic process
0.02065402






circulatory system process
0.02065402





M3
peroxisome organization
0.00366503
25
33




fatty acid beta-oxidation
0.00459225






fatty acid metabolic process
0.00505183






fatty acid catabolic process
0.00645779






fatty acid oxidation
0.00645779






lipid oxidation
0.0066749






monocarboxylic acid catabolic process
0.00832782






monocarboxylic acid metabolic process
0.01343222






carboxylic acid transport
0.01718533






organic acid transport
0.01718533





M4
symbiont process
0.02325045
11
1


7 h PMI
M1
fatty acid metabolic process
0.0018047
23
50




monocarboxylic acid metabolic process
0.0053895






cellular lipid catabolic process
0.0053895






lipid catabolic process
0.00606029






peroxisome organization
0.00606029






regulation of fatty acid metabolic process
0.00632649






fatty acid beta-oxidation
0.00704627






neutral lipid metabolic process
0.00745002






acylglycerol metabolic process
0.00745002






fatty acid catabolic process
0.00808599





M2
peptide hormone processing
0.0018047
17
14




drug transmembrane transport
0.00606029






drug transport
0.00808599






hormone metabolic process
0.00902764






protein processing
0.01391672






organic anion transport
0.01827469






protein maturation
0.01827469






regulation of hormone levels
0.02109436






anion transport
0.02867452






import into cell
0.03054423





M3
lipid localization
0.0053895
17
17




phospholipid transport
0.00606029






organophosphate ester transport
0.00736024






regulation of reactive oxygen species metabolic
0.00808599






process
0.00808599






regulation of lipid localization
0.01441779






reactive oxygen species metabolic process
0.01739625






response to metal ion
0.01745934






lipid transport
0.01827469






circulatory system process
0.01827469






blood circulation
















TABLE 12







Downregulated modules in the liver


DOWNREGULATED MODULES













MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PMI
M1
regulation of endocytosis
0.00001034






regulation of vesicle-mediated transport
0.00003473






regulation of receptor-mediated endocytosis
0.00003473






endocytosis
0.00004369






import into cell
0.00004597
8
12




positive regulation of endocytosis
0.00004597






receptor-mediated endocytosis
0.00016189






positive regulation of receptor-mediated
0.00054826






endocytosis
0.00392522






negative regulation of cellular catabolic process
0.00453021






negative regulation of catabolic process






M2
bile acid biosynthetic process
0.00013665
8
18




bile acid metabolic process
0.00021854






small molecule biosynthetic process
0.00080919






steroid biosynthetic process
0.00099556






organic hydroxy compound biosynthetic process
0.00154562






monocarboxylic acid biosynthetic process
0.00224344






steroid metabolic process
0.00282644






organic hydroxy compound metabolic process
0.0041208






carboxylic acid biosynthetic process
0.0041208






organic acid biosynthetic process
0.0041208






negative regulation of blood coagulation
0.00045951






negative regulation of hemostasis
0.00045951

19




negative regulation of coagulation
0.00052135






regulation of blood coagulation
0.0005927





M3
regulation of hemostasis
0.0005927
9





negative regulation of wound healing
0.0005927






negative regulation of response to wounding
0.0005927






regulation of coagulation
0.0006521






blood coagulation
0.00099556






hemostasis
0.00099556





M4
reactive oxygen species metabolic process
0.0021294
9
2




transmembrane receptor protein tyrosine kinase
0.00561605






signaling pathway
0.00000003






negative regulation of very-low-density lipoprotein







particle remodeling





7 h PM
M1
regulation of very-low-density lipoprotein
0.00000006
9
138




particle remodeling
0.00000043






very-low-density lipoprotein particle
0.00000043






remodeling
0.00000043






triglyceride-rich lipoprotein particle
0.00000043






remodeling
0.00000046






sterol import
0.00000046






cholesterol import
0.00000154






phospholipid efflux
0.00000154






high-density lipoprotein particle remodeling







protein-containing complex remodeling







protein-lipid complex remodeling






M2
cytoplasmic translation
0.00001502
10
12




translation
0.00004966






peptide biosynthetic process
0.00005325






amide biosynthetic process
0.00007408






peptide metabolic process
0.00010533






ribosomal small subunit biogenesis
0.000137






rRNA processing
0.00099778






rRNA metabolic process
0.0018087






ribosome biogenesis
0.00196663






ncRNA processing
0.00482245






coenzyme biosynthetic process
0.00223213






drug metabolic process
0.00265038






cofactor biosynthetic process
0.00322454






monocarboxylic acid biosynthetic process
0.00482245





M3
coenzyme metabolic process
0.00628091
14
16




carboxylic acid biosynthetic process
0.010031






organic acid biosynthetic process
0.010031






cofactor metabolic process
0.01473374






taxis
0.01570123






chemotaxis
0.01570123
















TABLE 13







Upregulated modules in the kidney









UPREGULATED MODULES












0 h PMI
MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PM
M1
carboxylic acid transport
0.00045523
2
4




organic acid transport
0.00045523






organic anion transport
0.00047204






anion transport
0.0008361





M2
transforming growth factor beta receptor
0.00045523
3
7




signaling pathway







cellular response to transforming growth factor
0.00046771






beta stimulus







forming growth factor beta transmembrane
0.00046771






receptor protein serine/threonine kinase







negative regulation of cell cycle
0.00102429






cellular response to growth factor stimulus
0.00105664






response to growth factor
0.0010605






regulation of mRNA splicing, via spliceosome
0.00047204






regulation of mRNA processing
0.0008361






regulation of RNA splicing
0.00100785





M3
regulation of mRNA metabolic process
0.00168308
5
10




mRNA splicing, via spliceosome
0.00176775






RNA splicing, via transesterification reactions
0.00176775






with bulged adenosine as nucleophile







RNA splicing, via transesterification reactions
0.00176775






RNA splicing
0.00266268






mRNA processing
0.00266268






mRNA metabolic process
0.0056398





M4
ossification
0.00185349
9
3




response to nutrient levels
0.00308148






response to extracellular stimulus
0.00324251





M5
monosaccharide metabolic process
0.0056398
21
8




negative regulation of multi-organism process
0.01152943






carbohydrate metabolic process
0.02064605






viral process
0.03197381






dephosphorylation
0.03684634






regulation of multi-organism process
0.03769913






symbiont process
0.03877931






regulation of response to external stimulus
0.0430254





M6
protein acetylation
0.00574013
13
2




protein acylation
0.00818346





M7
positive regulation of proteolysis
0.00818346
9
1


7 H PMI
M1
autophagy
0.00179789
3
4




positive regulation of cellular catabolic process
0.00179789






process utilizing autophagic mechanism
0.00179789






positive regulation of catabolic process
0.00179789





M2
muscle system process
0.00437296
9
2




nervous system process
0.00738351





M3
drug metabolic process
0.0056181
6
3




cell morphogenesis
0.0056181






cellular component morphogenesis
0.0056181
















TABLE 14







Downregulated modules in the kidney


DOWNREGULATED MODULES













MODULE
TOP TERMS
Q VAL
GENES
TERMS















1 h PMI
M1
sulfur compound metabolic process
0.00574843
3
1



M2
reactive oxygen species metabolic
0.00826615
10
3




process







drug metabolic process
0.02068022






protein complex oligomerization
0.02083823






reactive oxygen species metabolic
0.00826615
13
3



M3
process
0.00903419






sulfur compound metabolic process
0.01045815






regulation of anatomical structure size






M4
import into cell
0.00826615
17
9




carbohydrate metabolic process
0.00826615






regulation of carbohydrate metabolic
0.00826615






process







regulation of vesicle-mediated transport
0.00826615






positive regulation of endocytosis
0.00826615






monosaccharide metabolic process
0.00965095






negative regulation of secretion
0.01045815






regulation of endocytosis
0.01250846






regulation of canonical Wnt signaling
0.01664705






pathway







regulation of small molecule metabolic
0.01790918






process






M5
response to lipid
0.02155897
10
1


7 h PMI
M1
cytoplasmic translation
0.00085548
5
5




translation
0.00358328






peptide biosynthetic process
0.00358328






amide biosynthetic process
0.00377282






peptide metabolic process
0.00426545





M2
response to peptide
0.00125726
3
6




cellular response to peptide
0.00125726






cellular response to organonitrogen
0.0028522






compound







membrane receptor protein tyrosine kinase
0.00303333






signaling p







cellular response to nitrogen
0.00324142






compound







response to organonitrogen
0.00358328






compound






M3
cell part morphogenesis
0.00359538
9
6




cellular response to hormone stimulus
0.00972276






negative regulation of protein
0.00972276






phosphorylation







negative regulation of phosphorylation
0.00972276






response to hormone
0.01170763






cellular component morphogenesis
0.0119158





M4
positive regulation of secretion
0.00813972






carbohydrate derivative biosynthetic
0.00972276
10
3




process







regulation of secretion
0.01262213
















TABLE 15







Upregulated modules in the hippocampus for OrganEx vs other experimental conditions








