Mass spectrum processing apparatus and method

Abstract

It produces a mass difference distribution that allows unambiguous identification of multiple monomer units. [Solution] A mass difference calculator 34 generates a mass difference distribution based on a mass spectrum acquired from a polymer sample. The mass difference distribution includes a main peak and a sequence of secondary peaks attributable to polymers in the polymer sample. A main mass difference determiner 36 determines a main mass difference corresponding to the main peak. A mass difference sequence calculator 38 calculates a mass difference sequence based on the mass difference corresponding to the main peak. A peak eliminater 40 identifies and eliminates a sequence of secondary peaks based on the mass difference sequence.

Description

[Technical Field]

[0001] The present invention relates to a mass spectrometric processing apparatus and method, and in particular to a technique for analyzing polymer samples. [Background technology]

[0002] Generally, a mass spectrometry system includes a mass spectrometer and an information processing device. The mass spectrometer performs mass analysis on a sample. The information output from the mass spectrometer is processed by the information processing device. The information processing device generates a mass spectrum based on the input information and processes the mass spectrum. The information processing device corresponds to a mass spectrum processing device.

[0003] A homopolymer is a polymer having one type of monomer unit (repeating unit). The mass spectrum obtained from a homopolymer contains multiple peaks corresponding to multiple degrees of polymerization. The individual peak intervals (mass differences) among these peaks are the same. The peak interval corresponds to the mass of the monomer unit. The content of the mass spectrum obtained from a polymer sample containing multiple types of homopolymers is generally complex. The content of the mass spectrum obtained from a copolymer is also generally complex. In this specification, copolymer means a polymer having two or more types of monomer units.

[0004] Patent Document 1 describes a mass spectrum processing device. In this mass spectrum processing device, the mass difference and ion intensity ratio are calculated for each peak pair contained in a mass spectrum acquired from a polymer sample. The ion intensity ratio is used as a weight. Multiple intervals are set on the mass difference axis, and a weighted sum is calculated for each interval. A mass difference distribution is formed by multiple weighted sums lined up on the mass difference axis. Specifically, the mass difference distribution is a mass difference list or a mass difference graph. Patent Document 1 does not describe processing such as erasure or removal of multiple peaks contained in the mass difference distribution. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2019-35719 Summary of the Invention [Problem to be solved by the invention]

[0006] The mass difference distribution contains a series of peaks (which may also be referred to as a series of difference values) derived from a particular polymer. The series of peaks includes a peak (main peak) corresponding to a repeating unit and multiple peaks other than the main peak (sub-peak series). To identify multiple monomer units stepwise, it is desirable to make the main peak prominent and the sub-peak series inconspicuous in the mass difference distribution for each polymer contained in the polymer sample.

[0007] It is an object of the present invention to provide a simplified mass difference distribution, or to generate a mass difference distribution in which the masses of the monomer units can be clearly identified. [Means for solving the problem]

[0008] The mass spectrum processing device of the present invention includes a processor that calculates the mass difference for each peak pair contained in a mass spectrum generated by mass analysis of a polymer sample, thereby generating a mass difference distribution, wherein the mass difference distribution includes a series of peaks derived from polymers in the polymer sample, the series of peaks including a main peak corresponding to a monomer unit in the polymer and a series of sub-peaks consisting of multiple sub-peaks other than the main peak, and the processor eliminates the series of sub-peaks in the mass difference distribution based on the main peak.

[0009] A mass spectrum processing method according to the present invention is a mass spectrum processing method executed by an information processing device, and includes a step of calculating a mass difference for each peak pair contained in a mass spectrum generated by mass analysis of a polymer sample, thereby generating a mass difference distribution, wherein the mass difference distribution includes a series of peaks derived from polymers in the polymer sample, the series of peaks including a main peak corresponding to a monomer unit in the polymer and a series of sub-peaks consisting of a plurality of sub-peaks other than the main peak, and the mass spectrum processing method further includes a step of eliminating the series of sub-peaks in the mass difference distribution based on the main peak. [Effects of the Invention]

[0010] The present invention can provide a simplified mass difference distribution, or can generate a mass difference distribution in which the masses of the monomer units can be clearly identified. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a block diagram showing an example of the configuration of a mass spectrometry system according to an embodiment. [Figure 2] FIG. 2 is a diagram showing an example of a mass spectrum. [Figure 3] FIG. 1 is a diagram showing an example of a KMD plot. [Figure 4] FIG. 10 is a diagram illustrating an example of deisotope processing. [Figure 5] FIG. 10 is a diagram showing a plurality of mass differences determined from a plurality of peak pairs. [Figure 6] FIG. 10 is a diagram showing an example of a mass difference list. [Figure 7] FIG. 10 is a diagram showing an example of a mass difference graph. [Figure 8] FIG. 10 is a diagram illustrating an example of an erasure process. [Figure 9] FIG. 10 is a diagram illustrating an example of an image displayed on a display device. [Figure 10] 3 is a flowchart showing mass spectrum processing according to the first embodiment. [Figure 11]FIG. 10 is a diagram illustrating a first example of an erasure process according to the first embodiment. [Figure 12] FIG. 10 is a diagram illustrating a second example of the erasure process according to the first embodiment. [Figure 13] 10 is a flowchart showing mass spectrum processing according to a second embodiment. [Figure 14] FIG. 10 is a diagram illustrating an erasure process according to the second embodiment. [Figure 15] 10 is a flowchart showing mass spectrum processing according to a third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, an embodiment will be described with reference to the drawings.

[0013] (1) Overview of the embodiment A mass spectrum processing apparatus according to an embodiment includes a processor that calculates the mass difference for each peak pair included in a mass spectrum generated by mass analysis of a polymer sample, thereby generating a mass difference distribution. The mass difference distribution includes a series of peaks derived from polymers in the polymer sample. The peak series includes a main peak corresponding to a monomer unit in the polymer and a series of sub-peaks consisting of multiple sub-peaks other than the main peak. The processor eliminates the sub-peak series from the mass difference distribution based on the main peak.

