System and method for determining location and time of clipped ADC ion response signals in mass spectrometry

Abstract

A method for performing mass spectrometry includes: generating a plurality of ions from an analyte; directing the plurality of ions into an ion detector to generate a plurality of ion detection signals; generating a plurality of data points corresponding to the plurality of ion detection signals, each data point of the plurality of data points representing an intensity of the detected ion as a function of an X parameter, where the X parameter is a function of a mass-to-charge ratio of the detected ion; identifying a cut-off intensity corresponding to a set of cut-off data points of the plurality of data points; identifying a selected set of data points of the plurality of data points based on the set of cut-off data points; and deriving at least one feature corresponding to a maximum point associated with the plurality of data points from the set of selected data points.

Description

[0001] Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 334,871, filed on April 26, 2022, entitled “Systems and Methods for Determining Position and Time of Clipped ADC Ion Response Signals in Mass Spectrometry,” which is incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates generally to ion detectors and, more particularly, to ion detectors used in mass spectrometry. Background Art

[0004] Various techniques (such as mass spectrometers) generate different types of ions from some source molecules (e.g., analytes), produce a stream of these ions, and detect the ions by applying different techniques (such as time-of-flight detection techniques) to the stream. As part of the detection, the system can measure some physical properties of the ions, and determine one or more properties of the source molecules based on those physical properties, such as their chemical composition, structure, etc. The measured physical properties of the ions can include their mass, charge, or mass-to-charge ratio (m / z) of each type of ion, or the intensity of the stream for each type of ion.

[0005] However, existing technologies may not be able to accurately measure some of those physical properties. For example, some of the available measuring instruments (such as analog-to-digital converters ADC) may not be able to measure ion flow intensities above a certain cutoff limit. Therefore, new technologies are needed to make up for these shortcomings of existing measuring instruments and to more accurately obtain the physical properties of ion flow based on the inaccurate measurements of available measuring instruments. Summary of the invention

[0006] In some embodiments, the technology described herein relates to a method for performing mass spectrometry, the method comprising: generating a plurality of ions from an analyte; directing the plurality of ions into an ion detector to generate a plurality of ion detection signals; generating a plurality of data points corresponding to the plurality of ion detection signals, each data point in the plurality of data points representing an intensity of the detected ion as a function of an X parameter, wherein the X parameter is a function of a mass-to-charge ratio of the detected ion; identifying a cutoff intensity corresponding to a set of cutoff data points in the plurality of data points; identifying a set of selected data points in the plurality of data points based on the set of cutoff data points; and deriving at least one feature corresponding to a maximum point associated with the plurality of data points based on the set of selected data points.

[0007] In some embodiments, the technology described herein relates to a method, wherein the set of cutoff data points covers a cutoff portion; and identifying the set of selected data points includes: identifying a first selected data point having a first selected X-parameter located on a first side of the cutoff portion and having a first selected intensity less than the cutoff intensity; identifying a second selected data point having a second selected X-parameter located on a second side of the cutoff portion and having a second selected intensity less than the cutoff intensity and not less than the first selected intensity; and identifying a third selected data point having a third selected X-parameter located on the second side of the cutoff portion and having a third selected intensity less than the first selected intensity.

[0008] In some embodiments, the technology described herein is directed to a method in which deriving at least one feature includes: deriving an interpolated data point from the second selected data point and the third selected data point, the interpolated data point having an intensity equal to the first selected intensity and having an interpolated X-parameter that is not less than the second selected X-parameter and not greater than the third selected X-parameter; deriving a selected X-parameter width from a difference between the interpolated X-parameter and the first selected X-parameter; and deriving the at least one feature from the first selected intensity and the selected X-parameter width.

[0009] In some embodiments, the technology described herein relates to a method in which deriving at least one characteristic from a first selected intensity and a selected X-parameter width includes: determining a ratio of the first selected intensity to a cutoff intensity; and applying a conversion mechanism to the ratio and the selected X-parameter width to determine the at least one characteristic.

[0010] In some embodiments, the technology described herein is directed to a method in which at least one feature includes an intensity of a maximum point associated with a plurality of data points.

[0011] In some embodiments, the technology described herein is directed to a method in which at least one feature includes an X-parameter of a maximum point associated with a plurality of data points.

[0012] In some embodiments, the techniques described herein relate to a method in which the X parameter is the time of flight of the detected ions.

[0013] In some embodiments, the technology described herein relates to a mass spectrometer comprising: an ion source configured to generate a plurality of ions from an analyte; an ion detector configured to receive the plurality of ions and generate a plurality of ion detection signals; and an analyzer module configured to: generate a plurality of data points corresponding to the plurality of ion detection signals, each data point in the plurality of data points representing an intensity of the detected ion as a function of an X parameter, wherein the X parameter corresponds to a mass-to-charge ratio of the detected ion; identify a cutoff intensity corresponding to a set of cutoff data points in the plurality of data points; identify a set of selected data points in the plurality of data points based on the set of cutoff data points; and derive, based on the set of selected data points, at least one feature corresponding to a maximum point associated with the plurality of data points.

[0014] In some embodiments, the technology described herein relates to a mass spectrometer, wherein the set of cutoff data points covers a cutoff portion; and identifying the set of selected data points includes: identifying a first selected data point having a first selected X-parameter located on a first side of the cutoff portion and having a first selected intensity less than the cutoff intensity; identifying a second selected data point having a second selected X-parameter located on a second side of the cutoff portion and having a second selected intensity less than the cutoff intensity and not less than the first selected intensity; and identifying a third selected data point having a third selected X-parameter located on the second side of the cutoff portion and having a third selected intensity less than the first selected intensity.

[0015] In some embodiments, the technology described herein relates to a mass spectrometer, wherein deriving at least one feature includes: deriving an interpolated data point from a second selected data point and a third selected data point, the interpolated data point having an intensity equal to the first selected intensity and having an interpolated X-parameter that is not less than the second selected X-parameter and not greater than the third selected X-parameter; deriving a selected X-parameter width from a difference between the interpolated X-parameter and the first selected X-parameter; and deriving the at least one feature from the first selected intensity and the selected X-parameter width.