OrganEx
UPREGULATED MODULES












vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
regulation of calcium ion transmembrane
0.00000148
3
62




transporter







regulation of protein dephosphorylation
0.00000264






regulation of calcium ion transmembrane
0.00000264






transport







regulation of ion transmembrane transporter
0.00000836






activity







regulation of calcium ion transport
0.00000836






regulation of dephosphorylation
0.00000836






regulation of transmembrane transporter
0.00000836






activity







regulation of transporter activity
0.00000836






regulation of cytosolic calcium ion
0.00000933






concentration







protein dephosphorylation
0.00000946





M2
postsynapse organization
0.00002732
5
11




synapse organization
0.00013829






modification by host of symbiont
0.00034457






morphology or physiology







interaction with symbiont
0.00036868






modification of morphology or physiology
0.00051716






of other organism involved in symbiotic







interaction







modification of morphology or physiology
0.00105763






of other organism







positive regulation of multi-organism
0.00113891






process







regulation of symbiosis, encompassing
0.00225101






mutualism through parasitism







actin cytoskeleton organization regulation of
0.00477062






multi-organism process







regulation of multi-organism process
0.00477062





M3
positive regulation of cell-matrix adhesion
0.00034457
11
14




integrin-mediated signaling pathway
0.00061588






positive regulation of cell-substrate adhesion
0.00094367






regulation of cell-matrix adhesion
0.00133405






regulation of cell-substrate adhesion
0.00321521






cell-matrix adhesion
0.00370559






cell-substrate adhesion
0.00705772






positive regulation of cell adhesion
0.00740948






regulation of ion transport
0.01072926






positive regulation of cellular component
0.01473763






biogenesis






M4
establishment of organelle localization
0.0015234
5
2




organelle localization
0.00260079





M5
negative regulation of protein
0.00197
11
11




serine/threonine kinase activity







negative regulation of protein kinase activity
0.00521825






negative regulation of kinase activity
0.00598533






negative regulation of transferase activity
0.00750629






negative regulation of protein
0.01223217






phosphorylation







regulation of protein serine/threonine kinase
0.01355639






activity







negative regulation of phosphorylation
0.01365901






peptidyl-tyrosine phosphorylation
0.01407734






peptidyl-tyrosine modification
0.01429091






positive regulation of apoptotic process
0.01976654





M6
cellular response to metal ion
0.00394424
15
15




sodium ion transmembrane transport
0.00440242






cellular response to inorganic substance
0.00445226






sodium ion transport
0.00471215






regulation of ion transmembrane transporter
0.00611441






activity







regulation of transmembrane transporter
0.006273






activity







regulation of transporter activity
0.00705772






response to metal ion
0.00750629






regulation of cation transmembrane
0.00830569






transport







regulation of ion transmembrane transport
0.0108403





M7
purine ribonucleotide metabolic process
0.00483097
8
9




ribonucleotide metabolic process
0.00492221






purine nucleotide metabolic process
0.00501519






ribose phosphate metabolic process
0.00507639






purine-containing compound metabolic
0.00598533






process







nucleotide metabolic process
0.00737697






nucleoside phosphate metabolic process
0.00742628






organic cyclic compound catabolic process
0.00819991






nucleobase-containing small molecule
0.00928187






metabolic process





1 h PMI
M1
negative regulation of protein
0.00632916
8
11




serine/threonine kinase activity







negative regulation of protein kinase activity
0.0068929






negative regulation of kinase activity
0.0068929






negative regulation of transferase activity
0.00705237






negative regulation of protein
0.00848203






phosphorylation







regulation of protein serine/threonine kinase
0.00859112






activity







negative regulation of phosphorylation
0.00859112






peptidyl-tyrosine phosphorylation
0.00859112






peptidyl-tyrosine modification
0.00859112






positive regulation of apoptotic process
0.01171437





M2
postsynapse organization
0.00632916
17
28




synapse organization
0.00632916






positive regulation of viral process
0.00776015






neuron projection morphogenesis
0.00848203






plasma membrane bounded cell projection
0.00859112






morphogenesis







cell projection morphogenesis
0.00859112






cell part morphogenesis
0.00982363






positive regulation of multi-organism
0.01171437






process







establishment of organelle localization
0.01496545






regulation of membrane potential
0.01570713





M3
regulated exocytosis
0.00632916
12
2




exocytosis
0.00705237





M4
heart process
0.00632916
9
28




regulation of heart contraction
0.00632916






regulation of heart rate
0.00632916






striated muscle contraction
0.00632916






response to calcium ion
0.00632916






regulation of blood circulation
0.00632916






heart contraction
0.00632916






cardiac muscle contraction
0.00632916






muscle contraction
0.0068929






calcium-mediated signaling
0.0068929





M5
calcium-mediated signaling
0.00632916
5
3




second-messenger-mediated signaling
0.0068929






supramolecular fiber organization
0.00763474




7 h PMI
M1
central nervous system myelination
0.00010421
12
21




axon ensheathment in central nervous
0.00010421






system







oligodendrocyte development
0.00062285






oligodendrocyte differentiation
0.00062285






ensheathment of neurons
0.00065125






axon ensheathment
0.00065125






myelination
0.00065125






glial cell development
0.00067302






glial cell differentiation
0.0011697






gliogenesis
0.00260164





M2
postsynapse organization
0.00132508
17
91




supramolecular fiber organization
0.00258787






symbiont process
0.00258787






positive regulation of multi-organism
0.00290139






process







synapse organization
0.00614214






cellular response to interferon-gamma
0.00614214






regulation of symbiosis, encompassing
0.00669687






mutualism through parasitism







regulation of protein secretion
0.00820244






regulation of peptide secretion
0.0090486






negative regulation of supramolecular fiber
0.00947399






organization






M3
establishment of protein localization to
0.00338045
4
2




organelle







regulation of cellular protein localization
0.00669687





M4
negative regulation of MAPK cascade
0.01245222
17
10




negative regulation of protein kinase activity
0.0163574






negative regulation of kinase activity
0.01741828






regulation of ERKI and ERK2 cascade
0.01784267






ERK1 and ERK2 cascade
0.01998293






negative regulation of transferase activity
0.02039825






negative regulation of proteolysis
0.02214126






negative regulation of protein
0.0262057






phosphorylation







negative regulation of phosphorylation
0.02835256






negative regulation of intracellular signal
0.03926507






transduction





ECMO
M1
membrane depolarization
0.00022659
13
40




regulation of membrane potential
0.00140469






regulation of membrane depolarization
0.00140469






regulation of metal ion transport
0.00140469






regulation of cation transmembrane
0.00140469






transport







regulation of ion transmembrane transporter
0.00140469






activity







regulation of transmembrane transporter
0.00140469






activity







regulation of transporter activity
0.00140469






regulation of ion transmembrane transport
0.00140469






amyloid precursor protein metabolic process
0.00140469





M2
cellular metal ion homeostasis
0.00140469
11
15




glutamate receptor signaling pathway
0.00140469






cellular ion homeostasis
0.00141584






cellular cation homeostasis
0.00141584






metal ion homeostasis
0.00141584






cellular chemical homeostasis
0.00162159






cation homeostasis
0.00162159






inorganic ion homeostasis
0.00162159






cellular homeostasis
0.00183596






positive regulation of cytosolic calcium ion
0.00468417






concentration






M3
vesicle organization
0.00140469
4
3




endocytosis
0.00162159






import into cell
0.00183596





M4
regulation of cytoskeleton organization
0.00210499
3
1



M5
supramolecular fiber organization
0.01236373
8
1



M6
glycerolipid metabolic process
0.01362313
16
1
















TABLE 16







Downregulated modules in the hippocampus for OrganEx vs other experimental conditions













MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
cell-cell adhesion via plasma-membrane adhesion
0.0004168
6
2




molecules







cell-cell adhesion
0.00377508





M2
action potential
0.0004168
7
3




multicellular organismal signaling
0.0004168






regulation of membrane potential
0.00146461





M3
cellular response to growth factor stimulus
0.00261105
5
2




response to growth factor
0.00261637




1 h PMI
M1
cell-matrix adhesion
0.0023427
9
3




cell-substrate adhesion
0.00483403






regulation of cytoskeleton organization
0.00966187





M2
cellular component morphogenesis
0.029452
18
1


7 h PMI
M1
substrate-dependent cell migration
0.00021131
11
4




integrin-mediated signaling pathway
0.00086613






cell-matrix adhesion
0.00370986






cell-substrate adhesion
0.00607305





M2
monovalent inorganic cation transport
0.00090489
13
6




potassium ion transport
0.00441522






potassium ion transmembrane transport
0.00441522






cellular potassium ion transport
0.00441522






regulation of ERKI and ERK2 cascade
0.00621087






ERK1 and ERK2 cascade
0.00684584




ECMO
M1
negative regulation of transcription from RNA
0.00050986
10
28




polymerase II promoter in response to stress







negative regulation of inclusion body assembly
0.00050986






regulation of inclusion body assembly
0.00058354






inclusion body assembly
0.00088919






regulation of protein ubiquitination
0.00112921






regulation of protein modification by small protein
0.00122915






conjugation or removal







signal transduction involved in cell cycle checkpoint
0.00123005






signal transduction involved in DNA integrity
0.00123005






checkpoint







signal transduction involved in DNA damage
0.00123005






checkpoint







regulation of transcription from RNA polymerase II
0.00180748






promoter in response to stress






M2
negative regulation of transcription from RNA
0.00050986
6
23




polymerase II promoter in response to stress







regulation of transcription from RNA polymerase II
0.00112921






promoter in response to stress







regulation of DNA-templated transcription in response
0.00117198






to stress







cellular response to reactive oxygen species
0.00199647






response to reactive oxygen species
0.00248837






negative regulation of viral process
0.00248837






transforming growth factor beta receptor signaling
0.00261758






pathway







cellular response to transforming growth factor beta
0.00375985






stimulus







response to transforming growth factor beta
0.00375985






cellular response to oxidative stress
0.00375985





M3
regulation of substrate adhesion-dependent cell
0.003814
23
39




spreading







regulation of cell development
0.00762995






substrate adhesion-dependent cell spreading
0.00762995






nervous system process
0.00836972






cognition
0.00836972






regulation of cell morphogenesis involved in
0.00870874






differentiation







regulation of cell-substrate adhesion
0.01664242






positive regulation of supramolecular fiber organization
0.01744524






cellular response to peptide
0.01745126






response to peptide
0.02004258





M4
positive regulation of cell migration
0.0197859
13
3




positive regulation of cellular component movement
0.02026998






positive regulation of cell motility
0.02026998
















TABLE 17







Upregulated modules in the heart for OrganEx vs other experimental conditions









UPREGULATED MODULES












OrganEx vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
regulation of extrinsic apoptotic signaling pathway
0.00002361
24
179