[0014] According to the above configuration, by eliminating the sub-peak sequence in the mass difference distribution, the mass difference distribution can be simplified, and in particular, the main peak can be made more prominent. When a polymer sample contains multiple polymers, multiple sub-peak sequences corresponding to the multiple polymers may be eliminated sequentially. By eliminating the first to i-th sub-peak sequences, it becomes easier to identify the i+1th and subsequent main peaks, where i is an integer greater than or equal to 1. Eliminating the sub-peak sequence is a process that makes the main peak more prominent and the sub-peak sequence less prominent.

[0015] The polymer contains end groups and, in some cases, adduct ions. By calculating the mass difference between two peaks, the mass of the end groups and the mass of the adduct ions are canceled out. In an embodiment, the mass difference distribution is a mass difference graph and / or a mass difference list, as described below. In a mass difference distribution, the substance of each peak constituting a peak train is a combination of mass difference and weight. The main peak in the peak train represents a monomer unit in the polymer. Each sub-peak in the peak train is a peak other than the main peak. A homopolymer contains one type of monomer unit. Therefore, a peak train obtained from a homopolymer contains one main peak. A copolymer contains multiple types of monomer units. Therefore, a peak train obtained from a copolymer contains multiple main peaks.

[0016] In an embodiment, a processor identifies a main peak, calculates a mass difference sequence for searching for secondary peaks based on the main mass difference corresponding to the main peak, and identifies a secondary peak sequence based on the mass difference sequence. The main mass difference corresponding to the main peak corresponds to the mass of a monomer unit. Therefore, a mass difference sequence for searching for secondary peaks is calculated from the main mass difference corresponding to the main peak. A processor according to an embodiment estimates a composition from the main mass difference, calculates a calculated mass (accurate mass) from the estimated composition, and calculates a mass difference sequence for searching for secondary peaks based on the calculated calculated mass. Multiple sections on the mass difference axis may be identified based on the mass difference sequence, and multiple peaks belonging to the identified multiple sections may be identified as secondary peak sequences.

[0017] In an embodiment, the processor identifies a main peak within a main peak search range defined for the mass difference distribution. The main peak search range is a range of masses that the monomer units can have. The main peak search range is specified by a user or determined automatically. For example, within the main peak search range, multiple peaks may be identified as multiple main peaks in order of magnitude, starting from the largest peak.

[0018] In an embodiment, the polymer sample includes a plurality of homopolymers. The mass difference distribution includes a plurality of peak trains derived from the plurality of homopolymers. The plurality of peak trains include a plurality of main peaks corresponding to a plurality of monomer units in the plurality of homopolymers and a plurality of minor peak trains. The processor identifies the plurality of main peaks, calculates a plurality of mass difference trains for searching for minor peaks based on the plurality of main mass differences corresponding to the plurality of main peaks, and identifies and eliminates a plurality of minor peak trains based on the plurality of mass difference trains.

[0019] In an embodiment, the processor calculates a plurality of mass difference sequences by multiplying each of a plurality of mass differences corresponding to a plurality of main peaks by an integer sequence, where the integer sequence is composed of a plurality of integers equal to or greater than 2, and specifically, the integer sequence is composed of, for example, 2, 3, 4, ...

[0020] In an embodiment, the polymer in the polymer sample is a copolymer having multiple different monomer units. The peak sequence includes multiple main peaks corresponding to the multiple monomer units. The processor identifies multiple main mass differences corresponding to the multiple main peaks, calculates a mass difference sequence for searching for secondary peaks based on the multiple main mass differences, and identifies a secondary peak sequence based on the mass difference sequence.

[0021] In an embodiment, the processor calculates the mass difference sequence for searching for the minor peak based on a first-order polynomial including multiple mass differences. For example, if the copolymer includes j types of monomer units, the first-order polynomial has j terms, where j is an integer equal to or greater than 2.

[0022] In an embodiment, the processor applies a first elimination process to the mass difference distribution to eliminate minor peak sequences attributable to homopolymers. The processor also applies a second elimination process to the mass difference distribution to eliminate minor peak sequences attributable to copolymers. Successful completion of the first elimination process indicates the possibility of the presence of homopolymers and, at the same time, the possibility of the presence of copolymers. Successful completion of the second elimination process indicates the existence of copolymers.

[0023] In the embodiment, the mass difference distribution to which the second erasure process is applied is a mass difference distribution to which the first erasure process has already been applied. The first erasure process and the second erasure process may be applied in parallel to the same mass difference distribution.

[0024] In an embodiment, the processor identifies whether the polymer contained in the polymer sample is a homopolymer or a copolymer based on at least the results of the second elimination process. For example, a large number or rate of eliminations in the second elimination process may confirm the presence of a copolymer, while a small number or rate of eliminations in the second elimination process may confirm the presence of multiple homopolymers. Both the results of the first elimination process and the second elimination process may be referenced. The type of polymer may be identified based on multiple main peaks that have a certain relationship.

[0025] A mass spectrum processing method according to an embodiment includes a step of calculating a mass difference for each peak pair included in a mass spectrum generated by mass analysis of a polymer sample, thereby generating a mass difference distribution. The mass difference distribution includes a series of peaks derived from polymers in the polymer sample. The peak series includes a main peak corresponding to a monomer unit in the polymer and a series of sub-peaks consisting of multiple sub-peaks other than the main peak. The mass spectrum processing method further includes a step of eliminating the series of sub-peaks in the mass difference distribution based on the main peak.

[0026] A program (or program product) for executing the above-described mass spectrum processing method may be stored in an information processing device via a network or via a portable storage medium. The information processing device is configured by a computer, a mass spectrum processing device, a mass spectrum processing system, etc. The information processing device has a non-transitory storage medium in which the above-described program is stored.