[0016] In some embodiments, the technology described herein relates to a mass spectrometer wherein deriving at least one feature based on a first selected intensity and a selected X-parameter width comprises: determining a ratio of the first selected intensity to a cutoff intensity; and applying a lookup table to the ratio and the selected X-parameter width to determine the at least one feature.

[0017] In some embodiments, the technology described herein relates to a mass spectrometer wherein at least one characteristic comprises an intensity of a maximum point associated with a plurality of data points.

[0018] In some embodiments, the technology described herein relates to a mass spectrometer wherein at least one feature comprises an X-parameter of a maximum point associated with a plurality of data points.

[0019] In some embodiments, the technology described herein relates to a method for performing mass spectrometry, the method comprising: digitizing at least one analog ion detection signal to generate a digital signal comprising a plurality of data points, wherein the at least one analog ion detection signal is generated by an ion detector in response to detecting one or more ions received by the ion detector; identifying one or more cutoff data points corresponding to a cutoff intensity associated with the digital signal; selecting a plurality of selected data points from the plurality of data points, each of the plurality of selected data points representing a signal intensity below the cutoff intensity; determining a width of the digital signal using the plurality of selected data points; and calculating a true maximum intensity of the digital signal using the width of the digital signal.

[0020] In some embodiments, the technology described herein relates to a method in which a plurality of data points represent the intensity of a digital signal as a function of time.

[0021] In some embodiments, the technology described herein relates to a method wherein a plurality of selected data points include: a first data point at a first time side of a cutoff portion that includes one or more cutoff data points; and at least two data points at a second time side of the cutoff portion that is opposite to the first time side.

[0022] In some embodiments, the technology described herein relates to a method, which also includes obtaining an interpolation point corresponding to an intersection of an interpolation line and a constant intensity line, wherein the interpolation line connects the at least two data points and the constant intensity line corresponds to the intensity of the first data point.

[0023] In some embodiments, the technology described herein relates to a method in which a width of a digital signal is determined as a distance between a first data point and an interpolation point.

[0024] In some embodiments, the technology described herein relates to a method in which digitizing at least one analog ion detection signal includes feeding the at least one analog ion detection signal to an input of an analog-to-digital converter (ADC).

[0025] In some embodiments, the techniques described herein relate to a method in which one or more cutoff data points correspond to portions of an analog signal that exceed a dynamic range of an ADC.

[0026] In some embodiments, the technology described herein relates to a method that also includes generating one or more ions via ionization of at least one analyte in a sample. A further understanding of various aspects of the embodiments can be obtained by referring to the following detailed description in conjunction with the associated drawings, which are briefly described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings are not necessarily to scale or detailed. Instead, emphasis is generally placed on illustrating the principles of the embodiments described herein. The drawings, which are included in and constitute a part of this specification, illustrate several embodiments consistent with the present disclosure. The drawings, together with the description, are used to explain the principles of the present disclosure.

[0028] In the attached picture:

[0029] Figure 1 is a block diagram of an ion detection system 100 according to some embodiments.

[0030] Figure 2 A data graph 200 is shown illustrating an example of signal truncation by an ADC according to some embodiments.

[0031] Figure 3 is a flow chart of a maximum point obtaining method 300 according to some embodiments, the maximum point obtaining method being used to obtain coordinates of a truncated maximum point corresponding to truncated data.

[0032] Figure 4 The application of the maximum point obtaining method 300 to a set of data points according to an embodiment is shown.

[0033] Figure 5 A three-dimensional lookup surface 500 depicting a lookup table is shown according to an embodiment.

[0034] Figure 6 is a flow chart of a lookup table generation method 600 according to some embodiments.

[0035] Figure 7 A set of graphs 700 is shown in accordance with some embodiments.

[0036] Figure 8 A lookup table generator interface 800 is shown in accordance with some embodiments.

[0037] Fig. 9 An example of an implementation of module 900 according to some embodiments is schematically depicted. DETAILED DESCRIPTION

[0038] It will be appreciated that, for the sake of clarity, the following discussion will illustrate various aspects of the embodiments of the present disclosure, while omitting certain specific details where it is convenient or appropriate to omit them. For example, the discussion of similar or similar features in alternative embodiments may be brief. For the sake of brevity, any very detailed discussion of well-known ideas or concepts may also be omitted. Those of ordinary skill will recognize that some embodiments of the present disclosure may not require certain aspects of the details specifically described in each implementation, and that these details are set forth herein only to provide a comprehensive understanding of the embodiments. Similarly, it will be clear that the described embodiments can be easily modified or varied according to common common sense without departing from the scope of the present disclosure. The following detailed description of the embodiments is not to be construed as limiting the scope of the applicant's teachings in any way.

[0039] Various embodiments address deficiencies in available measurement instruments by providing techniques for deriving some physical properties of ion flow from inaccurate measurements applied to the ion flow. These techniques can be implemented and added to some existing systems, as described in further detail below.

[0040] Figure 1 is a block diagram of an ion detection system 100 according to some embodiments. The ion detection system 100 includes an ion source 110 , a detector 120 , a signal processing board 130 , an ADC 140 (analog to digital converter) and an analyzer module 150 .

[0041] In various embodiments, the ion source 110 can generate one or more ion streams and send them to the detector 120. In some embodiments, the ion source 110 can generate one or more ion pulses, each pulse being referred to as a push. For example, with each push, multiple ions of different types can leave the ion source 110 and arrive at the detector 120. The ions can arrive at the detector 120 during a time period called the time of flight (TOF) for that ion. The TOF for an ion can be a function of its mass-to-charge ratio (m / z). Therefore, multiple ions of the same type can arrive at the detector 120 at the same time.

