Patent Grant
10128093
Information dependent analysis (IDA) is a flexible tandem mass spectrometry method in which a user can specify criteria for producing product ion spectra during a chromatographic run. For example, in an IDA method a precursor or mass spectrometry (MS) survey scan is performed to generate a precursor ion peak list. The user can select criteria to filter the peak list for a subset of the precursor ions on the peak list. The subset of precursor ions are then fragmented and product ion spectra are obtained repeatedly during the chromatographic run.
In a typical IDA method, a cycle consists of a single MS survey scan followed by N mass spectrometry/mass spectrometry (MS/MS) scans. After the MS survey scan, the precursor ion peak list is generated and filtered in real-time. For example, the peak list is generated by ranking the mass-to charge ratio (m/z) peaks of the MS survey scan spectrum from highest intensity to lowest intensity. The precursor ion peak list is then filtered.
Precursor ion peak list filtering can include, for example, a number of filtering steps. First, any precursor ions that were fragmented in an earlier cycle are excluded from the precursor ion peak list. Second, precursor ions on the peak list that are simply multiple charge states of the same precursor ion are collapsed into a single precursor ion with a single charge state. Third, precursor ions on the peak list that are within a certain m/z threshold or tolerance of a precursor ion that was previously fragmented are also excluded from the precursor ion list.
The N m/z peaks from the filtered precursor ion list with the highest intensity values are then selected for MS/MS analysis. As a result, each cycle consists of N MS/MS scans. A cycle is performed, for example, for each retention time of a chromatographic separation.
IDA is a useful technique for identifying proteins or peptides from peptide fragments. Typically, IDA is performed on a protein or peptide mixture, producing a plurality of product ion spectra for the peptide fragments that are produced. Each spectrum of the plurality of product ion spectra are then compared to a protein or peptide database in order to identify the proteins or peptides in the mixture.
Unfortunately, however, the protein or peptide identification can be adversely affected by mixed or convolved product ion spectra. In other words, some of the product ion spectra from the IDA method can include product ions from more than one precursor ion. As a result, when a mixed or convolved product ion spectrum is compared to a protein or peptide database, a match may not be found.
A number of methods have been proposed to deconvolve product ions produced from convolved precursor ions. In U.S. Provisional Patent Application Ser. No. 62/061,492, entitled “Improving IDA Spectral Output for Database Searches,” a post-processing method for deconvolving product ions is described that compares the intensity pattern of product ions over two or more IDA cycles. Product ions that share the same pattern are then grouped together. By comparing the product ions in each group to a database of known product ions for precursor ions, the parent precursor ions that produced each group are determined. In this way both the product ions and the precursor ions are deconvolved.
This method of deconvolution relies on data collected over two or more cycles. In fact, the method works best when three or more data points are collected across a chromatographic peak.
Unfortunately, however and as described above, in most IDA methods when a precursor ion is fragmented in a cycle, it is excluded from being fragmented in any subsequent cycles. As a result, there is not enough data to perform deconvolution using methods such as the one described above.
Currently, the mass spectrometry industry lacks a real-time method of ensuring that enough data is collected in an IDA method in order to apply a deconvolution method when precursor ions are potentially convolved. More simply, the mass spectrometry industry lacks a method of preventing previously fragmented precursor ions from being excluded in an IDA method, when those precursor ions may be convolved.
A system is disclosed for preventing potentially convolved precursor ion peaks from being excluded in subsequent cycles of an information dependent analysis (IDA) experiment so that additional product ion data is collected. The system includes an ion source, a mass spectrometer, and a processor.