[0027] (2) Details of the embodiment A mass spectrum processing system according to an embodiment is disclosed in Figure 1. The mass spectrum processing system is a system that acquires a mass spectrum by mass analysis of a polymer sample and analyzes one or more polymers contained in the polymer sample based on the mass spectrum.

[0028] The mass spectrum processing system is composed of a measurement device 10 and an information processing device 12. The measurement device 10 is a mass spectrometer, and the information processing device 12 is composed of a computer. The information processing device 12 corresponds to a mass spectrum processing device.

[0029] The measuring device 10 performs mass analysis on a sample. The measuring device 10 is composed of an ion source 16, a mass analyzer 18, and a detector 20. The ion source 16 is, for example, an ion source that complies with MALDI (Matrix Assisted Laser Desorption / Ionization) or ESI (Electrospray Ionization). A polymer sample S is ionized in the ion source 16. The mass analyzer 18 is, for example, a time-of-flight mass analyzer. Other types of mass analyzers may also be used as the mass analyzer 18. The detector 20 detects individual ions that have passed through the mass analyzer 18. A detection signal output from the detector 20 is converted into detection data in a signal processing circuit (not shown), and the detection data is sent to the information processing device 12.

[0030] The information processing device 12 has a processor 22, a memory 24, an input device (not shown), and a display device 26. The processor 22 performs a plurality of functions, which are represented by a plurality of blocks in FIG.

[0031] The spectrum generator 28 generates a mass spectrum based on the input detection data. The horizontal axis of the mass spectrum is the m / z axis (mass axis), and the vertical axis is the intensity axis (ion intensity axis). The generated mass spectrum is sent to the peak list generator 30 and the display processor 44.

[0032] The peak list generator 30 generates a peak list based on the mass spectrum. The peak list consists of multiple peak information corresponding to multiple peaks included in the mass spectrum. Each peak information is a list element, and each peak information is a combination of m / z and intensity. When generating the peak list, for example, the m / z corresponding to the center of gravity of each peak is identified, and the area of ​​the peak is identified as the ion intensity.

[0033] The deisotope processor 32 applies deisotope processing to the peak list. Specifically, the deisotope processor 32 selects peaks in order from the low mass side to the high mass side, regards the selected peak as a monoisotopic peak, and performs intensity aggregation based on the isotope pattern. As a result, multiple isotope peak components present on the high mass side of the monoisotopic peak are integrated into the monoisotopic peak. Specifically, the intensity of the monoisotopic peak increases, and multiple isotope peaks disappear or the intensities of multiple isotope peaks decrease. The deisotope processing itself is a known technique. The deisotope processing is performed as needed.

[0034] The deisotoped peak list is sent to the mass difference calculator 34 and the KMD (Kendrick mass defect) analyzer 48. The deisotoped peak list is sent to the display processor 44, where a deisotoped mass spectrum may be generated.

[0035] The mass difference calculator 34 calculates the mass difference (more precisely, the m / z difference) for each peak pair based on the deisotoped peak list, in other words, based on the deisotoped mass spectrum. Typically, the peak list contains a large number of peaks, that is, a large number of peak pairs. The mass difference calculator 34 identifies all combinations of two peaks from the peak list and calculates all mass differences based on those peak pairs.

[0036] Also, the mass difference calculator 34 calculates a weight for each peak pair, that is, for each mass difference. In an embodiment, when the intensity of the first peak in a peak pair is represented by A and the intensity of the second peak in the peak pair is represented by B, if A ≥ B, the mass difference calculator 34 calculates B / A as the weight, and if A < B, the mass difference calculator 34 calculates A / B as the weight. In that case, the weight is always a value of 1.0 or less. By calculating the weight in this way, a large weight is given to peak pairs having similar intensities, and a small weight is given to peak pairs having different intensities. The weight may be calculated by other methods.

[0037] Based on a plurality of mass differences and a plurality of weights corresponding to a plurality of peak pairs, the mass difference calculator 34 generates a mass difference list. Specifically, the mass difference calculator 34 sets a plurality of intervals on the mass difference axis (specifically, divides the mass difference axis into a plurality of intervals), and for each individual interval, obtains the total value of the weights. For example, when a plurality of mass differences belong to a certain interval, the plurality of weights associated with those mass differences are added, and the added value becomes the total weight value. When one mass difference belongs to a certain interval, the one weight associated with that mass difference becomes the total weight value. Hereinafter, the total weight value is simply referred to as "weight". The mass difference list has a plurality of weights corresponding to a plurality of intervals. In the mass difference list, for each interval, the peak pair that caused the mass difference belonging to that interval may be associated with that interval.

[0038] In an embodiment, the mass difference calculator 34 generates a mass difference graph based on the mass difference list. The horizontal axis in the mass difference graph is the mass difference axis, and the vertical axis is the weight axis. The mass difference graph corresponds to a mass difference histogram, or corresponds to a weighted mass difference histogram. In the display processor 44 described later, a mass difference graph may be generated based on the mass difference list.

[0039] The generated mass difference graph is stored in memory 24. Together with or instead of the mass difference graph, a mass difference list may be stored in memory 24. Both the mass difference list and the mass difference graph may be referred to as a mass difference distribution.

[0040] When a polymer sample contains m polymers, the mass difference graph obtained from the polymer sample contains m peak trains, where m is an integer equal to or greater than 1. A peak train resulting from a homopolymer contains one main peak and multiple peaks other than the main peak (sub-peak trains). A peak train resulting from a copolymer contains multiple main peaks and multiple peaks other than the multiple main peaks (sub-peak trains).

[0041] In the embodiment, a first erasure process and a second erasure process are provided, which are selectively performed or performed in stages. The first erasure process is for homopolymers, and the second erasure process is for copolymers.

[0042] In a first example described below, a first elimination process is applied to the mass difference graph (or mass difference list). In a second example described below, a second elimination process is applied to the mass difference graph (or mass difference list). In a third example described below, the first and second elimination processes are applied in stages to the mass difference graph (or mass difference list).