[0042] In some embodiments, the stream generated by each push may include multiple types of ions generated by the ion source 110 and sent to the detector 120. In addition, each stream may include one or more ions of one type of ion. In particular, the relationship between the number of different types of ions can reveal the composition or structure of one or more molecules from which the ions were generated.

[0043] The detector 120 can convert the detection of ions received from the ion source 110 into an output and send that output to the signal processing board 130. In various embodiments, the detector 120 may include a microchannel plate (MCP), which can generate one or more electrons for each ion that collides with the MCP. In addition, in some embodiments, the detector 120 may include a scintillator, a photodetector. The scintillator can generate one or more photons for each ion that collides with the scintillator, and the photodetector can convert the photons into electrical signals. In some embodiments, the output of the detector 120 can be in the form of an electrical signal, and can have a maximum value of more than 3 volts depending on the number of ions detected. In some embodiments, for each push, ions with the same m / z and therefore arriving at the detector 120 at approximately the same time generate a signal, which is sometimes referred to as a transient. Therefore, each push can generate multiple transients corresponding to multiple groups of ions generated in that push.

[0044] In some embodiments, the signal processing board 130 may receive the signal sent by the detector 120 and attenuate the signal above 3 volts to protect the ADC 140. In some embodiments, the signal thus processed by the signal processing board 130 may have a maximum magnitude of about 4 volts. The signal processing board 130 sends the processed signal to the ADC 140.

[0045] In some embodiments, the ADC 140 can tolerate inputs up to 10 volts, but can truncate (alternatively referred to as clipping or cutting off) signals having magnitudes exceeding a cutoff value. In some embodiments, the cutoff value can be, for example, about 250 mV (millivolts). Truncation of signals is further described below. Some embodiments provide methods and systems for detecting truncation of a signal and obtaining the strength and position of a non-truncated signal represented by the truncated signal for accurate analysis of data.

[0046] In some embodiments, the ion detection system 100 is configured to receive multiple types of ions generated in multiple pushes, and to sum signals corresponding to ions having the same m / z. Specifically, in some embodiments, the analyzer module 150 can receive data corresponding to those summed signals, and analyze the received data to determine the relative number of ions of different m / z values. In some embodiments, the relative intensity of the signal corresponding to each type of ion is proportional to or a function of the relative number of ions of that type detected by the detector 120.

[0047] Figure 2A data graph 200 is shown, illustrating an example of data generated by the system for each transient and also illustrating signal truncation by the ADC according to some embodiments. Specifically, in the data graph 200, the graph 220 corresponds to a non-truncated signal that would be generated for a transient. In the data graph 200, the Y coordinate corresponds to the intensity of the signal measured by the potential of the signal in volts and has a range between -0.2 volts and +2.0 volts. On the other hand, the X coordinate corresponds to the detection time of the signal, measured in picoseconds (ps), and has a range between zero and 25,000 picoseconds.

[0048] In various embodiments, the X-coordinate and the Y-coordinate may correspond to various quantities that may indicate the number of detected ions as a function of their m / z. For example, the X-coordinate may correspond to the time at which the ions arrive at the detector or the time at which the signal arrives at the ADC, etc. In addition, the time may be measured relative to the time at which each push is performed. Typically, the X-coordinate may measure a parameter referred to below as an X-parameter. In various embodiments, the X-parameter may be a function of the m / z of the detected ions. In some embodiments, for example, the X-parameter may correspond to the flight time of the ions. In the data graph 200, the signal shown by the non-truncated graph 220 peaks at a vertex or maximum point 222, where the X value is marked as a common X-value 252 and has a value close to 10,000 ps. This common X-value 252 corresponds to the m / z value of the ions in the transient corresponding to the non-truncated graph 220.

[0049] On the other hand, the Y coordinate can be a function of the number of ions present in the transient. For example, assuming that in this embodiment, each ion generates a 5 mV (millivolt) electrical signal, and considering that the transient signal corresponding to the non-truncated curve graph 220 has a magnitude of approximately 1750 mV (indicated by the maximum Y 254 corresponding to the maximum point 222), the analyzer module can determine that this transient contains 350 (1750 mV divided by 5 mV) ions that all have the same m / z corresponding to the common X value 252.

[0050] When receiving a signal, the ADC can sample and record the received signal at some discrete time points. In the data graph 200, the signal intensity is sampled at time points separated by 800ps, and each signal intensity is shown by a data point 212. As can be seen, the ADC cuts off the intensity of the received signal at a cutoff value 216 (about 250mv), and thus the data points 212 together form a truncated graph 210. The truncated graph 210, or the group of data points 212, is itself divided into five parts: a left platform portion 211, a left wing portion 213, a cutoff portion 215, a right wing portion 217, and a right platform portion 219. The combination of the left wing portion 213, the cutoff portion 215, and the right wing portion 217 forms the detected ion portion or (more succinctly) the detection portion 214.

[0051] The left plateau portion 211 and the right plateau portion 219 include data points with zero intensity. The remaining data, i.e., the detection portion 214, includes data points 212 with non-zero signal intensity. On the other hand, the cutoff portion 215 includes data points 212 whose intensity is truncated at a cutoff value 216.

[0052] Some embodiments provide systems and methods that receive data corresponding to some detected ions, and generate data points based on the data and correspondingly derive features of non-truncated curve graphs associated with the detected ions (or equivalently, with the data points). Examples of those systems and methods are described in further detail below.

[0053] Figure 3 is a flow chart of a maximum point obtaining method 300 according to some embodiments, the maximum point obtaining method being used to obtain the coordinates of a truncated maximum point corresponding to truncated data. The maximum point obtaining method 300 may be performed by a system or a portion of a system such as the above-described ion detection system. In addition, Figure 4 FIG. 3 shows the application of the maximum point obtaining method 300 to a set of data points according to an embodiment. More specifically, Figure 4 A set of graphs 400 is shown where the maximum point obtaining method 300 is applied according to an embodiment to obtain a common X value and a maximum Y for a common ion.