The ion source ionizes a sample received over time producing an ion beam. The mass spectrometer receives the ion beam from the ion source and is adapted to perform a plurality of cycles of an IDA experiment on the ion beam. Each cycle of the plurality of cycles includes a number of steps. In a mass spectrometry (MS) survey scan step, a precursor ion mass spectrum is produced. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In a mass spectrometry/mass spectrometry step (MS/MS) step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
During each cycle of the plurality of cycles, the processor performs a number of steps for each precursor ion peak on a filtered peak list produced in a filtering step. The processor identifies the precursor ion peak in a precursor ion spectrum produced in a MS survey scan step, and determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution. If the precursor ion peak includes a feature of convolution, the processor instructs the mass spectrometer to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles of the plurality of cycles.
A method is disclosed for preventing potentially convolved precursor ion peaks from being excluded in subsequent cycles of an information dependent analysis (IDA) experiment so that additional product ion data is collected.
A sample received over time is ionized and an ion beam is produced using an ion source. A plurality of cycles of an IDA experiment is performed on the ion beam using a mass spectrometer. Each cycle of the IDA experiment includes a number of steps. In an MS survey scan step, a precursor ion mass spectrum is produced. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In an MS/MS step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
During each cycle of the IDA experiment and for each precursor ion peak on a filtered peak list produced in the filtering step of each cycle, a number of steps are performed. The precursor ion peak is identified in the precursor ion spectrum produced in the MS survey scan step of the cycle using a processor. It is determined if the precursor ion peak in the precursor ion spectrum includes a feature of convolution using the processor. If the precursor ion peak includes a feature of convolution, the mass spectrometer is instructed to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles using the processor
A computer program product is disclosed that includes a non-transitory and tangible computer-readable storage medium whose contents include a program with instructions being executed on a processor so as to perform a method for preventing potentially convolved precursor ion peaks from being excluded in subsequent cycles of an IDA experiment so that additional product ion data is collected. In various embodiments, the method includes providing a system, wherein the system comprises one or more distinct software modules, and wherein the distinct software modules comprise a control module and an analysis module.
The control module instructs an ion source to ionize a sample received over time and to produce an ion beam. The control module instructs a mass spectrometer to perform a plurality of cycles of an IDA experiment on the ion beam. Each cycle of the IDA experiment includes a number of steps. In an MS survey scan step, a precursor MS survey scan is performed, producing a precursor ion mass spectrum. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, among other things, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In an MS/MS step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
During each cycle of the IDA experiment a number of steps are performed for each precursor ion peak on a filtered peak list produced in the filtering step of the cycle. The analysis module identifies the precursor ion peak in the precursor ion spectrum produced in the MS survey scan step. The analysis module determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution. If the precursor ion peak includes a feature of convolution, the control module instructs the mass spectrometer to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles of the plurality of cycles of the IDA experiment.
These and other features of the applicant's teachings are set forth herein.
The skilled artisan will understand that the drawings, described below, are for illustration purposes only. The drawings are not intended to limit the scope of the present teachings in any way.
Before one or more embodiments of the present teachings are described in detail, one skilled in the art will appreciate that the present teachings are not limited in their application to the details of construction, the arrangements of components, and the arrangement of steps set forth in the following detailed description or illustrated in the drawings. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting.
Computer system 100 may be coupled via bus 102 to a display 112, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a computer user. An input device 114, including alphanumeric and other keys, is coupled to bus 102 for communicating information and command selections to processor 104. Another type of user input device is cursor control 116, such as a mouse, a trackball or cursor direction keys for communicating direction information and command selections to processor 104 and for controlling cursor movement on display 112. This input device typically has two degrees of freedom in two axes, a first axis (i.e., x) and a second axis (i.e., y), that allows the device to specify positions in a plane.
A computer system 100 can perform the present teachings. Consistent with certain implementations of the present teachings, results are provided by computer system 100 in response to processor 104 executing one or more sequences of one or more instructions contained in memory 106. Such instructions may be read into memory 106 from another computer-readable medium, such as storage device 110. Execution of the sequences of instructions contained in memory 106 causes processor 104 to perform the process described herein. Alternatively hard-wired circuitry may be used in place of or in combination with software instructions to implement the present teachings. Thus implementations of the present teachings are not limited to any specific combination of hardware circuitry and software.