via death domain receptors







positive regulation of extrinsic apoptotic signaling
0.00002361






pathway via death domain receptors







extrinsic apoptotic signaling pathway via death
0.00011521






domain receptors







positive regulation of TRAIL-activated apoptotic
0.00029119






signaling pathway







regulation of extrinsic apoptotic signaling pathway
0.00032231






positive regulation of extrinsic apoptotic signaling
0.00032313






pathway







regulation of apoptotic signaling pathway
0.00034095






regulation of TRAIL-activated apoptotic signaling
0.00034095






pathway







positive regulation of smooth muscle cell
0.00034095






proliferation







oncostatin-M-mediated signaling pathway
0.00034095





M2
establishment of protein localization to organelle
0.00029119
24
122




regulation of cellular protein localization
0.00029119






positive regulation of cellular protein localization
0.00029119






positive regulation of protein import into nucleus
0.00029119






positive regulation of protein import
0.00029119






protein import
0.00032231






regulation of protein import into nucleus
0.00034095






regulation of protein import
0.00034095






positive regulation of nucleocytoplasmic transport
0.00039583






positive regulation of protein localization to
0.00051733






nucleus






M3
positive regulation of MAP kinase activity
0.01239568
19
10




regulation of MAP kinase activity
0.01929366






activation of protein kinase activity
0.02032994






positive regulation of protein serine/threonine
0.02046562






kinase activity







regulation of protein serine/threonine kinase
0.0339451






activity







positive regulation of MAPK cascade
0.03835472






positive regulation of protein kinase activity
0.0393374






positive regulation of kinase activity
0.04337171






cellular response to growth factor stimulus
0.04459056






response to growth factor
0.04609302






positive regulation of smooth muscle cell
0.00016128






proliferation





1 h PMI
M1
smooth muscle cell proliferation
0.00017323
9
109




regulation of smooth muscle cell proliferation
0.00017323






negative regulation of plasminogen activation
0.00017323






negative regulation of fibrinolysis
0.00017323






muscle cell proliferation
0.00019664






regulation of fibrinolysis
0.00020283






regulation of plasminogen activation
0.00023696






positive regulation of blood coagulation
0.00029821






positive regulation of coagulation
0.00029821






chaperone-mediated protein folding
0.00116853





M2
positive regulation of ATPase activity
0.00156601
17
52




positive regulation of cell cycle process
0.00176265






positive regulation of cytokinesis
0.00196763






negative regulation of MAP kinase activity
0.00203168






positive regulation of cell division
0.00222306






regulation of translational initiation
0.00235603






establishment of protein localization to organelle
0.00235603






regulation of ATPase activity
0.00235603






establishment of protein localization to
0.0027263






mitochondrion







cell morphogenesis involved in differentiation
0.00446098





M3
calcium ion transport
0.00759034
10
8




negative regulation of cell differentiation
0.00835761






divalent metal ion transport
0.00879372






divalent inorganic cation transport
0.00879372






cell morphogenesis
0.0116237






membrane organization
0.01258141






cellular component morphogenesis
0.01358402






extrinsic apoptotic signaling pathway via death
0.0001177






domain receptors





7 h PMI
M1
regulation of extrinsic apoptotic signaling pathway
0.00031453
21
179




via death domain receptors







positive regulation of angiogenesis
0.00031453






positive regulation of vasculature development
0.00031453






regulation of transcription from RNA polymerase
0.00033563






II promoter in response to stress







oncostatin-M-mediated signaling pathway
0.00033563






extrinsic apoptotic signaling pathway
0.00033998






regulation of DNA-templated transcription in
0.00033998






response to stress







negative regulation of plasminogen activation
0.00033998






negative regulation of fibrinolysis
0.00033998






calcium ion transport
0.0001177





M2
divalent metal ion transport
0.0001177
16
49




divalent inorganic cation transport
0.0001177






calcium ion transmembrane transport
0.00033563






cell activation involved in immune response
0.00693738






intracellular protein transport
0.00854985






cell-cell adhesion
0.00854985






cellular homeostasis
0.00854985






regulation of phosphatase activity
0.00991974






central nervous system development
0.01151349






positive regulation of ATPase activity
0.00174275





M3
regulation of ATPase activity
0.0026367
12
5




establishment of protein localization to
0.00293313






mitochondrion







protein localization to mitochondrion
0.00293313






establishment of protein localization to organelle
0.01267787






cellular component assembly involved in
0.00109672






morphogenesis 0.00109672 myofibril assembly





ECMO
M1
striated muscle cell development
0.00109672
11
16




muscle cell development
0.00116538






striated muscle cell differentiation
0.00215042






actomyosin structure organization
0.00378743






muscle cell differentiation
0.00378743






muscle structure development
0.00695858






actin filament organization
0.00909936






regulation of ion transport
0.01399645






positive regulation of ATPase activity
0.00109672





M2
regulation of ATPase activity
0.00109672
5
3




negative regulation of intracellular signal
0.00755618






transduction







positive regulation of vascular smooth muscle cell
0.00109672






proliferation






M3
regulation of vascular smooth muscle cell
0.00132483
11
24




proliferation







vascular smooth muscle cell proliferation
0.00132483






positive regulation of smooth muscle cell
0.00146751






proliferation







regulation of transcription from RNA polymerase
0.00161299






II promoter in response to stress







regulation of DNA-templated transcription in
0.00180501






response to stress







smooth muscle cell proliferation
0.00369898






regulation of smooth muscle cell proliferation
0.00369898






positive regulation of apoptotic process
0.00378743






positive regulation of programmed cell death
0.00378743






negative regulation of intracellular signal
0.00109672






transduction






M4
negative regulation of intrinsic apoptotic signaling
0.00132483
5
14




pathway







negative regulation of cellular amide metabolic
0.00146751






process







regulation of intrinsic apoptotic signaling pathway
0.00200305






negative regulation of apoptotic signaling pathway
0.00281162






intrinsic apoptotic signaling pathway
0.00378743






regulation of cellular amide metabolic process
0.00419639






positive regulation of cellular catabolic process
0.00484584






regulation of apoptotic signaling pathway
0.00494742






positive regulation of cytokine production
0.00573414






ATP hydrolysis coupled ion transmembrane
0.00132483






transport






M5
ATP hydrolysis coupled cation transmembrane
0.00132483
15
25




transport







ATP hydrolysis coupled transmembrane transport
0.00132483






mitochondrial membrane organization
0.00420776






mitochondrial transport
0.00747788






cellular response to nutrient levels
0.00795956






cellular response to extracellular stimulus
0.00843396






response to nutrient levels
0.01107734






response to extracellular stimulus
0.01193224






regulation of membrane potential
0.01399645






angiogenesis
0.01930628





M6
blood vessel morphogenesis
0.02092554
12
7




blood vessel development
0.0214603






vasculature development
0.02245115






cardiovascular system development
0.02245115






tube morphogenesis
0.02341853






tube development
0.02626913
















TABLE 18







Downregulated modules in the heart for OrganEx vs other experimental conditions













MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
muscle tissue morphogenesis
0.00266479
23
25




ventricular cardiac muscle tissue development
0.00266479






cardiac ventricle morphogenesis
0.00266479






ventricular cardiac muscle tissue morphogenesis
0.00266479






cardiac muscle tissue morphogenesis
0.00266479






muscle organ morphogenesis
0.00266479






cardiac ventricle development
0.00329834






tissue morphogenesis
0.00337476






cardiac chamber morphogenesis
0.00337476






cardiac chamber development
0.00369421





M2
ncRNA metabolic process
0.03335282
23
6




cellular response to hormone stimulus
0.03860622






transmembrane receptor protein tyrosine kinase
0.03860622






signaling pathway







response to hormone
0.04748336






positive regulation of cellular component biogenesis
0.0495055






supramolecular fiber organization
0.0495055




1 h PMI
M1
muscle tissue morphogenesis
0.00004401
22
51




ventricular cardiac muscle tissue development
0.00004401






cardiac ventricle morphogenesis
0.00004401






ventricular cardiac muscle tissue morphogenesis
0.00004401






cardiac muscle tissue morphogenesis
0.00004401






muscle organ morphogenesis
0.00004401






cardiac ventricle development
0.00005839






cardiac chamber morphogenesis
0.00007473






cardiac chamber development
0.00010322






tissue morphogenesis
0.00021319





M2
regulation of embryonic development
0.00236854
18
30




cell-substrate adherens junction assembly
0.00482378






focal adhesion assembly
0.00482378






cell-substrate junction assembly
0.0050007






adherens junction assembly
0.0050007






adherens junction organization
0.00613601






positive regulation of cell migration
0.0109135






positive regulation of cell motility
0.0110496






positive regulation of cellular component movement
0.0111725






cell junction assembly
0.01299785





M3
regulation of cell-matrix adhesion
0.00669186
17
13




actomyosin structure organization
0.00944387






regulation of cell-substrate adhesion
0.01221792






cell-matrix adhesion
0.01271436






negative regulation of cell migration
0.02123794






cell-substrate adhesion
0.02143607






negative regulation of cell motility
0.02143607






actin filament organization
0.02143607






negative regulation of cellular component movement
0.02176389






negative regulation of locomotion
0.02255749




7 h PMI
M1
muscle tissue morphogenesis
0.00000104
10
29




ventricular cardiac muscle tissue development
0.00000104






cardiac ventricle morphogenesis
0.00000104






ventricular cardiac muscle tissue morphogenesis
0.00000104






cardiac muscle tissue morphogenesis
0.00000104






muscle organ morphogenesis
0.00000104






cardiac ventricle development
0.00000138






cardiac chamber morphogenesis
0.00000177






muscle structure development
0.00000226






cardiac chamber development
0.00000226





M2
regulation of transmembrane transport
0.00425822
9
1


ECMO
M1
negative regulation of chondrocyte differentiation
0.00185788
24
23




negative regulation of cartilage development
0.00185788






regulation of chondrocyte differentiation
0.00196174






regulation of cartilage development
0.00277101






chondrocyte differentiation
0.00385886






cartilage development
0.0057775






connective tissue development
0.00633818






cellular response to interleukin-1
0.00633818






cellular response to BMP stimulus
0.00803146






response to BMP
0.00803146





M2
response to peptide
0.00185788
14
15




cellular response to peptide
0.00185788






cellular response to organonitrogen compound
0.00385886






cellular response to nitrogen compound
0.00554635






response to organonitrogen compound
0.00626552






cellular response to peptide hormone stimulus
0.00626552






response to peptide hormone
0.00633818






regulation of supramolecular fiber organization
0.01274967






actin filament organization
0.0131885






cellular response to hormone stimulus
0.02135503





M3
regulation of cysteine-type endopeptidase activity
0.00336961
17
32




involved in apoptotic process







regulation of cysteine-type endopeptidase activity
0.00385886






glycosaminoglycan metabolic process
0.00469825






aminoglycan metabolic process
0.0050056






negative regulation of response to DNA damage
0.0057775






stimulus







regulation of endopeptidase activity
0.00619305






regulation of peptidase activity
0.00633818






positive regulation of cysteine-type endopeptidase
0.00790601






activity involved in apoptotic process







ossification
0.00816077






morphogenesis of an epithelium
0.00844225
















TABLE 19







Upregulated modules in the liver for OrganEx vs other experimental condition









UPREGULATED MODULES












OrganEx vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
endoplasmic reticulum calcium ion homeostasis
0.00398603
22
70