[0054] The graph group 400 includes a truncated graph 410 outlining a set of data points such as data points 412 and 431-436, the truncated graph having portions such as a left wing portion 413, a cutoff portion 415, a right wing portion 417, the combination of which constitutes a detection portion 414. The graph group 400 also includes a non-truncated graph 420 including a non-truncated maximum point 422 having coordinates labeled common X value 424 and maximum Y 426. The graph group 400 also includes a selected Y value 440. These listed portions of the graph group 400 are described in detail below.

[0055] return Figure 3 In the method 300, at step 302, the system generates one or more ions. The ions can be generated by an ion source such as a mass spectrometer or a portion of a mass spectrometer.

[0056] At step 304, the system detects one or more ions. The ions may be detected by any suitable detector, such as an electrical detector or an optical detector.

[0057] At step 306, the system can generate data points corresponding to the detected ions. The data points can correspond, for example, to the detection time and intensity of the signal corresponding to the detected ions.

[0058] With respect to step 306, a graph set 400 includes a plurality of data points, such as data points 431-436 generated by an ion detection system according to an embodiment. For each data point, the Y coordinate may be a function of the intensity of the corresponding signal, and the X coordinate may be a function of the detection time of the corresponding signal. In graph set 400, the Y coordinate has a range in ADC units between about -2000 and about 120000, and the X coordinate has a range between 0 and 20000 picoseconds. In some embodiments, the ADC may record the Y coordinate in ADC units corresponding to 16-bit integers, and thus have a range of 2 16 =65536. In graph set 400, data points with non-zero intensity in detection portion 414 correspond to transients that include detected ions with a common m / z corresponding to common X value 424 (about 9000 picoseconds).

[0059] return Figure 3In the method 300 of , at step 308, the system may identify a cutoff value. The cutoff value is a value on the Y axis at which the system or a portion of the system (such as an ADC) truncates the Y coordinate of the signal corresponding to one or more of the data points. In the group of graphs 400, for example, the system may identify a cutoff value 416 in the truncation graph 410 that is approximately 5500. The system may identify the cutoff value as the maximum value of the Y coordinate among the data points. In some embodiments, a plurality of consecutive data points located at the cutoff portion may have the same Y coordinate equal to the cutoff value. In the truncation graph 410, for example, four data points in the cutoff portion 415 (such as data point 433) display this property, indicating that their signal strengths have been truncated by the system. In some embodiments, the ion detection system 100, or some portion of the ion detection system 100 (such as the signal processing board 130 or the ADC 140) may identify (mark) data points whose intensities have been truncated.

[0060] return Figure 3 In the method 300, at steps 310-316, the system uses the data points in the truncated curve graph 410 to estimate some features of the non-truncated curve graph 420 and, in particular, the coordinates of the non-truncated maximum point 422. To this end, at step 310, the system selects a plurality of data points in the manner described below and identifies them as selected data points to be used in subsequent steps.

[0061] More specifically, and with reference to Figure 4 400, the system identifies three selected points 432, 434, and 435 in the following manner. First, the system identifies data points 432 and 434 as data points having the highest Y coordinate values ​​in the left wing portion 413 and the right wing portion 417, respectively. In other words, the system can select data points 432 and 434 as data points that are not in the cutoff portion 415 and have the highest Y coordinate values ​​on both sides of the cutoff portion 415, indicating that their Y coordinates are not truncated. Next, the system compares the values ​​of the Y coordinates of the two selected points and determines that data point 434 has a higher Y coordinate value. Then, the system identifies and selects data point 435 as the data point having the second highest Y coordinate value on the same wing portion as data point 434, which is the right wing portion 417.

[0062] More generally, at step 310, the system can identify three selected data points that satisfy the following basic conditions. First, the first selected data point of them is located in one of the left wing portion or the right wing portion, and the other two selected data points are located on the other wing portion and their Y coordinates bracket the Y coordinate of the first selected data point (the Y coordinate of one selected data point is located above the Y coordinate of the first selected data point, and the Y coordinate of one selected data point is located below the Y coordinate of the first selected data point). In addition, at least the first two selected data points of the three selected data points need to have non-zero and non-truncated Y coordinates, so they cannot be in the plateau portion or the cutoff portion. In some embodiments, such as the embodiment shown in the curve group 400, in addition to the basic condition, the three selected data points also meet an additional condition: they are the highest data points that meet the basic condition (i.e., have the largest possible Y coordinate in this group). But in other embodiments, they may not have to meet this additional condition. For example, using the data points in the truncation curve graph 410, the system may instead select data point 435 on the right wing portion 417 as the first selected data point, and data points 432 and 431 as the second selected data point and the third selected data point, respectively, on the left wing portion 413, noting that the Y coordinates of data points 432 and 431 bracket the Y coordinate of data point 435. Alternatively, and according to the same procedure, the system may select data point 431 as the first selected data point, and further select data points 435 and 436 as the second selected data point and the third selected data point, respectively.

[0063] return Figure 3 In the method 300, at step 312, the system uses the selected data points to determine one or more parameters referred to as selected parameters. In some embodiments, the selected parameters include a selected Y value (eg, a selected intensity) and a selected width, as described below.

[0064] In some embodiments, to determine the selected parameter, first, the system determines the Y coordinate of the first selected data point (here, data point 432) as the selected Y value (which is labeled as selected Y value 440 and is approximately 30,000 in the curve group 400). Next, the system draws the intersection line 442 as a horizontal line with a Y coordinate equal to the selected Y value. Next, the system determines the interpolation point 444 as the intersection of the intersection line 442 and the straight line (interpolation line) connecting the second selected data point and the third selected data point (here, data points 434 and 435). The interpolation point 444 therefore has a Y value equal to the selected Y value. Finally, the system determines the selected width as the distance (or the difference in their X coordinates) between the first selected data point (here, data point 432) and the interpolation point (here, interpolation point 444). In the curve group 400, the selected width is labeled as selected width 446 and has a value of approximately 4,000 picoseconds.