[0043] In the first elimination process, the main mass difference determiner 36, the mass difference sequence calculator 38, and the peak eliminator 40 operate repeatedly until a certain termination condition is met.

[0044] The main mass difference determiner 36 identifies the largest peak among the multiple peaks that have not been selected so far within the main peak search range defined on the mass difference graph as the main peak. This identification identifies the main mass difference as the mass difference corresponding to the main peak.

[0045] The mass difference sequence calculator 38 calculates a plurality of mass differences (mass difference sequence) for searching for secondary peaks based on the identified main mass difference (i.e., the mass of the polymer unit). The peak eliminater 40 identifies a secondary peak sequence from the mass difference graph read from the memory 24 based on the mass difference sequence for searching for secondary peaks, and eliminates the secondary peak sequence. The secondary peak sequence may be eliminated from the mass difference list.

[0046] When erasing a series of sub-peaks, the data representing each sub-peak may be completely erased, each sub-peak may be masked, the displayed image representing each sub-peak may be erased, or the brightness of the displayed image representing each sub-peak may be reduced.

[0047] In the first elimination process, if multiple main peaks are included in the main peak search range, the multiple main peaks are identified in order, and multiple sub-peak sequences corresponding to the multiple main peaks are eliminated in order. Multiple main peaks may also be identified simultaneously, and multiple sub-peak sequences may also be eliminated simultaneously.

[0048] In the second elimination process, the main mass difference determiner 36 identifies the top n peaks within a main peak search range defined for the mass difference graph as a main peak set. For example, if n is 2, the main mass difference determiner 36 identifies the largest and second largest peaks within the main peak search range as a main peak set. The main mass difference determiner 36 may identify the main peak set based on a user specification. The mass difference sequence calculator 38 calculates multiple mass differences (mass difference sequence) for searching for secondary peaks based on the main mass difference set (i.e., the masses of multiple polymer units) corresponding to the identified main peak set. The peak eliminater 40 identifies a secondary peak sequence from the mass difference graph read from the memory 24 based on the mass difference sequence for searching for secondary peaks and eliminates the secondary peak sequence. Note that in the second elimination process, the main mass difference determiner 36, mass difference sequence calculator 38, and peak eliminater 40 may be operated repeatedly to identify multiple copolymers.

[0049] The composition estimator 42 estimates the composition formula of the monomer unit based on the main mass difference corresponding to the main peak, i.e., based on the mass of the monomer unit, as necessary. The composition estimator 42 also calculates the calculated mass (accurate mass) of the monomer unit from the estimated composition formula. If multiple main peaks are identified, the composition estimator 42 calculates multiple calculated masses corresponding to them.

[0050] Prior to composition estimation, composition estimation conditions are input. For example, upper and lower limits for the number of atoms for each element may be specified. Mass error ranges, electron counts, charge counts, degree of unsaturation (DBE), etc. may also be specified.

[0051] When composition estimation is performed, the mass difference sequence calculator 38 calculates a mass difference sequence based on one or more calculated masses. The main mass differences include measurement errors. In the process of calculating the mass difference sequence from the main mass differences, composition estimation, i.e., calculation of accurate masses, can be performed to obtain a more accurate mass difference sequence. In the stage of creating the mass difference list, composition estimation may be performed for each list element, i.e., for each individual mass difference.

[0052] The display 26 is configured by, for example, a liquid crystal display, and displays on its screen a mass spectrum, a list of mass differences after elimination processing, a graph of mass differences after elimination processing, analysis results (monomer unit list), and the like.

[0053] The display processor 44 includes an analyzer 46. The analyzer 46 functions in a third embodiment, which will be described later. The analyzer 46 identifies whether the polymer in the polymer sample is a homopolymer or a copolymer based on the results of the first elimination process and / or the results of the second elimination process.

[0054] The KMD analyzer 48 performs KMD analysis based on the peak list after deisotope processing, thereby generating a KMD plot. The KMD plot is displayed on the display 26 as necessary. KMD analysis is a well-known technique, which will be described later. In the KMD analysis, the major mass difference (mass of the monomer unit) determined by the major mass difference determiner 36 may be used as Mr, which will be described later. The exact mass of the monomer unit identified by the composition estimator 42 may be used as Mr, which will be described later.

[0055] FIG. 2 shows a mass spectrum 50 obtained from a polymer sample. The polymer sample is a mixture containing six types of polymers. The six polymers are five types of polyethylene oxide and propylene oxide. The five types of polyethylene oxide have different end groups. It is very difficult to directly identify all six types of monomer units from mass spectrum 50.

[0056] FIG. 3 shows a KMD plot 52 generated by applying KMD analysis to the mass spectrum 50 shown in FIG. 2. The horizontal axis is the NKM (nominal Kendrick mass) axis, and the vertical axis is the KMD axis. One polymer is represented by one element row 56. One element row 56 is composed of multiple elements 54 arranged horizontally, and each element represents a combination of NKM and KMD. The size of the element 54 represents the ion intensity. In the example shown, in the KMD analysis, the calculated mass of C2H4O is specified as the accurate mass Mr of the monomer unit.

[0057] The five types of polyethylene oxide are represented by five element rows 58 parallel to the horizontal NKM axis. Propylene oxide is represented by an element row 60 extending diagonally. This is because the mass of the monomer unit of propylene oxide differs from the above-mentioned Mr. Prior to creating a KMD plot, it is necessary to correctly specify Mr; however, as mentioned above, if the content of the mass spectrum acquired from the polymer sample is complex, it is not possible to accurately identify Mr from the mass spectrum.

[0058] An example of deisotope processing is shown in Figure 4. (A) shows a peak list created from a mass spectrum. Multiple intensities are associated with multiple m / z values. (B) shows the peak list after deisotope processing. In the example shown, deisotope processing has significantly reduced the number of list elements that make up the peak list, i.e., the number of peaks.