positive regulation of ATPase activity
0.00546596






cellular response to extracellular stimulus
0.00546596






response to nutrient levels
0.00546596






cellular response to nutrient levels
0.00546596






intracellular protein transport
0.00546596






retrograde protein transport, ER to cytosol
0.00546596






endoplasmic reticulum to cytosol transport
0.00546596






response to extracellular stimulus
0.00549078






cellular response to external stimulus
0.00664246





M2
positive regulation of cell-matrix adhesion
0.0050993
12
31




regulation of apoptotic signaling pathway
0.00546596






positive regulation of cell-substrate adhesion
0.0054697






negative regulation of intrinsic apoptotic signaling
0.00664246






pathway







positive regulation of cellular component biogenesis
0.00669441






regulation of cell-matrix adhesion
0.00669441






negative regulation of intracellular signal transduction
0.00764427






positive regulation of apoptotic signaling pathway
0.00798568






regulation of intrinsic apoptotic signaling pathway
0.00896691






regulation of cell-substrate adhesion
0.00951003





M3
positive regulation of protein tyrosine kinase activity
0.00546596
18
25




regulation of protein tyrosine kinase activity
0.00669441






positive regulation of protein kinase activity
0.00859284






positive regulation of kinase activity
0.00959975






positive regulation of apoptotic process
0.01084788






positive regulation of programmed cell death
0.01090735






positive regulation of peptidyl-tyrosine
0.0138127






phosphorylation







negative regulation of cell adhesion
0.01681081






regulation of peptidyl-tyrosine phosphorylation
0.01949561






protein dephosphorylation
0.01949561




1 h PMI
M1
sphingomyelin biosynthetic process
0.0000256
12
14




sphingomyelin metabolic process
0.00028511






sphingolipid biosynthetic process
0.00189297






membrane lipid biosynthetic process
0.00286198






phospholipid biosynthetic process
0.00314563






sphingolipid metabolic process
0.00354297






ammonium ion metabolic process
0.0045515






membrane lipid metabolic process
0.0045515






phospholipid metabolic process
0.00838847






positive regulation of GTPase activity
0.0088777





M2
protein refolding
0.00041268
12
73




positive regulation of interleukin-10 production
0.00114827






regulation of interleukin-10 production
0.00169446






interleukin-10 production
0.0017855






T cell mediated immunity
0.00190809






lymphocyte activation involved in immune response
0.00223168






regulation of protein stability
0.00237253






protein folding
0.00314563






adaptive immune response based on somatic
0.00368494






recombination of immune receptors built from







immunoglobulin superfamily domains







supramolecular fiber organization
0.0045515





M3
response to interferon-beta
0.00169446
17
29




cellular response to cytokine stimulus
0.00186289






type I interferon signaling pathway
0.00186289






cellular response to type I interferon
0.00189297






negative regulation of intracellular signal transduction
0.00195108






response to type I interferon
0.00237253






cellular response to interferon-gamma
0.00368494






cytokine-mediated signaling pathway
0.00398415






cellular response to interleukin-1
0.0045515






response to interferon-gamma
0.00485815





M4
negative regulation of cell adhesion
0.0045515
7
4




defense response to other organism
0.00838847






positive regulation of apoptotic process
0.01173558






positive regulation of programmed cell death
0.01184138




7 h PMI
M1
negative regulation of intracellular signal transduction
0.00098861
24
103




cellular response to cytokine stimulus
0.00156467






response to interferon-beta
0.00589599






type I interferon signaling pathway
0.00737842






cellular response to type I interferon
0.00740207






retrograde protein transport, ER to cytosol
0.00889139






endoplasmic reticulum to cytosol transport
0.00889139






response to type I interferon
0.00893024






negative regulation of ERK1 and ERK2 cascade
0.00898752






cellular response to interferon-gamma
0.01325363





M2
peptide hormone processing
0.00105037
13
12




hormone metabolic process
0.01325363






cell killing
0.01445314






protein processing
0.01445314






negative regulation of cell adhesion
0.01560983






protein maturation
0.0162748






regulation of hormone levels
0.01877447






defense response to other organism
0.02386996






symbiont process
0.02927052






peptide metabolic process
0.03190489





M3
phosphatidylethanolamine biosynthetic process
0.00105037
27
27




regulation of transcription from RNA polymerase II
0.00105037






promoter in response to stress







regulation of DNA-templated transcription in response
0.00105037






to stress







phosphatidylethanolamine metabolic process
0.00150736






negative regulation of transcription from RNA
0.00193167






polymerase II promoter in response to stress







glycerophospholipid biosynthetic process
0.01445314






protein folding
0.01445314






calcium ion transport
0.01560983






phospholipid biosynthetic process
0.01560983






divalent metal ion transport
0.0162748




ECMO
M1
positive regulation of fat cell differentiation
0.00276459
21
12




regulation of fat cell differentiation
0.00425328






fat cell differentiation
0.00436295






connective tissue development
0.00521535






regulation of ossification
0.00707335






ossification
0.01007525






neuron death
0.01007525






skeletal system development
0.01199471






hematopoietic or lymphoid organ development
0.03558779






negative regulation of hydrolase activity
0.03792403





M2
drug metabolic process
0.00276459
16
32




reactive oxygen species metabolic process
0.00276459






regulation of reactive oxygen species biosynthetic
0.00361438






process







neurotransmitter metabolic process
0.00425328






reactive oxygen species biosynthetic process
0.00425328






dicarboxylic acid metabolic process
0.00425328






cofactor metabolic process
0.00425328






protein homotetramerization
0.00425328






cellular response to organonitrogen compound
0.00425328






cellular modified amino acid metabolic process
0.00515027





M3
response to inorganic substance
0.00425328
4
2




response to drug
0.00575263


















TABLE 20







Downregulated modules in the liver for OrganEx vs other experimental conditions













MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
bile acid biosynthetic process
0.00031886
9
13