[0065] return Figure 3 In the method 300, at step 314, the system uses a conversion mechanism to obtain the coordinates of the non-truncated maximum point according to the selected parameters, such as the selected width and the selected Y value determined in step 312. The conversion mechanism is further described below.

[0066] In some embodiments, the shape or maximum point of the non-truncated curve graph 420 can be uniquely determined according to the selected parameters. The analyzer module can use one or more selected parameters in the selected parameters as the input of the conversion mechanism, and the conversion mechanism can output the coordinates of the non-truncated maximum point in response to the input. The conversion mechanism can include one or more of the use of algorithms, parameter formulas for the non-truncated curve graph 420, or lookup tables. Examples of these methods are further described below. In the example of the curve graph group 400, based on the selected Y value 440 and the selected width 446, the system can obtain the coordinates of the non-truncated maximum point 422, which are marked as the common X value 424 and the maximum Y 426, respectively. In some embodiments, instead of using the absolute value of the selected Y value 440, the system can rescale the selected Y value 440 by the cutoff value 416, and instead use the selected Y value 440 divided by the cutoff value 416 (referred to as the rescaled selected Y) as the second parameter. Similarly, instead of finding the absolute value of MaxY 426, the system may find a rescaled value for MaxY 426, ie, MaxY 426 divided by the value of Cutoff 416 (referred to as Rescaled MaxY).

[0067] As described above, in some embodiments, the system uses a conversion mechanism to obtain the coordinates of a non-truncated maximum point associated with a data point based on selected parameters. Generally, the conversion mechanism can be a multi-variable function that receives one or more of the selected parameters as input and outputs the coordinates of the non-truncated maximum point. In various embodiments, the conversion mechanism can be in the form of a lookup table, a two-variable function, or via a three-dimensional surface (such as the following about Figure 5 The discussed lookup surface 500) is implemented in the form of a lookup table or the like.

[0068] Figure 5 A three-dimensional lookup surface 500 depicting such a lookup table is shown according to an embodiment. More specifically, the lookup surface 500 is shown in three-dimensional space, where the three dimensions are labeled selected width 510, selected intensity 520, and rescaled maximum Y 530. Equivalently, the lookup table can receive a selected width and a rescaled selected Y value as two inputs, and return an output rescaled maximum Y value, i.e., a rescaled value for the Y coordinate of a non-truncated maximum point associated with these two inputs or corresponding data points.

[0069] To use the lookup table (depicted by lookup surface 500), the system can first determine the selected width and rescaled selected Y based on the data points corresponding to the detected ions using the systems and methods discussed with respect to method 300 and set of graphs 400. Next, the system can find a point on lookup surface 500 whose coordinates along selected width 510 and selected intensity 520 are the determined selected width and rescaled selected Y, respectively. The system can then determine the coordinates of that point along rescaled maximum Y 530 as the rescaled maximum Y for the rescaled Y of the non-truncated maximum point associated with the data point. Figure 5 , this mechanism is illustrated by point 540 on the lookup surface 500. To find point 540, the system first determines the selected width value of 7100 and the rescaled selected Y value of 0.19 for the data point and marks them along the selected width 510 and the selected intensity 520, respectively. Next, the system finds point 540 on the lookup surface 500 whose projection onto the plane of the selected width 510 and the selected intensity 520 has these coordinates. Finally, the system finds that the coordinate of point 540 along the rescaled maximum Y530 has a value of approximately 2.3, which indicates that the non-truncated maximum point for the data point has a value of approximately 2.3 times the cutoff value for the data point. Equivalently, the system can enter the determined values ​​of 7100 and 0.19 in the lookup table and receive and output 2.3.

[0070] In the above mechanism, the system requires a lookup table or its corresponding lookup surface. Some embodiments use a lookup table generation method to generate the lookup table, as further described below.

[0071] Figure 6 6 is a flow chart of a method 600 for generating a lookup table according to some embodiments. The method 600 may be performed by an ion detection system, or one or more of its parts (such as an analyzer module). Figure 7 A graph set 700 and Figure 8 A lookup table generator interface (abbreviated LUTGI) 800 is shown, both of which are used during implementation of the method 600 according to some embodiments. Figure 6 , Figure 7 and Figure 8 .

[0072] In method 600, at step 602, the system generates one or more transients, and identifies one or more transients among them that are not clipped or truncated. More specifically, the system can identify non-truncated ion detections as ion detections that the ADC has not marked as truncated. In some embodiments, the system can estimate the number of ions in each transient, and select those transients that include less than a set number of ions so that they are not truncated. In some embodiments, the number of ions in a transient can be estimated based on the maximum intensity of the transient. For example, in a system where one ion generates a 10mv signal, a transient with a maximum intensity of approximately 100mv can be estimated to include approximately 10 ions. Furthermore, assuming that the cutoff value in this system is approximately 250 mv, the system can identify transients as non-cutoff transients if the maximum intensity is less than 250 mv and alternatively less than a set maximum value (such as one of 250 mv, 200 mv, 150 mv, 100 mv, etc.), or alternatively, the estimated number of ions in the transient is less than a maximum of 25 ions or less than a set number of ions (which can be one of 20, 15, 10, etc.). Figure 7 In group of graphs 700 , data point 712 represents such a data point generated for the non-truncated transient represented by graph 710 .

[0073] Next, at step 604, the system generates a standardized graph, such as standardized graph 710. A standardized graph is a graph of non-truncated transients whose maximum points (such as vertex 714) have a Y coordinate equal to a cutoff value (such as cutoff value 716). To this end, the analyzer module can generate a graph that connects the data points for each non-truncated transient in one or more non-truncated transients identified at step 602, and then rescales the graph so that its vertices have values ​​equal to the cutoff value. In addition, the analyzer module can aggregate such single transient standardized graphs to generate an aggregated standardized graph. For aggregation, the analysis module can average the Y coordinate values ​​of the single transient standardized graph for each X coordinate. Therefore, aggregation can generate a smoothed standardized graph to be used as the output of step 604.