[0059] FIG. 5 shows an example of a mass difference calculation. A mass spectrum 62 includes multiple peaks p1 to p6. The multiple peaks p1 to p6 have multiple intensities I1 to I6. In calculating the mass difference, all peak pairs are identified in the mass spectrum 62, and all mass differences are calculated based on all peak pairs. For example, focusing on peak p3, five peak pairs are defined as combinations of peak p3 with peaks p1, p2, p4, p5, and p6. A mass difference d and a weight w are calculated for each peak pair. Specifically, five mass differences d1 to d5 corresponding to the five peak pairs are calculated, and five weights w1 to w5 corresponding to the five peak pairs are calculated. This calculation method corresponds to or is similar to the calculation method disclosed in Patent Document 1.

[0060] A plurality of peaks belonging to mass range A may be used as the object of calculation. Mass range A is defined by a lower limit Amin and an upper limit Amax. A plurality of peaks belonging to intensity range B may be used as the object of calculation. Intensity range B is defined by a lower limit Bmin and an upper limit Bmax. A lower limit and an upper limit for the mass difference to be specified may be set.

[0061] FIG. 6 shows an example of a mass difference list generated by mass difference calculation. The illustrated mass difference list 64 has a mass difference axis 66 as the vertical axis. A plurality of intervals 68 are set on the mass difference axis 66. Each interval 68 is defined by a lower limit and an upper limit. A weight (specifically, a weight sum) is associated with each interval. In the illustrated example, each interval is also associated with a composition formula obtained by composition estimation. In this way, composition estimation may be performed before identifying the main peak. When estimating the composition, the mass corresponding to the center of gravity calculated from one or more weights belonging to the interval may be referenced, or the mass corresponding to the midpoint within the interval may be referenced.

[0062] FIG. 7 shows an example of a difference value graph. The difference value graph is created based on the difference value list. The entity of the difference value graph and the entity of the difference value list are the same. The illustrated difference value graph 70 includes multiple peaks. The multiple peaks include, for example, two peak trains corresponding to two types of homopolymers, as well as a large amount of noise present near the baseline. The horizontal axis of the difference value graph 70 is the mass difference axis, and the vertical axis is the weight axis.

[0063] For example, a main peak search range C is defined for the difference value graph 70 by the user or automatically. The main peak search range C is defined by a lower limit Cmin and an upper limit Cmax. In the illustrated example, a first threshold T1 is also defined. Multiple peaks that belong to the main peak search range C and have weights greater than the threshold T1 are identified, and from among these peaks, the peak that has not been selected so far and has the largest weight is selected as the main peak.

[0064] In the illustrated example, peak P1 is first identified as the first major peak. This identification determines the mass difference (first major mass difference) corresponding to peak P1. The first major mass difference corresponds to the mass of the first monomer unit. Based on the first major mass difference, a first mass difference sequence for searching for minor peaks is calculated using a first calculation formula, which will be described later. Based on the first mass difference sequence, a first minor peak sequence is identified and eliminated.

[0065] Next, peak P2, which belongs to the main peak search range C and has a weight equal to or greater than the first threshold T1 and has not been selected up to now, is identified as the second main peak. This identification determines the mass difference (second main mass difference) corresponding to peak P2. The second main mass difference corresponds to the mass of the second monomer unit. Based on the second main mass difference, a second mass difference sequence for searching for a secondary peak is calculated using a first calculation formula, which will be described later. Based on the second mass difference sequence, a second secondary peak sequence is identified, and the second secondary peak sequence is eliminated.

[0066] If there is no peak that belongs to the main peak search range C and has a weight equal to or greater than the first threshold T1 that has not been selected so far, the main peak search ends.

[0067] When identifying a sub-peak sequence, a sub-peak search range D may be defined. The sub-peak search range D is defined by a lower limit Dmin and an upper limit Dmax. A second threshold T2 may also be defined for searching for a sub-peak. In this case, peaks greater than the threshold T2 may be identified as sub-peaks. Peaks smaller than the second threshold T2 may be considered noise and deleted. In an embodiment, multiple main peaks are identified in sequence, thereby sequentially eliminating multiple sub-peak sequences. This has the advantage of making it easier to identify the next main peak. For example, even if one or more sub-peaks exist within the main peak search range, their influence is avoided or mitigated.

[0068] 8 shows the peak deletion process. (A) shows the difference value list before the deletion process. (B) shows the difference value list after the deletion process. The difference value list before the deletion process includes multiple list elements (i.e., multiple peaks) 74, 76, 78, and 80. Of these, list element 74 corresponds to the main peak, and list elements 76, 78, and 80 correspond to minor peaks, respectively. In the difference value list after the deletion process, list elements 76, 78, and 80 have been deleted, and list element 74 remains.

[0069] 9 shows an image 82 displayed on the screen of the display device. Area 84 is for setting initial conditions. Area 84 has a field 94 for inputting a peak list name, a field 96 for inputting the lower limit of the mass range, a field 98 for inputting the upper limit of the mass range, a field 100 for inputting the lower limit of the intensity range, a field 102 for inputting the upper limit of the intensity range, a field 104 for inputting the upper limit of the mass of the monomer unit to be searched, a field 106 for inputting the lower limit of the mass of the monomer unit to be searched, and a field 108 for inputting the width of each interval on the mass difference axis.

[0070] Area 86 is for specifying deisotope processing conditions. Area 84 has a field 110 for specifying a monomer, a field 112 for specifying an adduct ion, etc. Area 88 is for specifying composition estimation conditions. For example, the upper and lower limits of the number of atoms are specified for each element.

[0071] Area 90 displays mass difference graphs before and after the elimination process. The illustrated mass difference graph 114 is the one after the elimination process. In the illustrated example, mass difference graph 114 has a first main peak P1 and a second main peak P2. Multiple peaks 115 corresponding to noise are present near the baseline. The brightness of these peaks 115 may be reduced. In mass difference graph 114, the first and second minor peak series have been eliminated, resulting in the first and second major peaks P1 and P2 standing out.