In various embodiments, computer system 100 can be connected to one or more other computer systems, like computer system 100, across a network to form a networked system. The network can include a private network or a public network such as the Internet. In the networked system, one or more computer systems can store and serve the data to other computer systems. The one or more computer systems that store and serve the data can be referred to as servers or the cloud, in a cloud computing scenario. The one or more computer systems can include one or more web servers, for example. The other computer systems that send and receive data to and from the servers or the cloud can be referred to as client or cloud devices, for example.
The term “computer-readable medium” as used herein refers to any media that participates in providing instructions to processor 104 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device 110. Volatile media includes dynamic memory, such as memory 106. Transmission media includes coaxial cables, copper wire, and fiber optics, including the wires that comprise bus 102.
Common forms of computer-readable media or computer program products include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, digital video disc (DVD), a Blu-ray Disc, any other optical medium, a thumb drive, a memory card, a RAM, PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, or any other tangible medium from which a computer can read.
Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to processor 104 for execution. For example, the instructions may initially be carried on the magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 100 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector coupled to bus 102 can receive the data carried in the infra-red signal and place the data on bus 102. Bus 102 carries the data to memory 106, from which processor 104 retrieves and executes the instructions. The instructions received by memory 106 may optionally be stored on storage device 110 either before or after execution by processor 104.
In accordance with various embodiments, instructions configured to be executed by a processor to perform a method are stored on a computer-readable medium. The computer-readable medium can be a device that stores digital information. For example, a computer-readable medium includes a compact disc read-only memory (CD-ROM) as is known in the art for storing software. The computer-readable medium is accessed by a processor suitable for executing instructions configured to be executed.
The following descriptions of various implementations of the present teachings have been presented for purposes of illustration and description. It is not exhaustive and does not limit the present teachings to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practicing of the present teachings. Additionally, the described implementation includes software but the present teachings may be implemented as a combination of hardware and software or in hardware alone. The present teachings may be implemented with both object-oriented and non-object-oriented programming systems.
As described above, the mass spectrometry industry lacks a real-time method of ensuring that enough data is collected in an information dependent analysis (IDA) method in order to apply a deconvolution method when precursor ions are potentially convolved. More simply, the mass spectrometry industry lacks a method of preventing previously fragmented precursor ions from being excluded in an IDA method, when those precursor ions may be convolved.
In various embodiments, in real-time a precursor ion on a filtered peak list in an IDA method is identified as including a feature of convolution from the precursor or mass spectrometry (MS) survey scan. The precursor ion is then added to a do not exclude list so that the precursor ion is fragmented over two or more cycles of the IDA method. In this way, it is ensured that enough mass spectrometry/mass spectrometry (MS/MS) data or product ion data is always collected to apply a deconvolution method to this data, which is something the mass spectrometry industry has been unable to obtain.
For example, any precursor ions that were fragmented in an earlier cycle are excluded from the precursor ion peak list. Also, precursor ions on the peak list that are within a certain m/z threshold or tolerance of a precursor ion that was previously fragmented are also excluded from the precursor ion list.
In addition, precursor ions on the peak list that are simply multiple charge states of the same precursor ion are collapsed into a single precursor ion with a single charge state. For example, peak 210 has an m/z of 1000, peak 220 has an m/z of 500, and peak 230 has an m/z of 250. Peaks 210, 220, and 230, therefore, are the +1, +2, and +4 charge states of a precursor ion of mass 1000, respectively. As a result, peaks 220 and 230 are filtered from the peak list.
On comparison with
Conventionally, each precursor ion represented by each peak of
In various embodiments, however, before excluding a fragmented precursor ion from the peak list in the next cycle, the precursor ion peak is examined for a feature of convolution. Features of convolution can include, but are not limited to, decreased peak resolving power, more than one precursor ion in the MS/MS isolation window, a peak shape that exhibits convolution, or the absence of a known isotopic form of the precursor ion in the MS survey scan.