[0074] The shape of the standardized curve graph may depend on the specific circumstances of one or more parts (such as ion source, detector, signal processing board or ADC) in the different parts of the ion detection system, for example. Therefore, the shape of the standardized curve graph may be specific to the ion detection system, but may not change for the detection of different rounds using the same ion detection system. Therefore, the analyzer module may use the standardized curve graph to obtain the characteristics of the transients generated by the same ion detection system, such as the characteristics of the vertex (maximum point) of the truncated transients, as further described below. In some embodiments, the analyzer module may standardize the transient curve graph so that the vertex has a value other than the cutoff value. In some embodiments, this standardized value for the vertex may be, for example, for the intensity of the transient corresponding to an ion. In various embodiments, for the standardized value for the vertex, the analyzer module may select any positive value that does not exceed the cutoff value. In some embodiments, the result of the analysis may not depend on this standardized value for the vertex, as long as all curve graphs are standardized to the same vertex value. In some embodiments, the reason may be that the final analysis depends on the relative intensity of different ions rather than their absolute values.

[0075] During the remainder of method 600, the system generates multiple graphs, referred to as scaling graphs, from the standardized graph 710, one of which is shown as scaling graph 720. For each scaling graph, a real number, referred to as a scaling factor, is associated with the scaling graph. More specifically, each scaling graph is a version of the standardized graph 710 scaled by a factor equal to its scaling factor. That is, for each X coordinate, the Y coordinate of the scaling graph is equal to the Y coordinate of the standardized graph 710 at the same X coordinate multiplied by the scaling factor. Each scaling graph can represent a non-truncated graph representing a signal associated with the detection of multiple ions, wherein the signal intensity of the multiple ions is equal to the signal intensity for a single ion multiplied by the scaling factor. Therefore, the system can obtain non-truncated parameters corresponding to truncated transients, such as the coordinates of the non-truncated maximum point corresponding to the truncated transients, from the scaling graph.

[0076] Returning to the specific case of method 600, at step 606, the system generates a scaling graph such as scaling graph 720. To do so, the system may select a scaling factor (which is selected to be 1.5 for scaling graph 720) and, for each X coordinate, multiply the Y coordinate of normalized graph 710 by the selected scaling factor to obtain the Y coordinate of the corresponding scaling graph at the same X coordinate.

[0077] exist Figure 8 8, step 606 involves the first three entries of LUTGI 800, which are labeled as initial scaling factor, final scaling factor, and step scaling factor, and are set to 1.0, 10.0, and 0.1, respectively. These settings indicate that, in this embodiment, the lookup table generator will start the scaling factor at a value equal to 1.0 and proceed by incrementing the scaling factor by 0.1 at each step, until a maximum value of 10.0 is reached. For each value of the scaling factor at each step, the lookup table generator performs step 606 by generating a corresponding scaling curve graph as described above. Next, for the generated scaling curve graph, the system performs the remaining steps of method 600, as described below, to obtain a number of entries of the lookup table corresponding to the generated scaling curve graph.

[0078] Specifically, at step 608, the system generates a cross-section of the generated scaling curve graph. To do this, the system selects a rescaling value and generates a horizontal line such as cross-section line 742, whose value of the Y coordinate rescaled by the cutoff value (i.e., the value of cutoff value 716) is equal to the selected rescaling value. In the example of the graph group 700, the selected rescaling value for the cross-section line 742 (i.e., the value of selected Y 740 divided by the value of cutoff value 716) is approximately 0.4.

[0079] Will Figure 6 Method 600 with Figure 8 800, step 608 in method 600 involves the last three entries of LUTGI 800, which are labeled as initial threshold, final threshold, and step threshold, and are set to 0.3, 0.9, and 0.01, respectively. These settings indicate that, in this embodiment, for each of the generated scaling curve graphs described above, the system will start the rescaling value at 0.3 and proceed by incrementing the rescaling value by 0.01 at each step until a maximum rescaling value of 0.9. For each pair of scaling factor and rescaling value, the system performs the remaining steps of method 600, namely step 610, to obtain an entry of the lookup table. Various embodiments may use other values ​​for the settings.

[0080] More specifically, at step 610 of method 600, the system determines the values ​​of one or more parameters corresponding to the previously generated scaling graph and intersection, and records these parameters as an entry in a lookup table. Specifically, the parameters may include a rescaled selected Y and a selected width. In the example shown in graph group 700, these parameters are depicted as a selected width 748 and a selected Y 740 (to be divided by the cutoff value 716 to obtain the rescaled selected Y). Specifically, the selected width 748 is the length of the intersection 744, and the intersection is the portion of the intersection line 742 located within the scaling graph 720. The system can record these two values ​​together with the coordinates of the non-truncated maximum point 722 of the scaling graph 720 as an entry in the lookup table. The coordinates of the non-truncated maximum point 722 may include: its X coordinate, i.e., the common X value 724; and its Y coordinate, i.e., the maximum Y 726 (after being divided by the cutoff value 716 to obtain its rescaled value).

[0081] In some embodiments, instead of recording the common X value 724, the system may instead record a center offset 728. The center offset 728 may indicate the distance between the common X value 724 and the X coordinate of the intersection center 746, which is the midpoint of the intersection 744. The center offset may have an algebraic value, i.e., it may be negative, zero, or positive. For example, in some embodiments, the center offset is equal to the X coordinate of the intersection center minus the value of the common X value. In such embodiments, when applying the conversion mechanism, in addition to determining the width, the system also finds the intersection and its midpoint, i.e., the intersection center, and subtracts the center offset from the intersection center to obtain the common X value.

[0082] In some embodiments, one or more of the coordinates of the non-truncated maximum point may be a function of one but not both of the two parameters, and may not vary with the other. For example, in some embodiments, for a common X value or equivalently the center offset may not vary with the selected Y (or equivalently the rescaled selected Y) but only depend on the selected width. In such a case, the lookup surface may be replaced with a lookup curve that, for example, shows the value of the center offset as a function of the selected width.