[0072] The analysis results of a polymer sample are displayed in area 92. In the illustrated example, a list 116 showing the analysis results of monomer units is displayed in area 92. List 116 has a plurality of list elements 118. Each list element 118 includes a mass difference 120, a weight (weight sum) 122, a composition formula 124, a polymer name 126, and the like.

[0073] Next, a first example will be described with reference to Figures 10 to 12. The first example is carried out on the premise that the polymer sample contains one or more homopolymers.

[0074] FIG. 10 shows the mass spectrum processing according to the first embodiment. In S10, a mass spectrum is generated by mass analysis of a polymer sample. In S12, a peak list is generated based on the mass spectrum. In S14, deisotoping is applied to the peak list. In S16, a mass difference distribution is generated based on the peak list after deisotoping. The mass difference distribution is specifically a mass difference list and a mass difference graph based on the mass difference list. In S18, a main peak that satisfies predetermined conditions is identified from the mass difference graph.

[0075] In S20, a mass difference sequence for searching for a secondary peak is calculated based on the primary mass difference corresponding to the primary peak. Specifically, each mass difference ΔM constituting the mass difference sequence for searching for a secondary peak is calculated by multiplying the primary mass difference (mass of the monomer unit) Ma by each integer k constituting the integer sequence according to the following first calculation formula: ΔM=Ma×k

[0076] Here, k is an integer greater than or equal to 2, specifically, k = 2, 3, 4, etc. If Ma contains a non-negligible measurement error, the measurement error will be magnified by multiplication by the integer k. Preferably, Ma is given a calculated mass obtained by composition estimation.

[0077] In S22, a secondary peak sequence is identified based on the mass difference sequence used for the secondary peak search, and the secondary peak sequence is deleted. In S24, it is determined whether or not to continue searching for another primary peak. If another primary peak is to be searched for, the steps from S18 onwards are executed again. If it is determined in S24 that the primary peak search has ended, the results of the monomer unit search are displayed in S26. For example, an image such as that shown in Figure 9 is displayed.

[0078] FIG. 11 shows a first example of the erasure process according to the first embodiment. (A) shows the mass difference graph before the erasure process. The mass difference graph is a bar graph. The horizontal axis of the mass difference graph is the mass difference axis, and the vertical axis is the weight axis. The mass difference graph is specifically produced from polyethylene oxide. The mass of the polymer unit in polyethylene oxide is 44.026 u.

[0079] The mass difference graph includes multiple peaks P10, P12, P13, and P14. The mass difference corresponding to each peak is shown near the apex of each peak. The main mass difference corresponding to main peak P10 is 44, and multiplying this by 2, 3, and 4 gives mass differences of 88, 132, and 176. The three minor peaks with these mass differences, namely peaks P12, P13, and P14, are the targets for elimination processing.

[0080] (B) shows the mass difference graph after the elimination process. Each eliminated peak may be hidden, displayed at a low brightness, or displayed as a dashed line. The elimination process for peaks P12, P13, and P14 makes the main peak P10 stand out.

[0081] FIG. 12 shows a second example of the erasure process according to the first embodiment. (A) shows the mass difference graph before the erasure process. The mass difference graph is specifically for a mixture of polyethylene oxide and polypropylene oxide. As mentioned above, the mass of the polymer unit in polyethylene oxide is 44.026 u. The mass of the polymer unit in polypropylene oxide is 58.042 u.

[0082] The mass difference graph contains multiple peaks P20, P21, P22, P23, P30, P31, and P32. The mass difference corresponding to each peak is shown near the apex of each peak. The main mass difference corresponding to the first main peak P20 is 44, and multiplying this by 2, 3, and 4 gives mass differences of 88, 132, and 176. The three minor peaks corresponding to these mass differences, namely peaks P21, P22, and P23, are the targets of the first elimination process.

[0083] The mass difference corresponding to the second main peak P30 is 58, and multiplying this by 2 and 3 gives a mass difference of 116,174. The two minor peaks corresponding to these mass differences, namely peaks P31 and P32, are then subjected to the second elimination process.

[0084] (B) shows the mass difference graph after elimination. After elimination of peaks P20, P21, P22, P23, P30, P31, and P32, the two main peaks P20 and P30 stand out.

[0085] Next, a second example will be described with reference to Figures 13 and 14. The second example is carried out on the premise that the polymer sample contains a copolymer.

[0086] Figure 13 shows the mass spectrum processing according to the second embodiment. Steps S30 to S36 are the same as steps S10 to S16 shown in Figure 10. In step S38, a main peak set is identified in the mass difference graph. Specifically, multiple main peaks corresponding to multiple monomer units in the copolymer are identified. The multiple main peaks make up a main peak set. The multiple main peaks may be identified automatically, or may be identified based on user specification.

[0087] In S40, a mass difference sequence for searching for secondary peaks is calculated based on the multiple primary mass differences corresponding to the primary peak set. For example, if a copolymer has two types of monomer units, each mass difference ΔM constituting the mass difference sequence is calculated according to the following second calculation formula: ΔM=Ma×a+Mb×b

[0088] The second calculation formula is a first-order polynomial, and the number of terms in the second calculation formula is two. Here, Ma represents the mass difference corresponding to the first main peak (the mass of the first monomer unit), and Mb represents the mass difference corresponding to the second main peak (the mass of the second monomer unit). a is an integer that varies, for example, within the range of -5 to +5. b is also an integer that varies, for example, within the range of -5 to +5. All combinations (a, b) are given to the second calculation formula. If ΔM is negative, the negative value is invalid.

[0089] If the copolymer has more than two types of monomer units, the second formula is modified accordingly. In general, if the copolymer has j types of monomer units, a first-order formula with j terms is used, where j is an integer greater than or equal to 2.