Resolving power, R. is defined, for example, as a peak mass or m/z, m, divided by the peak width, Δm, necessary for separation at the peak mass, R=m/Δm. Resolving power is specific to each mass spectrometry instrument. For example, if the mass spectrometer used to provide the data for
In
Another way of looking at this data is to compare peak width 215 with peak width 415. For a mass spectrometer with a resolving power of 10,000, the peak width of an m/z at 1,000 should be 0.1, which is the value of peak width 415. Peak width 215 of precursor ion peak 210 is 0.2. Since the peak width of precursor ion peak 210 is greater than what the peak width should be for instrument with a resolving power of 10,000, precursor ion peak 210 may be convolved with another precursor ion peak, and precursor ion peak 210, therefore, includes a feature of convolution.
In addition to precursor ion peak 210, isolation window 510 includes precursor ion peak 520. More than one precursor ion in an isolation window results in the fragmentation of more than one precursor ion. If two or more of the fragmented precursor ions produce products ions that have the same or almost the same m/z values, those product ions can be convolved. As a result, the presence of precursor ion peak 520 in isolation window 510 indicates that convolution may occur, and precursor ion peak 210 includes a feature of convolution.
As described above, if a precursor ion on the filtered peak list of an IDA method includes a feature of convolution, the precursor ion is not excluded from the filtered peak list of the next cycle so that additional product ion data can be collected for the precursor ion. This additional data can be used to deconvolve the product ions. The precursor ion is not excluded, for example, by adding it to a “do not exclude list.” The do not exclude list is then interrogated during each cycle of the IDA method when the filtered peak list is being created.
For each precursor ion on the do not exclude list there is also stored a number of cycles during which the precursor ion should not be excluded. The number of cycles is decremented each time the precursor ion is additionally fragmented.
In various embodiments, the number of cycles during which the precursor ion should not be excluded is a function of the number of other precursor ions that may be convolved with the precursor ion of the filtered peak list. For example, if one additional precursor ion is found in the isolation window of a precursor ion on the filtered peak list, the number of cycles during which the precursor ion should not be excluded is one or two. If two additional precursor ions are found in the isolation window of the precursor ion on the filtered peak list, the number of cycles during which the precursor ion should not be excluded is two or three. In other words, when a precursor ion on the filtered peak list is found to be convolved with other ions, the number of additional cycles over which data should be collected for the precursor ion is proportional to read number of other precursor ions that are convolved with the precursor ion.
In various embodiments, the number of cycles during which the precursor ion should not be excluded is dependent upon the algorithms used to deconvolve the convolved product ions. For example, if a deconvolution algorithm requires three points across a chromatography peak, then the number of cycles during which the precursor ion should not be excluded is at least two.
In various embodiments, system 800 can also include sample introduction device 840. Sample introduction device 840 can provide a sample to ion source 810 over time using one of a variety of techniques. These techniques include, but are not limited to, gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), or flow injection analysis (FIA).
Mass spectrometer 820 is, for example, a tandem mass spectrometer. A mass analyzer of mass spectrometer 820 can include, but is not limited to, a time-of-flight (TOF), a quadrupole, an ion trap, a linear ion trap, an orbitrap, or a Fourier transform mass analyzer. Mass spectrometer 820 receives the ion beam from ion source 810. As shown in
Mass spectrometer 820 is adapted to perform a plurality of cycles of an IDA experiment on the ion beam. Each cycle of the IDA experiment includes a number of steps. In an MS survey scan step, a precursor MS survey scan is performed, producing a precursor ion mass spectrum. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, among other things, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In an MS/MS step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
Processor 830 can be, but is not limited to, a computer, microprocessor, or any device capable of sending and receiving control signals and data from mass spectrometer 830 and processing data. Processor 830 can be, for example, computer system 100 of
During each cycle of the plurality of cycles, processor 830 performs a number of steps for each precursor ion peak on a filtered peak list produced in the filtering step of the cycle. Processor 830 identifies the precursor ion peak in a precursor ion spectrum produced in the MS survey scan step. Processor 830 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution. Finally, if the precursor ion peak includes a feature of convolution, processor 830 instructs mass spectrometer 820 to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles of the plurality of cycles.