bile acid metabolic process
0.00032782






small molecule biosynthetic process
0.00146015






steroid biosynthetic process
0.00146015






organic hydroxy compound biosynthetic
0.00191362






process







monocarboxylic acid biosynthetic process
0.00271082






steroid metabolic process
0.00314049






organic hydroxy compound metabolic process
0.00434973






carboxylic acid biosynthetic process
0.00434973






organic acid biosynthetic process
0.00434973





M2
tube morphogenesis
0.00783003
7
2




tube development
0.00835127




1 h PMI
M1
organic hydroxy compound metabolic process
0.00041564
10
19




small molecule catabolic process
0.00041564






lipid catabolic process
0.00041564






alcohol catabolic process
0.00041564






organic hydroxy compound catabolic process
0.00042391






monocarboxylic acid metabolic process
0.00082197






fatty acid catabolic process
0.00082197






monocarboxylic acid catabolic process
0.0010703






cellular lipid catabolic process
0.00184709






viral genome replication
0.00184709





M2
small molecule biosynthetic process
0.00155758
11
4




carboxylic acid biosynthetic process
0.00560495






organic acid biosynthetic process
0.00560495






regulation of response to external stimulus
0.01648373




7 h PMI
M1
regulation of endocytosis
0.0000003
9
75




regulation of receptor-mediated endocytosis
0.00000079






regulation of vesicle-mediated transport
0.00000184






endocytosis
0.00000265






import into cell
0.00000376






receptor-mediated endocytosis
0.00000837






regulation of very-low-density lipoprotein
0.00002529






particle clearance







negative regulation of very-low-density
0.00002529






lipoprotein particle clearance







chylomicron remnant clearance
0.00002529






triglyceride-rich lipoprotein particle clearance
0.00002529





M2
small molecule catabolic process
0.00045254
11
20




carboxylic acid biosynthetic process
0.00048814






organic acid biosynthetic process
0.00048814






alpha-amino acid catabolic process
0.00071999






cellular amino acid catabolic process
0.00079081






small molecule biosynthetic process
0.00144404






coenzyme biosynthetic process
0.00167035






cofactor biosynthetic process
0.00246223






alpha-amino acid metabolic process
0.00284418






monocarboxylic acid biosynthetic process
0.00357393





M3
primary alcohol metabolic process
0.00062878
12
4




alcohol metabolic process
0.0043331






organic hydroxy compound metabolic process
0.00773974






drug metabolic process
0.01946794





M4
negative regulation of angiogenesis
0.00071999
6
13




negative regulation of blood vessel
0.00073575






morphogenesis







negative regulation of vasculature development
0.00079436






regulation of angiogenesis
0.00284418






regulation of vasculature development
0.00312124






angiogenesis
0.0043331






blood vessel morphogenesis
0.00467035






blood vessel development
0.00505178






small molecule biosynthetic process
0.00536108






vasculature development
0.00537425




ECMO
M1
negative regulation of innate immune response
0.02465491
19
40




negative regulation of immune response
0.02898008






regulation of calcium ion transmembrane
0.02898008






transport







protein processing
0.03198994






regulation of response to external stimulus
0.03198994






negative regulation of defense response
0.03198994






protein maturation
0.03198994






negative regulation of cell adhesion
0.03198994






circulatory system process
0.03198994






calcium ion transmembrane transport
0.03198994





M2
cellular component morphogenesis
0.03198994
21
14




positive regulation of cell development
0.03198994






response to endoplasmic reticulum stress
0.03308581






regulation of cell morphogenesis
0.03500906






positive regulation of cell adhesion
0.03583142






actin filament organization
0.03583142






regulation of protein stability
0.040358






regulation of cell development
0.04147795






cell morphogenesis
0.04906785






dephosphorylation
0.05084461





M3
transmembrane receptor protein tyrosine kinase
0.03198994
9
5




signaling pathway







metal ion homeostasis
0.03198994






cation homeostasis
0.03198994






inorganic ion homeostasis
0.03198994






endomembrane system organization
0.03198994
















TABLE 21







Upregulated modules in the kidney for OrganEx vs other experimental conditions









UPREGULATED MODULES












OrganEx vs
MODULE
TOP TERMS
Q VAL
GENES
TERMS















0 h PMI
M1
protein folding
0.00000036
21
205




chaperone-mediated protein complex assembly
0.00000036






telomerase holoenzyme complex assembly
0.00000332






protein refolding
0.00001041






telomere maintenance via telomerase
0.00002933






RNA-dependent DNA biosynthetic process
0.00004271






telomere maintenance via telomere
0.00004271






lengthening







regulation of DNA biosynthetic process
0.00008467






regulation of protein stability
0.00009942






telomere maintenance
0.00013759





M2
actin cytoskeleton reorganization
0.00065265
5
11




negative regulation of MAPK cascade
0.00128835






regulation of intracellular transport
0.00387651






regulation of vesicle-mediated transport
0.00421455






positive regulation of cellular catabolic process
0.00441408






negative regulation of protein phosphorylation
0.00465765






negative regulation of phosphorylation
0.00512152






positive regulation of catabolic process
0.0051579






actin cytoskeleton organization
0.00616101






regulation of cellular protein localization
0.00617329





M3
protein tetramerization
0.00677288
16
17




innate immune response-activating signal
0.00723792






transduction







pattern recognition receptor signaling pathway
0.00723792






activation of innate immune response
0.00985675






positive regulation of innate immune response
0.01317658






immune response-activating signal
0.01453597






transduction







immune response-regulating signaling
0.01572326






pathway







regulation of innate immune response
0.0158122






positive regulation of defense response
0.0158122






activation of immune response
0.01950167





M4
dephosphorylation
0.01918327
11
1


1 h PMI
M1
telomerase holoenzyme complex assembly
0.0000033
20
76




chaperone-mediated protein complex assembly
0.00002344






positive regulation of telomerase activity
0.00021783






regulation of telomerase activity
0.00033656






protein folding
0.0004495






positive regulation of DNA biosynthetic
0.0004551






process







telomere maintenance via telomerase
0.00049629






protein refolding
0.00058816






RNA-dependent DNA biosynthetic process
0.00058816






telomere maintenance via telomere
0.00058816






lengthening






M2
vitamin transmembrane transport
0.00089093
20
17




negative regulation of anoikis
0.00095354






regulation of anoikis
0.001341






vitamin transport
0.00159456






anoikis
0.00160714






positive regulation of apoptotic signaling
0.00960626






pathway







regulation of extrinsic apoptotic signaling
0.01003699






pathway







extrinsic apoptotic signaling pathway
0.01707675






negative regulation of cellular catabolic
0.02206534






process







negative regulation of catabolic process
0.02460865




7 h PMI
M1
protein folding
0.00007133
22
164




chaperone-mediated protein complex assembly
0.00007133






mitotic spindle assembly
0.00120742






telomere maintenance via telomerase
0.00120742






protein refolding
0.00120742






negative regulation of transcription from RNA
0.00120742






polymerase II promoter in response to stress







negative regulation of inclusion body assembly
0.00120742






telomerase holoenzyme complex assembly
0.00120742






‘de novo’ protein folding
0.00120742






‘de novo’ posttranslational protein folding
0.00120742





M2
positive regulation of cellular protein
0.0043662
5
4




localization







positive regulation of protein transport
0.00532702






positive regulation of establishment of protein
0.00552056






localization







regulation of cellular protein localization
0.00744499





M3
regulation of intrinsic apoptotic signaling
0.00476218
11
5




pathway







negative regulation of apoptotic signaling
0.00591462






pathway







regulation of response to DNA damage
0.00744499






stimulus







intrinsic apoptotic signaling pathway
0.00828698






regulation of apoptotic signaling pathway
0.01219699





M4
actin cytoskeleton organization
0.00744499
5
1


ECMO
M1
response to thyroid hormone
0.00289388
23
49




cellular response to thyroid hormone stimulus
0.00289388






regulation of transcription from RNA
0.00774834






polymerase II promoter in response to stress







cellular response to glucose starvation
0.00774834






regulation of DNA-templated transcription in
0.00774834






response to stress







circadian rhythm
0.00774834






rhythmic process
0.00774834






maintenance of location
0.00774834






positive regulation of smooth muscle cell
0.00774834






proliferation







smooth muscle cell proliferation
0.01219399





M2
protein polyubiquitination
0.00774834
6
1



M3
protein stabilization
0.00774834
6
3




regulation of protein stability
0.00924636






regulation of chromosome organization
0.01025647





M4
positive regulation of intracellular transport
0.00774834
7
3




regulation of intracellular transport
0.00858876






microtubule cytoskeleton organization
0.01406365





M5
cellular response to oxidative stress
0.00774834
9
5




response to oxidative stress
0.01179599






regulation of transmembrane transport
0.01219399






regulation of protein catabolic process
0.01406365






response to organonitrogen compound
0.02146332





M6
mRNA processing
0.00774834
5
2




mRNA metabolic process
0.00924636
















TABLE 22







Downregulated modules in the kidney for OrganEx vs other experimental conditions











MODULE
TOP TERMS
Q VAL
GENES
TERMS














M1
gluconeogenesis
0.00022628
9
9



hexose biosynthetic process
0.00022628





monosaccharide biosynthetic process
0.00022628





glucose metabolic process
0.00127219





carbohydrate biosynthetic process
0.00146553





hexose metabolic process
0.00146553





monosaccharide metabolic process
0.00223435





carbohydrate metabolic process
0.00637556





small molecule biosynthetic process
0.01099155




M2
carboxylic acid transport
0.00090887
19
13



organic acid transport
0.00090887





organic anion transport
0.00223435





fatty acid transport
0.00223435





monocarboxylic acid transport
0.00293503





anion transport
0.0051951





regulation of stress-activated MAPK cascade
0.0138882





regulation of stress-activated protein kinase
0.0138882





signaling






cascade






stress-activated MAPK cascade
0.01395919





stress-activated protein kinase signaling cascade
0.01395919




M3
fatty acid oxidation
0.00293503
18
12



lipid oxidation
0.0029948





monosaccharide metabolic process
0.00783306





alpha-amino acid metabolic process
0.00833857





cellular amino acid metabolic process
0.01341131





fatty acid metabolic process
0.01395919





lipid modification
0.01395919





carbohydrate metabolic process
0.02064605





anion transport
0.02908113





monocarboxylic acid metabolic process
0.02956181




M1
sialylation
0.00023984
14
7



response to insulin
0.00117307





response to peptide hormone
0.00227106





response to peptide
0.00415449





carbohydrate metabolic process
0.00958846





response to hormone
0.01872034





response to organonitrogen compound
0.0236127




M1
positive regulation of endocytosis
0.00068494
12
24



positive regulation of receptor internalization
0.00098167





regulation of endocytosis
0.00098167





regulation of receptor internalization
0.00168554





positive regulation of receptor-mediated
0.00168554





endocytosis






regulation of vesicle-mediated transport
0.00168554





endocytosis
0.00219667





import into cell
0.00228672





receptor internalization
0.00228672





regulation of receptor-mediated endocytosis
0.00228672




M2
sulfur amino acid metabolic process
0.00084666
7
4



alpha-amino acid metabolic process
0.00228672





cellular amino acid metabolic process
0.00389259





sulfur compound metabolic process
0.0039442




M3
carbohydrate phosphorylation
0.00168554
16
21



intrinsic apoptotic signaling pathway by p53 class
0.00228672





mediator






ammonium ion metabolic process
0.00549372





monosaccharide metabolic process
0.00664531





signal transduction by p53 class mediator
0.00679184





cellular carbohydrate metabolic process
0.00731867





regulation of proteasomal protein catabolic process
0.00796902





positive regulation of binding
0.00924769





regulation of proteolysis involved in cellular protein
0.01072861





catabolic process






regulation of cellular protein catabolic process
0.0133162




M1
gliogenesis
0.00241591
7
2



neurogenesis
0.01454255




M2
cellular response to transforming growth factor beta
0.01057722
11
17



stimulus






response to transforming growth factor beta
0.01057722





cell-cell junction organization
0.01057722





cell junction organization
0.01057722





cellular divalent inorganic cation homeostasis
0.01454255





divalent inorganic cation homeostasis
0.01454255





cellular metal ion homeostasis
0.01650704





cellular ion homeostasis
0.01650766





cellular cation homeostasis
0.01650766





metal ion homeostasis
0.01650766




M3
nervous system process
0.01966787
6
1
















TABLE 23







List of Enriched GO terms.