[0083] In various embodiments, one or more of the disclosed modules may be implemented via one or more computer programs for performing the functions of the corresponding modules or via a computer processor executing those programs. In some embodiments, one or more of the disclosed modules may be implemented via one or more hardware units of a firmware for performing the functions of the corresponding modules. In various embodiments, one or more of the disclosed modules may include a storage medium for storing data used by the module or a software or firmware program executed by the module. In various embodiments, one or more of the disclosed modules or disclosed storage media may be inside or outside the disclosed system. In some embodiments, one or more of the disclosed modules or storage media may be implemented via a computing "cloud", and the disclosed system is connected to the computing "cloud" via a network connection and uses external modules or storage media accordingly. In some embodiments, the disclosed storage medium for storing information may include a non-transient computer-readable medium, such as a CD-ROM, a computer storage device (e.g., a hard disk), or a flash memory. In addition, in various embodiments, one or more of the storage media may be a non-transient computer-readable medium, which stores data or computer programs executed by various modules, or implements various techniques or flow charts disclosed herein.

[0084] As an example, Fig. 9 Schematically depicted is an example of an implementation of a module 900 according to some embodiments. The module 900 comprises a processor 910 (e.g. a microprocessor), at least one permanent memory module (e.g. a ROM 920), at least one transient memory module (e.g. a RAM) 930, a bus 940 and a communication module 950.

[0085] The processor 910, ROM 920 and RAM 930 may be used to execute and store instructions for performing the functions of the module 900. In addition, the bus 940 may allow communication between the processor and various other components of the controller. The communication module 950 may be configured to allow sending and receiving signals.

[0086] Although some aspects have been described in the context of systems and / or devices, it is clear that these aspects can also represent the description of corresponding methods, where blocks or devices correspond to method steps or features of method steps. Similarly, the aspects described in the context of method steps also represent the description of the features of corresponding blocks or items or corresponding devices. Some or all of the method steps in the method steps can be performed by (or using) hardware devices, such as processors, microprocessors, programmable computers or electronic circuits. In some embodiments, one or more of the most important method steps can be performed by such devices.

[0087] Those of ordinary skill will appreciate that various changes may be made to the above-described embodiments without departing from the scope of the present invention.

[0088] The above detailed description refers to the accompanying drawings. The same or similar reference numerals may be used in the drawings or in the description to refer to the same or similar parts. In addition, similarly named elements may perform similar functions and may be similarly designed unless otherwise specified. The details are set forth to provide an understanding of the exemplary embodiments. Embodiments, such as alternative embodiments, may be practiced without some of these details. In other instances, well-known techniques, procedures, and components are not described in detail to avoid obscuring the embodiments.

[0089] The foregoing descriptions presenting the embodiments are for illustrative purposes only. They are not exhaustive and do not limit the embodiments to the disclosed precise forms. Although several exemplary embodiments and features have been described, modifications, adaptations and other implementations may be possible without departing from the spirit and scope of the embodiments. Therefore, unless otherwise expressly stated, the description relates to one or more embodiments and should not be interpreted as limiting the embodiment as a whole. Whether or not the disclosure states that a feature is related to "one", "the", "one", "one or more", "some" or "various" embodiments, this is correct. As used herein, the singular forms "one", "an" and "the" may include plural forms unless the context expressly specifies otherwise. In addition, the term "coupling" does not exclude the presence of intermediate elements between the coupling items. In addition, stating that a feature may exist indicates that the feature may exist in one or more embodiments.

[0090] In the present disclosure, the terms "comprises," "comprising," "containing," and "having," when used after a group or system, mean open inclusion and do not exclude the addition of other, non-listed members to the group or system. In addition, unless otherwise stated or inferred from the context, if the conjunction "or" is used, the conjunction "or" is not exclusive, but rather inclusive, meaning and / or. Furthermore, if these terms are used, a subset of a group may include one or more than one (including all) members of the group.

[0091] Additionally, if used in this disclosure, and unless otherwise stated or inferred, if the first variable does not decrease when the second variable increases but generally increases, then the first variable is an increasing function of the second variable. On the other hand, if the first variable does not increase when the second variable increases but generally decreases, then the first variable is a decreasing function of the second variable. In some embodiments, if the first variable is directly proportional or inversely proportional to the second variable, then the first variable can be an increasing function or a decreasing function of the second variable, respectively.

[0092] The disclosed systems, methods and devices are not limited to any specific aspect or feature or combination thereof, nor do the disclosed systems, methods and devices require any one or more specific advantages or problems to be solved. Any operating theory is for ease of explanation, but the disclosed systems, methods and devices are not limited to such operating theories.

[0093] Modifications and variations are possible in light of the above teachings, or may be obtained from practical embodiments. For example, the steps do not have to be performed in the same order described or with the same degree of separation. Likewise, various steps may be omitted, repeated, combined, or performed in parallel as needed to achieve the same or similar goals. Similarly, the system does not necessarily have to include all the parts described in the embodiments, and may also include other parts not described in the embodiments. Therefore, the embodiments are not limited to the above details, but are instead defined by the appended claims according to the full scope of their equivalents. In addition, the present disclosure relates to all novel and non-obvious, individual and in various combinations and sub-combinations of the various disclosed embodiments. Features and aspects.

[0094] Although the present disclosure has been described in detail in conjunction with specific embodiments, many substitutions, modifications and variations will be apparent from the foregoing description. It is therefore contemplated that the appended claims will include any such substitutions, modifications and variations that fall within the true spirit and scope of the present disclosure.

Claims

1. A method for performing mass spectrometry, the method comprising: generating multiple ions from the analyte; directing the plurality of ions into an ion detector to generate a plurality of ion detection signals; generating a plurality of data points corresponding to the plurality of ion detection signals, each data point in the plurality of data points representing an intensity of a detected ion as a function of an X parameter, wherein the X parameter is a function of a mass-to-charge ratio of the detected ion; identifying cutoff intensities corresponding to a set of cutoff data points in the plurality of data points; identifying a selected set of data points from the plurality of data points based on the set of cutoff data points; as well as At least one feature corresponding to a maximum point associated with the plurality of data points is derived based on the set of selected data points.