[0090] In S42, a secondary peak sequence is identified based on the mass difference sequence, and the secondary peak sequence is eliminated. In S46, the monomer unit search results are displayed. After S42, it may be determined whether to repeat S38 to S42. In other words, multiple elimination processes corresponding to multiple copolymers may be applied sequentially.

[0091] Figure 14 shows the erasure process according to the second example. (A) shows the mass difference graph before the erasure process. The mass difference graph is specifically produced from EO (ethylene oxide)-PO (propylene oxide) copolymer.

[0092] The mass difference graph contains many peaks. The mass difference corresponding to each peak is shown near the apex of each peak. The copolymer contained in the polymer sample has a first monomer unit and a second monomer unit. The first main peak P40 and the second main peak P50 correspond to the first monomer unit and the second monomer unit.

[0093] The main mass difference corresponding to the first main peak P40 is 44, and the main mass difference corresponding to the second main peak P50 is 58. A mass difference sequence for searching for secondary peaks is calculated according to the second calculation formula above. A secondary peak sequence to be eliminated is identified based on the mass difference sequence, and the secondary peak sequence is eliminated. (B) shows the mass difference graph after the elimination process. The dashed line sequence 130 indicates the eliminated secondary peak sequence.

[0094] Next, a third embodiment will be described with reference to Fig. 15. In the third embodiment, the first and second erasure processes are performed sequentially. For example, the third embodiment is performed when it is desired to distinguish between m types of homopolymers having m types of monomer units and a copolymer having m types of monomer units.

[0095] In Figure 15, S10 to S22 are the same as S10 to S22 shown in Figure 10. That is, in S10, a mass spectrum is created, in S12, a peak list is created, and in S14, deisotoping is applied to the peak list. In S16, a mass difference distribution is generated based on the peak list after deisotoping. In S18, a main peak is identified in the mass difference distribution. In S20, a mass difference sequence for searching for a secondary peak is calculated based on the main mass difference corresponding to the main peak. In S22, a secondary peak sequence is identified and eliminated based on the mass difference sequence.

[0096] In S50, the result of the elimination of the minor peak sequence is evaluated as necessary. In this case, for example, the number of eliminations or the elimination rate may be calculated as the first evaluation value. The number of eliminations is the number of eliminated peaks. The elimination rate is, for example, the ratio of the number of eliminated peaks to the total number of existing peaks. S24 in FIG. 15 is the same as S24 shown in FIG. 10. Reference numeral 132 denotes the first elimination process. When m major peaks are included in the difference value graph, multiple minor peak sequences corresponding to the m major peaks are eliminated from the difference value graph. m is, for example, 2.

[0097] S38A to S42 in Fig. 15 correspond to S38 to S42 shown in Fig. 13. In S38A, a main peak set is identified. In the third embodiment, the main peak set is composed of m main peaks identified in the first elimination process. In S40, a mass difference sequence for searching for secondary peaks is calculated based on the main peak set. In S42, secondary peak sequences are identified and eliminated based on the mass difference sequence.

[0098] If the analyte is a copolymer having m types of monomer units, the remaining multiple minor peaks are eliminated in S42. Therefore, a large number of eliminations or a large elimination rate is obtained as the second evaluation value in S52. On the other hand, if the analyte is a homopolymer having m monomer units, the m minor peaks have already been eliminated in S22, so no minor peaks are eliminated in S42, or only a small number of peaks are eliminated. Therefore, a small number of eliminations or a small elimination rate is obtained as the second evaluation value in S52. In S52, the analyte is identified based on the second evaluation value. That is, it is identified whether the analyte is a multiple homopolymer or a copolymer. Reference numeral 134 denotes a second elimination process.

[0099] If the polymer sample contains multiple copolymers, the second elimination process 134 may be performed repeatedly. For example, if four main peaks are identified in the first elimination process, various main peak sets may be defined based on the four main peaks, and a second elimination process may be performed for each main peak set.

[0100] In a second embodiment, an analyte may be identified based on both the results of the first and second elimination processes, and the first and second elimination processes may be applied in parallel to the same mass difference distribution.

[0101] According to the mass spectrum processing method of the embodiment, it is possible to simplify the mass difference distribution and make one or more main peaks stand out. In other words, it is possible to clearly identify one or more monomer units. For example, it is possible to accurately determine the exact mass of the monomer unit prior to the KMD analysis described below.

[0102] (3) Explanation of KMD analysis For a given polymer mass M, the Kendrick mass (KM) is defined as follows: KM = M × Mri / Mr (1)

[0103] Here, Mri is the integer mass of the monomer unit, and Mr is the exact mass of the monomer unit. The integer mass of the former can be calculated from the exact mass of the latter. The exact mass is the mass including the decimal point.

[0104] The integer part of KM is defined as the Nominal Kendrick Mass (NKM). The Kendrick Mass Defect (KMD) is defined as the difference between NKM and KM as follows: KMD = NKM - KM (2)

[0105] On the other hand, the mass M of a polymer can generally be expressed as follows: M = Mr × n + Me + Mc (3)

[0106] Here, n is the degree of polymerization, Me is the mass of the terminal group (total mass of the two terminal groups), and Mc is the mass of the adduct ion (total mass of the adduct ions if multiple adduct ions are attached). On the right side of the above formula (3), (Mr × n) is the mass of the main chain portion, and (Me + Mc) is the mass of the portion other than the main chain portion (non-main chain portion).

[0107] By substituting the right-hand side of equation (3) for M in equation (1) above, KM can be expressed as follows: KM = Mri × n + ( Me + Mc ) Mri / Mr (4)

[0108] Since the first term on the right side of equation (4) above is an integer, it does not contribute to KMD. Based on this, KMD can be expressed as follows from equations (2) and (4) above: KMD = Round { ( Me + Mc ) Mri / Mr} - ( Me + Mc ) Mri / Mr (5)

[0109] The first term on the right side of the above equation (5) is NKM. Round{} means rounding off. According to the above equation (5), KMD takes a value within the range of -0.5 to +0.5. KMD does not depend on the degree of polymerization n. More specifically, KMD does not depend on the mass of the main chain portion, but depends on the mass of the non-main chain portion. In KMD analysis, the above coefficient (Mri / Mr) is used to obtain a feature quantity that is not dependent on the mass of the main chain portion.