GO. ID
Term
Annotated
Significant
Expected
classicFisher
module


















1
GO:0048812
neuron projection morphogenesis
157
7
0.67
2.80E−06
ME_1


2
GO:0120039
plasma membrane bounded cell projection . . .
161
7
0.68
3.30E−06
ME_1


3
GO:0048858
cell projection morphogenesis
162
7
0.69
3.40E−06
ME_1


4
GO:0032990
cell part morphogenesis
166
7
0.7
4.00E−06
ME_1


5
GO:0000902
cell morphogenesis
264
8
1.12
8.50E−06
ME_1


6
GO:0032989
cellular component morphogenesis
203
7
0.86
1.50E−05
ME_1


7
GO:0048667
cell morphogenesis involved in neuron di . . .
145
6
0.62
2.50E−05
ME_1


8
GO:0031175
neuron projection development
231
7
0.98
3.50E−05
ME_1


9
GO:0022008
neurogenesis
429
9
1.82
4.00E−05
ME_1


10
GO:0051649
establishment of localization in cell
553
10
2.35
4.60E−05
ME_1


11
GO:0007399
nervous system development
571
10
2.42
6.10E−05
ME_1


12
GO:0051049
regulation of transport
453
9
1.92
6.10E−05
ME_1


13
GO:1902903
regulation of supramolecular fiber organ . . .
105
5
0.45
6.60E−05
ME_1


14
GO:0120036
plasma membrane bounded cell projection . . .
351
8
1.49
6.70E−05
ME_1


15
GO:0030182
neuron differentiation
353
8
1.5
7.00E−05
ME_1


16
GO:0030030
cell projection organization
357
8
1.51
7.60E−05
ME_1


17
GO:0051179
localization
1714
17
7.27
7.60E−05
ME_1


18
GO:0048666
neuron development
266
7
1.13
8.70E−05
ME_1


19
GO:0007409
axonogenesis
115
5
0.49
0.0001
ME_1


20
GO:0000904
cell morphogenesis involved in different . . .
187
6
0.79
0.0001
ME_1


21
GO:0048699
generation of neurons
399
8
1.69
0.00017
ME_1


22
GO:1904062
regulation of cation transmembrane trans . . .
68
4
0.29
0.00017
ME_1


23
GO:0061564
axon development
129
5
0.55
0.00018
ME_1


24
GO:0051128
regulation of cellular component organiz . . .
647
10
2.74
0.00018
ME_1


25
GO:0032879
regulation of localization
704
10
2.99
0.00036
ME_1


26
GO:0046777
protein autophosphorylation
56
4
0.14
7.90E−06
ME_2


27
GO:2001222
regulation of neuron migration
11
2
0.03
0.0003
ME_2


28
GO:0048667
cell morphogenesis involved in neuron di . . .
145
4
0.35
0.00033
ME_2


29
GO:0048812
neuron projection morphogenesis
157
4
0.38
0.00045
ME_2


30
GO:0120039
plasma membrane bounded cell projection . . .
161
4
0.39
0.0005
ME_2


31
GO:0048858
cell projection morphogenesis
162
4
0.4
0.00051
ME_2


32
GO:0032990
cell part morphogenesis
166
4
0.41
0.00056
ME_2


33
GO:0000904
cell morphogenesis involved in different . . .
187
4
0.46
0.00088
ME_2


34
GO:0032989
cellular component morphogenesis
203
4
0.5
0.0012
ME_2


35
GO:0030001
metal ion transport
213
4
0.52
0.00143
ME_2


36
GO:0010959
regulation of metal ion transport
95
3
0.23
0.00143
ME_2


37
GO:0031175
neuron projection development
231
4
0.57
0.00193
ME_2


38
GO:0051928
positive regulation of calcium ion trans . . .
28
2
0.07
0.00204
ME_2


39
GO:0048813
dendrite morphogenesis
29
2
0.07
0.00218
ME_2


40
GO:0006811
ion transport
426
5
1.04
0.00265
ME_2


41
GO:0006796
phosphate-containing compound metabolic . . .
884
7
2.16
0.00283
ME_2


42
GO:0006793
phosphorus metabolic process
898
7
2.2
0.0031
ME_2


43
GO:0000902
cell morphogenesis
264
4
0.65
0.00315
ME_2


44
GO:0048666
neuron development
266
4
0.65
0.00324
ME_2


45
GO:0006812
cation transport
288
4
0.7
0.00432
ME_2


46
GO:0032879
regulation of localization
704
6
1.72
0.00451
ME_2


47
GO:0001764
neuron migration
43
2
0.11
0.00476
ME_2


48
GO:0016358
dendrite development
49
2
0.12
0.00615
ME_2


49
GO:0043269
regulation of ion transport
164
3
0.4
0.00675
ME_2


50
GO:0043270
positive regulation of ion transport
53
2
0.13
0.00717
ME_2


51
GO:0010738
regulation of protein kinase A signaling
10
1
0.01
0.0098
ME_3


52
GO:0033238
regulation of cellular amine metabolic p . . .
10
1
0.01
0.0098
ME_3


53
GO:0043486
histone exchange
10
1
0.01
0.0098
ME_3


54
GO:1902410
mitotic cytokinetic process
10
1
0.01
0.0098
ME_3


55
GO:0010640
regulation of platelet-derived growth fa . . .
11
1
0.01
0.0107
ME_3


56
GO:0030520
intracellular estrogen receptor signalin . . .
11
1
0.01
0.0107
ME_3


57
GO:0042133
neurotransmitter metabolic process
11
1
0.01
0.0107
ME_3


58
GO:0060065
uterus development
12
1
0.01
0.0117
ME_3


59
GO:0006884
cell volume homeostasis
13
1
0.01
0.0127
ME_3


60
GO:0032506
cytokinetic process
13
1
0.01
0.0127
ME_3


61
GO:0046850
regulation of bone remodeling
13
1
0.01
0.0127
ME_3


62
GO:0061756
leukocyte adhesion to vascular endotheli . . .
13
1
0.01
0.0127
ME_3


63
GO:0010737
protein kinase A signaling
14
1
0.01
0.0136
ME_3


64
GO:0070936
protein K48-linked ubiquitination
15
1
0.01
0.0146
ME_3


65
GO:0006635
fatty acid beta-oxidation
16
1
0.02
0.0156
ME_3


66
GO:0022602
ovulation cycle process
16
1
0.02
0.0156
ME_3


67
GO:0034103
regulation of tissue remodeling
16
1
0.02
0.0156
ME_3


68
GO:0045123
cellular extravasation
16
1
0.02
0.0156
ME_3


69
GO:0033143
regulation of intracellular steroid horm . . .
17
1
0.02
0.0165
ME_3


70
GO:0043044
ATP-dependent chromatin remodeling
17
1
0.02
0.0165
ME_3


71
GO:0045453
bone resorption
17
1
0.02
0.0165
ME_3


72
GO:0030104
water homeostasis
19
1
0.02
0.0185
ME_3


73
GO:0001541
ovarian follicle development
21
1
0.02
0.0204
ME_3


74
GO:0048008
platelet-derived growth factor receptor . . .
21
1
0.02
0.0204
ME_3


75
GO:0007193
adenylate cyclase-inhibiting G protein-c . . .
22
1
0.02
0.0214
ME_3


76
GO:0098742
cell-cell adhesion via plasma-membrane a . . .
48
2
0.06
0.0016
ME_4


77
GO:0007275
multicellular organism development
1360
6
1.78
0.0022
ME_4


78
GO:0007399
nervous system development
571
4
0.75
0.0038
ME_4


79
GO:0048856
anatomical structure development
1548
6
2.02
0.0044
ME_4


80
GO:0032502
developmental process
1677
6
2.19
0.0069
ME_4


81
GO:0030182
neuron differentiation
353
3
0.46
0.0085
ME_4


82
GO:0034329
cell junction assembly
113
2
0.15
0.0088
ME_4


83
GO:0048731
system development
1217
5
1.59
0.01
ME_4


84
GO:0048699
generation of neurons
399
3
0.52
0.012
ME_4


85
GO:0007157
heterophilic cell-cell adhesion via plas . . .
10
1
0.01
0.013
ME_4


86
GO:0032501
multicellular organismal process
1926
6
2.51
0.0144
ME_4


87
GO:0022008
neurogenesis
429
3
0.56
0.0146
ME_4


88
GO:0044331
cell-cell adhesion mediated by cadherin
12
1
0.02
0.0156
ME_4


89
GO:0071300
cellular response to retinoic acid
12
1
0.02
0.0156
ME_4


90
GO:0060612
adipose tissue development
13
1
0.02
0.0169
ME_4


91
GO:1903580
positive regulation of ATP metabolic pro . . .
13
1
0.02
0.0169
ME_4


92
GO:0034330
cell junction organization
163
2
0.21
0.0177
ME_4


93
GO:0034332
adherens junction organization
14
1
0.02
0.0181
ME_4


94
GO:0097009
energy homeostasis
14
1
0.02
0.0181
ME_4


95
GO:0099054
presynapse assembly
16
1
0.02
0.0207
ME_4


96
GO:0099172
presynapse organization
18
1
0.02
0.0233
ME_4


97
GO:0050873
brown fat cell differentiation
19
1
0.02
0.0245
ME_4


98
GO:0006140
regulation of nucleotide metabolic proce . . .
20
1
0.03
0.0258
ME_4


99
GO:1900542
regulation of purine nucleotide metaboli . . .
20
1
0.03
0.0258
ME_4


100
GO:0098609
cell-cell adhesion
203
2
0.26
0.0268
ME_4









Example 7

Here, the OrganEx technology and its potential to support recovery of key molecular and cellular processes in multiple porcine organs after prolonged global warm ischemia are described. This also demonstrates the underappreciated capacity of the large mammalian body for restoration of hemodynamic and metabolic parameters following circulatory arrest or other severe ischemic stress. This application of the OrganEx technology demonstrates that cellular demise can be halted, and their state be shifted towards recovery at molecular and cellular levels, even following prolonged warm ischemia. Additionally, a comprehensive single-cell transcriptomic analysis of multiple porcine organs was generated to provide a unique resource for future studies on cell-types, ischemia, and reperfusion.


Although some cellular viability can be restored following prolonged ischemia in tissue cultures or isolated organs, clinical scenarios typically involve shorter-duration ischemia in the setting of cardiac arrest or regional perfusions in the setting of organ transplant. By employing a rational polytherapy approach built upon optimized perfusion dynamics and augmentations to an acellular synthetic perfusate, the OrganEx technology was able to bridge prior clinical-translational gaps by restoring circulation and metabolic homeostasis across the whole body. This quells deleterious processes caused by disturbed cellular environments and lack of oxygen, representing a distinct feature of this technology and an essential control for multiple nonspecific injury mechanisms affecting end-organ recovery and overall prognosis after global ischemia. Potential applications of this technology are manifold and could provide novel pathways in ischemia research and advance related clinical disciplines. OrganEx has the potential to extend limits of allowable warm ischemia times through regional abdominal/thoracic reperfusion, thereby increasing organ availability for transplantation. This approach would require obligatory antecedent clamping of the aorta/carotid arteries to prevent brain recirculation in the organ donor. Conversely, if any future refinements of the technology could be aimed at the recovery of the brain function after injury, then the brain circulation would remain patent. In this regard, OrganEx technology may improve outcomes in extracorporeal cardiopulmonary resuscitation with the needed circulatory support, or the OrganEx perfusate could aid in recovery wherein cardiac function is preserved but the brain is damaged, as seen in stroke. Thus, a clear distinction should be made before possible utilization of OrganEx technology, relative to inclusion of the brain circulation.


While these studies demonstrate important cellular protection and repair processes in vital organs across meaningful timepoints, questions remain concerning organ recovery over an extended timeframe. Since repeating all experiments over additional, extended durations to comprise a full, longitudinal study were not feasible under current regulatory constraints, long-term organotypic slice culture preparations of hippocampus were employed to study post-perfusion cell survivability in the most ischemia-sensitive tissue possible. This demonstrated that OrganEx intervention provides enduring effects on cellular recovery following transfer to the extended survival conditions.


Enumerated Embodiments

The following enumerated embodiments are provided, the numbering of which is not to be construed as designating levels of importance.


Embodiment 1 provides an isolated perfusate mixture comprising:


an inorganic salt solution;


an artificial oxygen carrier; and


autologous blood.


Embodiment 2 provides the isolated perfusate mixture of embodiment 1, wherein the one or more artificial oxygen carriers is selected from the group consisting of hemoglobin glutamer-250, isolated cell-free hemoglobin, cross-linked hemoglobin, polymerized hemoglobin, encapsulated hemoglobin, and perfluorocarbon oxygen carriers.


Embodiment 3 provides the isolated perfusate mixture of embodiments 1-2, wherein the artificial oxygen carrier is hemoglobin glutamer-250.


Embodiment 4 provides the isolated perfusate mixture of embodiments 1-3, wherein the one or more inorganic salts are selected from the group consisting of sodium chloride, sodium bicarbonate, magnesium chloride, and calcium chloride.


Embodiment 5 provides the isolated perfusate mixture of embodiments 1-4, wherein the perfusate comprises a priming solution containing one or more sugars.


Embodiment 6 provides the isolated perfusate mixture of embodiments 1-5 wherein the one or more sugars are glucose or dextrane.


Embodiment 7 provides the isolated perfusate mixture of embodiments 1-6, further comprising one or more amino acids.