2. The method according to claim 1, wherein: The set of cutoff data points covers a cutoff portion; as well as Identifying the set of selected data points includes: identifying a first selected data point having a first selected X parameter located on a first side of the cutoff portion and having a first selected intensity less than the cutoff intensity; identifying a second selected data point having a second selected X parameter on a second side of the cutoff portion and having a second selected intensity less than the cutoff intensity and not less than the first selected intensity; and A third selected data point is identified, the third selected data point having a third selected X parameter located on the second side of the cutoff portion and having a third selected intensity less than the first selected intensity.

3. The method according to claim 2, wherein: Obtaining the at least one feature comprises: obtaining an interpolated data point from the second selected data point and the third selected data point, the interpolated data point having an intensity equal to the first selected intensity and having an interpolated X parameter not less than the second selected X parameter and not greater than the third selected X parameter; deriving a selected X-parameter width based on a difference between the interpolated X-parameter and the first selected X-parameter; and The at least one feature is derived as a function of the first selected intensity and the selected X-parameter width.

4. The method according to claim 3, wherein: Derivation of the at least one feature based on the first selected intensity and the selected X-parameter width comprises: determining a ratio of the first selected intensity to the cutoff intensity; and A conversion mechanism is applied to the ratio and the selected X-parameter width to determine the at least one characteristic.

5. A method according to any one of the preceding claims, wherein: The at least one feature comprises an intensity of the maximum point associated with the plurality of data points.

6. A method according to any one of the preceding claims, wherein: The at least one feature comprises an X parameter of the maximum point associated with the plurality of data points.

7. A method according to any one of the preceding claims, wherein: The X parameter is the time of flight of the detected ions.

8. A mass spectrometer comprising: an ion source configured to generate a plurality of ions from an analyte; an ion detector configured to receive the plurality of ions and generate a plurality of ion detection signals; as well as The analyzer module is configured to: generating a plurality of data points corresponding to the plurality of ion detection signals, each data point in the plurality of data points representing an intensity of a detected ion as a function of an X parameter, wherein the X parameter corresponds to a mass-to-charge ratio of the detected ion; identifying cutoff intensities corresponding to a set of cutoff data points in the plurality of data points; identifying a selected set of data points from the plurality of data points based on the set of cutoff data points; as well as At least one feature corresponding to a maximum point associated with the plurality of data points is derived based on the set of selected data points.

9. The mass spectrometer of claim 8, wherein: The set of cutoff data points covers a cutoff portion; as well as Identifying the set of selected data points includes: identifying a first selected data point having a first selected X parameter located on a first side of the cutoff portion and having a first selected intensity less than the cutoff intensity; identifying a second selected data point having a second selected X parameter on a second side of the cutoff portion and having a second selected intensity less than the cutoff intensity and not less than the first selected intensity; and A third selected data point is identified, the third selected data point having a third selected X parameter located on the second side of the cutoff portion and having a third selected intensity less than the first selected intensity.

10. The mass spectrometer according to claim 9, wherein: Obtaining the at least one feature comprises: obtaining an interpolated data point from the second selected data point and the third selected data point, the interpolated data point having an intensity equal to the first selected intensity and having an interpolated X parameter not less than the second selected X parameter and not greater than the third selected X parameter; deriving a selected X-parameter width based on a difference between the interpolated X-parameter and the first selected X-parameter; and The at least one feature is derived as a function of the first selected intensity and the selected X-parameter width.

11. The mass spectrometer according to claim 10, wherein: Derivation of the at least one feature based on the first selected intensity and the selected X-parameter width comprises: determining a ratio of the first selected intensity to the cutoff intensity; and A lookup table is applied to the ratio and the selected X-parameter width to determine the at least one characteristic.

12. The mass spectrometer according to any one of claims 8 to 11, wherein: The at least one feature comprises an intensity of the maximum point associated with the plurality of data points.

13. The mass spectrometer according to any one of claims 8 to 12, wherein: The at least one feature comprises an X parameter of the maximum point associated with the plurality of data points.

14. A method of performing mass spectrometry, the method comprising: digitizing at least one analog ion detection signal to generate a digital signal comprising a plurality of data points, wherein the at least one analog ion detection signal is generated by an ion detector in response to detecting one or more ions received by the ion detector; identifying one or more cutoff data points corresponding to a cutoff intensity associated with the digital signal; selecting a plurality of selected data points from the plurality of data points, each selected data point in the plurality of selected data points representing a signal intensity below the cutoff intensity; determining a width of the digital signal using the plurality of selected data points; as well as The true maximum strength of the digital signal is calculated using the width of the digital signal.

15. The method according to claim 14, wherein: The plurality of data points represent the intensity of the digital signal as a function of time.

16. The method according to claim 15, wherein: The plurality of selected data points include: a first data point at a first time side of a cutoff portion including the one or more cutoff data points; and At least two data points at a second temporal side of the cutoff portion opposite the first temporal side.

17. The method according to claim 16 further includes obtaining an interpolation point, wherein the interpolation point corresponds to an intersection of an interpolation line and a constant intensity line, wherein the interpolation line connects the at least two data points and the constant intensity line corresponds to the intensity of the first data point.

18. The method according to claim 17, wherein: The width of the digital signal is determined as a distance between the first data point and the interpolation point.

19. The method according to any one of claims 14 to 18, wherein: Digitizing the at least one analog ion detection signal includes feeding the at least one analog ion detection signal to an input of an analog-to-digital converter ADC.

20. The method according to claim 19, wherein: The one or more cutoff data points correspond to portions of the analog signal that exceed the dynamic range of the ADC.

21. The method of any one of claims 14-20, further comprising generating the one or more ions via ionization of at least one analyte in the sample.

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