In various embodiments, the number of one or more subsequent cycles during which the precursor ion peak is prevented from being excluded is a function of the number of other precursor ion peaks that are found to be convolved with the precursor ion peak in the feature of convolution.
In various embodiments, processor 830 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution based on the resolving power of the precursor ion peak. Processor 830 calculates a resolving power, R, of the precursor ion peak according to R=m/Δm, where m is the mass-to-charge ratio of the precursor ion peak and Δm is the FWHM of the precursor ion peak. Processor 830 compares the resolving power, R, to a resolving power of mass spectrometer 820. Finally, if the resolving power, R, of the precursor ion peak is less than the resolving power of mass spectrometer 820, processor 830 determines that the precursor ion peak includes a feature of convolution.
In various embodiments, processor 830 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution based on the number of other precursor ion peaks in the MS/MS isolation window of the precursor ion peak. Processor 830 counts the number of other precursor ion peaks located within an isolation window used to fragment the precursor ion represented by the precursor ion peak in the MS/MS step. If the number of other precursor ion peaks is one or more, processor 830 determines that the precursor ion peak includes a feature of convolution.
In various embodiments, processor 830 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution based on peak shape of the precursor ion peak. Processor 830 compares a peak shape of the precursor ion peak to a known shape produced by mass spectrometer 820 for a single precursor ion. A known shape produced by mass spectrometer is, for example, a Gaussian shape. If the peak shape differs from the known shape by more than a predetermined threshold, processor 830 determines that the precursor ion peak includes a feature of convolution.
In various embodiments, processor 830 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution based on the absence of an isotopic pattern for the precursor ion in the precursor ion spectrum. Processor 830 calculates a pattern of one or more isotopic precursor ion peaks for the precursor ion represented by the precursor ion peak based on the known chemical formula of the precursor ion. Processor 830 compares the pattern to the precursor ion spectrum. If the pattern is not found in the precursor ion spectrum, processor 830 determines that the precursor ion peak includes a feature of convolution.
In various embodiments, processor 830 instructs mass spectrometer 830 to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles of the plurality of cycles by adding the precursor ion peak to a do not exclude list. During each filtering step of each cycle of the plurality of cycles the do not exclude list is compared to each precursor ion peak selected for exclusion. The precursor ion peak selected for exclusion is not excluded if the precursor ion peak selected for exclusion is on the do not exclude list.
In various embodiments, the do not exclude list also includes for each precursor ion peak the number of cycles during which the peak should not be excluded. Processor 830 then further adds the number of one or more subsequent cycles of the plurality of cycles during which the precursor ion peak is to be excluded to the do not exclude list along with the precursor ion peak.
In various embodiments, the additional product ion data collected for a convolved precursor ion peak is used in real-time to calculate a deconvolved product ion spectrum for the convolved precursor ion peak. For example, processor 830 further calculates a deconvolved product ion spectrum for the precursor ion peak using a product ion spectrum produced for the precursor ion peak during the MS/MS step of the each cycle and each product ion spectrum produced for the precursor ion peak from each MS/MS step of the one or more subsequent cycles.
In step 910 of method 900, a sample received over time is ionized and an ion beam is produced using an ion source.
In step 920, a plurality of cycles of an IDA experiment are performed on the ion beam using a mass spectrometer. Each cycle of the IDA experiment includes a number of steps. In an MS survey scan step, a precursor ion mass spectrum is produced. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In an MS/MS step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
During each cycle of the IDA experiment and for each precursor ion peak on a filtered peak list produced in the filtering step of each cycle, a number of steps are performed.