Embodiment 8 provides the isolated perfusate mixture of embodiments 1-7, wherein the one or more amino acids are selected from the group consisting of glycine, L-alanyl-glutamine, L-arginine, L-cysteine, L-histidine, L-isoleucine, L-leucine, L-lysine, L-methionine, L-phenylalanine, L-serine, L-threonine, L-tryptophan, L-tyrosine, L-valine and salts and solvates thereof.


Embodiment 9 provides the isolated perfusate mixture of embodiments 1-8, wherein the mixture further comprises one or more vitamins.


Embodiment 10 provides the isolated perfusate mixture of embodiments 1-9, wherein the one or more vitamins are selected from the group consisting of choline, D-calcium pantothenate, folic acid, niacinamide, pyridoxine, riboflavin, thiamine, i-inositol and salts and solvates thereof.


Embodiment 11 provides the isolated perfusate mixture of embodiments 1-10, wherein the mixture further comprises, ferric nitrate, magnesium sulfate, potassium chloride, sodium phosphate, and derivatives thereof.


Embodiment 12 provides the isolated perfusate mixture of embodiments 1-11, wherein the mixture further comprises an anti-clotting agent.


Embodiment 13 provides the isolated perfusate mixture of embodiments 1-12, wherein the anti-clotting agent is heparin.


Embodiment 14 provides the isolated perfusate mixture of embodiments 1-13, wherein the percentage of autologous blood in the mixture is between 10% and 50%.


Embodiment 15 provides the isolated perfusate mixture of embodiments 1-14, wherein the percentage of autologous blood in the mixture is approximately 28%.


Embodiment 16 provides the isolated perfusate mixture of embodiments 1-15, wherein the mixture is dialyzed against a solution comprising inorganic salts.


Embodiment 17 provides the isolated perfusate mixture of embodiments 1-16, wherein the mixture is dialyzed against plasma.


Embodiment 18 provides the isolated perfusate mixture of embodiments 1-17, wherein the mixture comprises electrolytes and oncotic agents at levels comparable to those in autologous blood.


Embodiment 19 provides the isolated perfusate mixture of embodiments 1-18, wherein the perfusate further comprises cytoprotective agents.


Embodiment 20 provides the isolated perfusate mixture of embodiments 1-19, wherein the cytoprotective agents are selected from the group consisting of 2-Iminobiotin, Necrostatin-1, sodium 3-hydroxybutryate, glutathione, minocycline, lamotrigine, QVE-Oph, methylene blue, and or any salts, solvates, tautomers, and prodrugs thereof.


Embodiment 21 provides the isolated perfusate mixture of embodiments 1-20, wherein the mixture further comprises antibiotics.


Embodiment 22 provides the isolated perfusate mixture of embodiments 1-21, wherein the antibiotic is ceftriazone.


Embodiment 23 provides the isolated perfusate mixture of embodiments 1-22, wherein the mixture comprises one or more anti-inflammatory agents.


Embodiment 24 provides the isolated perfusate mixture of embodiments 1-23, wherein the one or more the anti-inflammatory agents is dexamathazone or cetirizine.


Embodiment 25 provides the isolated perfusate mixture of embodiments 1-24, wherein the temperature of the mixture is approximately 28° C.


Embodiment 26 provides a system for the hypothermic preservation of organs in a mammal, the system comprising:


a perfusion device for the perfusion of an isolated perfusate mixture into the mammal, the perfusion device comprising:


a perfusion loop; and


a controller programmed to regulate at least a perfusate temperature within the perfusion loop to maintain hypothermic conditions; and the isolated perfusate mixture of any of embodiments 1-25.


Embodiment 27 provides the system of embodiment 26, wherein the perfusion loop further comprises at least one pulse generator programmed to generate a pressure pulse within the perfusate within the perfusion loop.


Embodiment 28 provides the system of embodiments 26-27, wherein the perfusion loop comprises a venous loop, a filtration loop and an arterial loop, wherein:


the venous loop comprises at least one perfusion pump;


the filtration loop comprises at least one perfusion pump, and at least one hemodiafiltration unit adapted and configured to equilibrate the perfusate;


the arterial loop comprises at least one gas exchange source and at least one gas mixer adapted and configured to supply oxygen and carbon dioxide to the perfusate;


wherein the mammal, the venous loop, the filtration loop and the arterial loop are in fluidic communication such that the perfusate can be carried from the mammal, through the venous loop, through the filtration loop, through the arterial loop and back to the mammal.


Embodiment 29 provides the system of embodiments 26-28, wherein one or more components selected from the group consisting of the venous loop, the filtration loop and the arterial loop further comprise a reservoir containing excess perfusate.


Embodiment 30 provides the system of embodiments 26-29, wherein one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop further comprise one or more elements selected from the group consisting of:

    • one or more valves adapted and configured to regulate the flow of the perfusate;
    • one or more filters adapted and configured to filter the perfusate; and
    • one or more sensors for measuring one or more properties of the perfusate selected from the group consisting of pH, dissolved oxygen concentration, dissolved carbon dioxide concentration, dissolved metabolite concentration, temperature, pressure, and flow rate.


Embodiment 31 provides the system of embodiments 26-30, wherein the one or more sensors measure the concentration of at least one dissolved metabolite selected from the group consisting of nitric oxide, lactate, bicarbonate, oxygen, carbon dioxide, total hemoglobin, methemoglobin, oxyhemoglobin, carboxyhemoglobin, sodium, potassium, chloride, calcium, glucose, urea, ammonia, and creatinine.


Embodiment 32 provides the system of embodiments 26-31, wherein the mammal perfusion apparatus comprises one or more sensors for measuring one or more properties of the perfusate selected from the group consisting of pressure and flow rate.


Embodiment 33 provides the system of embodiments 26-32, wherein one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop comprise one or more heat exchange units comprising:


one or more heat exchangers;


one or more temperature regulation units;


one or more temperature regulating pumps;


a thermoregulation fluid; and


one or more pipes configured and adapted to transport the thermoregulation fluid, wherein the one or more pipes are in fluidic communication with the one or more heat exchangers, the one or more temperature regulation units and the one or more temperature regulating pumps.


Embodiment 34 provides the system of embodiments 26-33, wherein the one or more components selected from the group consisting of the brain enclosure unit, the venous loop, the filtration loop and the arterial loop comprise one or more sensors adapted and configured to measure the temperature within the perfusion device.


Embodiment 35 provides the system of embodiments 26-34, wherein the one or more sensor(s) is/are adapted and configured to measure the temperature within the perfusion device, the one or more temperature regulation units and the one or more temperature regulating pumps are in electronic communication with a computer programmed to regulate the temperature of the thermoregulation fluid and the specified flow rate of the one or more temperature regulating pumps to maintain a specified temperature within the perfusion device.


Embodiment 36 provides the system of embodiments 26-35, wherein the hemodiafiltration unit is adapted and configured to supply one or more nutrients to the perfusate, selected from the group consisting of Glycine, L-Alanyl-Glutamine, L-Arginine hydrochloride, L-Cystine, L-Histidine hydrochloride-H2O, L-Isoleucine, L-Leucine, L-Lysine hydrochloride, L-Methionine, L-Phenylalanine, L-Serine, L-Threonine, L-Tryptophan, L-Tyrosine, L-Valine, Choline chloride, D-Calcium pantothenate, Folic Acid, Niacinamide, Pyridoxine hydrochloride, Riboflavin, Thiamine hydrochloride, i-Inositol, Calcium Chloride (CaCl2)-2H2O), Ferric Nitrate (Fe(N03)3 9H2O), Magnesium Sulfate (MgSO4-7H2O), Potassium Chloride (KCl), Sodium Bicarbonate (NaHCO3), Sodium Chloride (NaCl), Sodium Phosphate monobasic (NaH2PO4-2H2O), D-Glucose (Dextrose), Phenol Red, Sodium Pyruvate, free fatty acids, cholesterol and nucleic acid constitutes.


Embodiment 37 provides the system of embodiments 26-36, wherein the system is configured to perfuse the mammal with the perfusate at a cardiac pulsatile pressure of about 20 mmHg to about 140 mmHg.


Embodiment 38 provides the system of embodiments 26-37, wherein the system is configured to perfuse the organs in the mammal with the perfusate through the pulse generator at a rate of about 40 to about 180 beats per minute.


Embodiment 39 provides the system of embodiments 26-38, further comprising a controller in electronic communication with one or more elements of the system.


Embodiment 40 provides a mammal perfused with the isolated perfusate composition of any of embodiments 1-25, wherein mammalian organs are perfused under hypothermic conditions.


Embodiment 41 provides the mammal of embodiment 40, wherein the mammal is a deceased mammal.


Embodiment 42 provides the mammal of embodiments 40-41, wherein the mammal is a human.


Embodiment 43 provides the mammal of embodiments 40-42, wherein the deceased mammal is deceased for longer than 1 hour.


Embodiment 44 provides the mammal of embodiments 40-45, wherein the deceased mammal has been deceased for longer than 4 hours.


Embodiment 45 provides the mammal of embodiments 40-45, wherein the mammal died of cardiac arrest.


Embodiment 46 provides the mammal of embodiments 40-45, wherein the organs in the deceased mammal are ischemic prior to perfusion with the isolated perfusate mixture of any of claims 1-25.


Embodiment 47 provides the mammal of embodiments 40-46, wherein rigor mortis is prevented.


Embodiment 48 provides the mammal of embodiments 40-47, wherein rigor mortis is reversed.


Embodiment 49 provides the mammal of embodiments 40-48, wherein the perfusate mixture flows into the ophthalmic artery.


Embodiment 50 provides the mammal of embodiments 40-49, wherein the perfusate mixture flows into the renal intralobular arteries.


Embodiment 51 provides perfused organs in a diseased mammal, wherein the perfused organs maintain one or more properties selected from the group consisting of an in vivo level of cell function and viability, and an in vivo level of morphology.


OTHER EMBODIMENTS

The recitation of a listing of elements in any definition of a variable herein includes definitions of that variable as any single element or combination (or subcombination) of listed elements. The recitation of an embodiment herein includes that embodiment as any single embodiment or in combination with any other embodiments or portions thereof.


The disclosures of each and every patent, patent application, and publication cited herein are hereby incorporated herein by reference in their entirety. While this invention has been disclosed with reference to specific embodiments, it is apparent that other embodiments and variations of this invention may be devised by others skilled in the art without departing from the true spirit and scope of the invention. The appended claims are intended to be construed to include all such embodiments and equivalent variations.