[0110] An NKM-KMD pair is calculated for each peak in the mass spectrum of a polymer. That is, multiple NKM-KMD pairs corresponding to multiple peaks are obtained. Multiple NKM-KMD pairs are expressed as multiple display elements on a two-dimensional coordinate system having an NKM axis and a KMD axis. This generates a KMD plot (more precisely, an NKM-KMD plot).

[0111] In a KMD plot, multiple display elements corresponding to multiple peaks generated by a certain polymer are arranged at equal intervals parallel to the horizontal axis. For example, each display element is a circle, and in this case, the diameter of each circle is determined according to the area (ionic intensity) of each peak. Note that KMDs that take values ​​in the range of 0 to 1.0 are also known. Such KMDs can also be used in embodiments. [Explanation of symbols]

[0112] 10 measuring device, 12 information processing device, 22 processor, 28 spectrum generator, 30 peak list generator, 32 deisotope processor, 34 mass difference calculator, 36 main mass difference determiner, 38 mass difference sequence calculator, 40 peak eliminator, 44 display processor, 46 analyzer.

Claims

1. a processor for calculating a mass difference for each peak pair included in a mass spectrum generated by mass spectrometry of a polymer sample, thereby generating a mass difference distribution; the mass difference distribution includes a series of peaks attributable to polymers in the polymer sample; the peak train includes a main peak corresponding to a monomer unit in the polymer and a sub-peak train consisting of a plurality of sub-peaks other than the main peak, the processor eliminates the series of minor peaks in the mass difference distribution based on the major peak; A mass spectrum processing apparatus characterized by:

2. 2. The mass spectrum processing apparatus according to claim 1, The processor: Identifying the main peak; calculating a mass difference sequence for searching for a secondary peak based on the primary mass difference corresponding to the primary peak; Identifying the secondary peak sequence based on the mass difference sequence. A mass spectrum processing apparatus characterized by:

3. 3. The mass spectrum processing apparatus according to claim 2, the processor identifies the main peak within a main peak search range defined for the mass difference distribution. A mass spectrum processing apparatus characterized by:

4. 2. The mass spectrum processing apparatus according to claim 1, the polymer sample comprises a plurality of homopolymers comprising the polymer; the mass difference distribution includes a plurality of peak trains originating from the plurality of homopolymers; the plurality of peak trains include a plurality of main peaks and a plurality of sub-peak trains corresponding to a plurality of monomer units in the plurality of homopolymers; The processor: Identifying the plurality of main peaks; calculating a plurality of mass difference sequences for searching for secondary peaks based on a plurality of main mass differences corresponding to the plurality of main peaks; Identifying the plurality of sub-peak sequences based on the plurality of mass difference sequences; Eliminating the plurality of sub-peak sequences; A mass spectrum processing apparatus characterized by:

5. 5. The mass spectrum processing apparatus according to claim 4, the processor calculates the plurality of mass difference sequences by multiplying each of the plurality of mass differences corresponding to the plurality of main peaks by a sequence of integers; A mass spectrum processing apparatus characterized by:

6. 2. The mass spectrum processing apparatus according to claim 1, the polymer is a copolymer having a plurality of monomer units that are different from one another; the peak train includes a plurality of main peaks corresponding to the plurality of monomer units; The processor: Identifying a plurality of major mass differences corresponding to the plurality of major peaks; calculating a mass difference sequence for searching for a secondary peak based on the plurality of primary mass differences; Identifying the secondary peak sequence based on the mass difference sequence. A mass spectrum processing apparatus characterized by:

7. 7. The mass spectrometer according to claim 6, the processor calculates a mass difference sequence for searching the secondary peak based on a first-order polynomial including the plurality of mass differences; A mass spectrum processing apparatus characterized by:

8. 2. The mass spectrum processing apparatus according to claim 1, The processor: applying a first elimination process to the mass difference distribution to eliminate a sequence of sub-peaks derived from homopolymers; applying a second elimination process to the mass difference distribution to eliminate a series of secondary peaks derived from the copolymer; A mass spectrum processing apparatus characterized by:

9. 9. The mass spectrum processing apparatus according to claim 8, the mass difference distribution to which the second erasure process is applied is a mass difference distribution to which the first erasure process has already been applied; A mass spectrum processing apparatus characterized by:

10. 10. The mass spectrum processing apparatus according to claim 9, the processor identifies whether the polymer contained in the polymer sample is a homopolymer or a copolymer based on at least a result of the second elimination process. A mass spectrum processing apparatus characterized by:

11. A mass spectrum processing method executed in an information processing device, comprising: a step of calculating a mass difference for each peak pair included in a mass spectrum generated by mass spectrometry of a polymer sample, thereby generating a mass difference distribution; the mass difference distribution includes a series of peaks attributable to polymers in the polymer sample; the peak train includes a main peak corresponding to a monomer unit in the polymer and a sub-peak train consisting of a plurality of sub-peaks other than the main peak, The mass spectrum processing method further includes a step of eliminating the sequence of minor peaks in the mass difference distribution based on the major peak. A mass spectrum processing method comprising:

12. A program executed in an information processing device, a function for calculating the mass difference for each peak pair included in the mass spectrum generated by mass analysis of the polymer sample, thereby generating a mass difference distribution; the mass difference distribution includes a series of peaks attributable to polymers in the polymer sample; the peak train includes a main peak corresponding to a monomer unit in the polymer and a sub-peak train consisting of a plurality of sub-peaks other than the main peak, the program further includes a function of eliminating the sequence of minor peaks in the mass difference distribution based on the major peak. A program characterized by:

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