In step 930, the precursor ion peak is identified in the precursor ion spectrum produced in the MS survey scan step of the cycle using a processor.
In step 940, it is determined if the precursor ion peak in the precursor ion spectrum includes a feature of convolution using the processor.
In step 950, if the precursor ion peak includes a feature of convolution, the mass spectrometer is instructed to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles using the processor.
In various embodiments, a computer program product includes a tangible computer-readable storage medium whose contents include a program with instructions being executed on a processor so as to perform a method for preventing potentially convolved precursor ion peaks from being excluded in subsequent cycles of IDA experiment so that additional product ion data is collected. This method is performed by a system that includes one or more distinct software modules.
Control module 1010 instructs instruct an ion source to ionize a sample received over time and to produce an ion beam. Control module 1010 instructs instruct a mass spectrometer to perform a plurality of cycles of an IDA experiment on the ion beam. Each cycle of the IDA experiment includes a number of steps. In an MS survey scan step, a precursor MS survey scan is performed, producing a precursor ion mass spectrum. In a peak list step, the peaks of the precursor ion mass spectrum are ranked by intensity. In a filtering step, among other things, precursor ions that were fragmented in a previous cycle are excluded from the peak list and a subset of peaks from the peak list with the highest intensities are selected, producing a filtered peak list. In an MS/MS step, an MS/MS scan is performed on each precursor ion on the filtered peak list, producing a product ion spectrum for each MS/MS scan.
During each cycle of the IDA experiment a number of steps are performed for each precursor ion peak on a filtered peak list produced in the filtering step of the cycle. Analysis module 1020 identifies the precursor ion peak in the precursor ion spectrum produced in the MS survey scan step. Analysis module 1020 determines if the precursor ion peak in the precursor ion spectrum includes a feature of convolution. If the precursor ion peak includes a feature of convolution, control module 1010 instructs the mass spectrometer to prevent the precursor ion peak from being excluded in a filtering step of one or more subsequent cycles of the plurality of cycles of the IDA experiment.
While the present teachings are described in conjunction with various embodiments, it is not intended that the present teachings be limited to such embodiments. On the contrary, the present teachings encompass various alternatives, modifications, and equivalents, as will be appreciated by those of skill in the art.
Further, in describing various embodiments, the specification may have presented a method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. As one of ordinary skill in the art would appreciate, other sequences of steps may be possible. Therefore, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. In addition, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the various embodiments.
This application claims the benefit of U.S. Provisional Patent Application Ser. No. 62/174,264, filed Jun. 11, 2015, the content of which is incorporated by reference herein in its entirety.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/IB2016/053099 | 5/26/2016 | WO | 00 |
| Publishing Document | Publishing Date | Country | Kind |
|---|---|---|---|
| WO2016/198984 | 12/15/2016 | WO | A |
| Number | Name | Date | Kind |
|---|---|---|---|
| 20060169883 | Wang et al. | Aug 2006 | A1 |
| 20110303842 | Nakano | Dec 2011 | A1 |
| 20120191369 | Yamaguchi | Jul 2012 | A1 |
| 20130116934 | Yamada | May 2013 | A1 |
| 20140312220 | Simmons | Oct 2014 | A1 |
| 20150130810 | Yasuda | May 2015 | A1 |
| Number | Date | Country |
|---|---|---|
| 2008111911 | Sep 2008 | WO |
| 2010129187 | Nov 2010 | WO |
| 2015054468 | Apr 2015 | WO |
| Entry |
|---|
| International Search Report and Written Opinion for PCT/IB2016/053099, dated Sep. 12, 2016. |
| Number | Date | Country | |
|---|---|---|---|
| 20180166263 A1 | Jun 2018 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62174264 | Jun 2015 | US |