Claims
  • 1. An isolated perfusate mixture comprising: an inorganic salt solution;an artificial oxygen carrier; andautologous blood.
  • 2. The isolated perfusate mixture of claim 1, wherein the one or more artificial oxygen carrier(s) is/are selected from the group consisting of hemoglobin glutamer-250, isolated cell-free hemoglobin, cross-linked hemoglobin, polymerized hemoglobin, encapsulated hemoglobin, and perfluorocarbon oxygen carriers.
  • 3. The isolated perfusate mixture of claim 2, wherein the artificial oxygen carrier is hemoglobin glutamer-250.
  • 4. The isolated perfusate mixture of claim 1, wherein the one or more inorganic salts are selected from the group consisting of sodium chloride, sodium bicarbonate, magnesium chloride, and calcium chloride.
  • 5. The isolated perfusate mixture of claim 1, wherein the perfusate comprises a priming solution containing one or more sugars.
  • 6. The isolated perfusate mixture of claim 5, wherein the one or more sugars are glucose or dextrane.
  • 7. The isolated perfusate mixture of claim 1, further comprising one or more amino acids.
  • 8. The isolated perfusate mixture of claim 7, wherein the one or more amino acids are selected from the group consisting of glycine, L-alanyl-glutamine, L-arginine, L-cysteine, L-histidine, L-isoleucine, L-leucine, L-lysine, L-methionine, L-phenylalanine, L-serine, L-threonine, L-tryptophan, L-tyrosine, L-valine and salts and solvates thereof.
  • 9. The isolated perfusate mixture of claim 1, further comprising one or more vitamins.
  • 10. The isolated perfusate mixture of claim 9, wherein the one or more vitamin(s) is/are selected from the group consisting of choline, D-calcium pantothenate, folic acid, niacinamide, pyridoxine, riboflavin, thiamine, i-inositol and salts and solvates thereof.
  • 11. The isolated perfusate mixture of claim 1, further comprising, ferric nitrate, magnesium sulfate, potassium chloride, sodium phosphate, and derivatives thereof.
  • 12. The isolated perfusate mixture of claim 1, further comprising an anti-clotting agent.
  • 13. The isolated perfusate mixture of claim 12, wherein the anti-clotting agent is heparin.
  • 14. The isolated perfusate mixture of claim 1 wherein the percentage of autologous blood in the mixture is between about 10% and about 50%.
  • 15. The isolated perfusate mixture of claim 14, wherein the percentage of autologous blood in the mixture is approximately 28%.
  • 16. The isolated perfusate mixture of any of claims 1-15, wherein the mixture is dialyzed against a solution comprising inorganic salts.
  • 17. The isolated perfusate mixture of any of claims 1-15, wherein the mixture is dialyzed against plasma.
  • 18. The isolated perfusate mixture of any of claims 1-15, wherein the mixture comprises electrolytes and oncotic agents at levels comparable to those in autologous blood.
  • 19. The isolated perfusate mixture of claim 1, wherein the perfusate further comprises cytoprotective agents.
  • 20. The isolated perfusate mixture of claim 19, wherein the cytoprotective agents are selected from the group consisting of 2-Iminobiotin, Necrostatin-1, sodium 3-hydroxybutryate, glutathione, minocycline, lamotrigine, QVE-Oph, methylene blue, and or any salts, solvates, tautomers, and prodrugs thereof.
  • 21. The isolated perfusate mixture of claim 1, wherein the mixture further comprises antibiotics.
  • 22. The isolated perfusate mixture of claim 21, wherein the antibiotic is ceftriazone.
  • 23. The isolated perfusate mixture of claim 1, wherein the mixture comprises one or more anti-inflammatory agent(s).
  • 24. The isolated perfusate mixture of claim 1, wherein the one or more the anti-inflammatory agent(s) is dexamathazone or cetirizine.
  • 25. The perfusate mixture of any of claims 1-24, wherein the temperature of the mixture is approximately 28° C.
  • 26. A system for the hypothermic preservation of organs in a mammal, the system comprising: a perfusion device for the perfusion of an isolated perfusate mixture into the mammal, the perfusion device comprising:a perfusion loop; anda controller programmed to regulate at least a perfusate temperature within the perfusion loop to maintain hypothermic conditions; and the isolated perfusate mixture of any of claims 1-25.
  • 27. The system of claim 26, wherein the perfusion loop further comprises at least one pulse generator programmed to generate a pressure pulse within the perfusate within the perfusion loop.
  • 28. The system of claim 26, wherein the perfusion loop comprises a venous loop, a filtration loop and an arterial loop, wherein: the venous loop comprises at least one perfusion pump;the filtration loop comprises at least one perfusion pump, and at least one hemodiafiltration unit adapted and configured to equilibrate the perfusate;the arterial loop comprises at least one gas exchange source and at least one gas mixer adapted and configured to supply oxygen and carbon dioxide to the perfusate;wherein the mammal, the venous loop, the filtration loop and the arterial loop are in fluidic communication such that the perfusate can be carried from the mammal, through the venous loop, through the filtration loop, through the arterial loop and back to the mammal.
  • 29. The system of claim 28, wherein one or more components selected from the group consisting of the venous loop, the filtration loop and the arterial loop further comprise a reservoir containing excess perfusate.
  • 30. The system of claim 28, wherein one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop further comprise one or more elements selected from the group consisting of: one or more valves adapted and configured to regulate the flow of the perfusate;one or more filters adapted and configured to filter the perfusate; andone or more sensors for measuring one or more properties of the perfusate selected from the group consisting of pH, dissolved oxygen concentration, dissolved carbon dioxide concentration, dissolved metabolite concentration, temperature, pressure, and flow rate.
  • 31. The system of claim 28, wherein the one or more sensors measure the concentration of at least one dissolved metabolite selected from the group consisting of nitric oxide, lactate, bicarbonate, oxygen, carbon dioxide, total hemoglobin, methemoglobin, oxyhemoglobin, carboxyhemoglobin, sodium, potassium, chloride, calcium, glucose, urea, ammonia, and creatinine.
  • 32. The system of claim 28, wherein the mammal perfusion apparatus comprises one or more sensors for measuring one or more properties of the perfusate selected from the group consisting of pressure and flow rate.
  • 33. The system of claim 28, wherein one or more components selected from the group consisting of the mammal, the venous loop, the filtration loop and the arterial loop comprise one or more heat exchange units comprising: one or more heat exchangers;one or more temperature regulation units;one or more temperature regulating pumps;a thermoregulation fluid; andone or more pipes configured and adapted to transport the thermoregulation fluid, wherein the one or more pipes are in fluidic communication with the one or more heat exchangers, the one or more temperature regulation units and the one or more temperature regulating pumps.
  • 34. The system of claim 28, wherein the one or more components selected from the group consisting of the brain enclosure unit, the venous loop, the filtration loop and the arterial loop comprise one or more sensors adapted and configured to measure the temperature within the perfusion device.
  • 35. The system of claim 28, wherein the one or more sensor(s) is/are adapted and configured to measure the temperature within the perfusion device, the one or more temperature regulation units and the one or more temperature regulating pumps are in electronic communication with a computer programmed to regulate the temperature of the thermoregulation fluid and the specified flow rate of the one or more temperature regulating pumps to maintain a specified temperature within the perfusion device.
  • 36. The system of claim 28, wherein the hemodiafiltration unit is adapted and configured to supply one or more nutrients to the perfusate, selected from the group consisting of Glycine, L-Alanyl-Glutamine, L-Arginine hydrochloride, L-Cystine, L-Histidine hydrochloride-H2O, L-Isoleucine, L-Leucine, L-Lysine hydrochloride, L-Methionine, L-Phenylalanine, L-Serine, L-Threonine, L-Tryptophan, L-Tyrosine, L-Valine, Choline chloride, D-Calcium pantothenate, Folic Acid, Niacinamide, Pyridoxine hydrochloride, Riboflavin, Thiamine hydrochloride, i-Inositol, Calcium Chloride (CaCl2)-2H2O), Ferric Nitrate (Fe(NO3)3 9H2O), Magnesium Sulfate (MgSO4-7H2O), Potassium Chloride (KCl), Sodium Bicarbonate (NaHCO3), Sodium Chloride (NaCl), Sodium Phosphate monobasic (NaH2PO4-2H2O), D-Glucose (Dextrose), Phenol Red, Sodium Pyruvate, free fatty acids, cholesterol and nucleic acid constitutes.
  • 37. The system of any of claims 26-36, wherein the system is configured to perfuse the mammal with the perfusate at a cardiac pulsatile pressure of about 20 mmHg to about 140 mmHg.
  • 38. The system of any of claims 26-36, wherein the system is configured to perfuse the organs in the mammal with the perfusate through the pulse generator at a rate of about 40 to about 180 beats per minute.
  • 39. The system of any of claim 26-36, further comprising a controller in electronic communication with one or more elements of the system.
  • 40. A mammal perfused with the isolated perfusate mixture of any of claims 1-25, wherein mammalian organs are perfused under hypothermic conditions.
  • 41. The mammal of claim 40, wherein the mammal is a deceased mammal.
  • 42. The mammal of claim 40, wherein the mammal is a human.
  • 43. The mammal of claim 41 wherein the deceased mammal is deceased for longer than 1 hour.
  • 44. The deceased mammal of claim 43, wherein the deceased mammal has been deceased for longer than 4 hours.
  • 45. The deceased animal of claim 41, wherein the mammal died of cardiac arrest.
  • 46. The deceased mammal of claim 41, wherein the organs in the deceased mammal are ischemic prior to perfusion with the isolated perfusate mixture of any of claims 1-25.
  • 47. The deceased mammal of claim 41, wherein rigor mortis is prevented.
  • 48. The deceased mammal of claim 41, wherein rigor mortis is reversed.
  • 49. The diseased mammal of claim 41, wherein the perfusate mixture flows into the ophthalmic artery.
  • 50. The diseased mammal of claim 41, wherein the perfusate mixture flows into the renal intralobular arteries.
  • 51. The perfused organs in a diseased mammal, wherein the perfused organs maintain one or more properties selected from the group consisting of an in vivo level of cell function and viability, and an in vivo level of morphology.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 63/245,632, filed Sep. 17, 2021, which application is incorporated herein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under MH117064 and MH117064-01S1, awarded by the National Institute of Mental Health. The government has certain rights in the invention.

PCT Information
Filing Document Filing Date Country Kind
PCT/US2022/043816 9/16/2022 WO
Provisional Applications (1)
Number Date Country
63245632 Sep 2021 US