Verification of nucleic acid amplification reaction test results

Abstract

Systems, devices, articles, and methods for validating results of nucleic acid amplification reaction tests are disclosed. An example device includes programmable circuitry to instantiate or execute at least one of machine-readable instructions to: calculate amplitude differences between consecutive cycles of a plurality of cycles in a fluorescent signal obtained from the test; determine a sum of the amplitude differences between consecutive cycles; identify a final amplitude; identify a minimum amplitude of the plurality of cycles; determine a distance as a difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and validate a test result based on the ratio.

Description

Technical Field

[0001] This disclosure generally relates to nucleic acid amplification reaction testing, and more specifically to methods and apparatus for verifying the results of nucleic acid amplification reaction testing. Background Technology

[0002] The determination of the amount of nucleic acids of interest in biological samples is used in many industrial, medical, biological, and / or research fields. For example, the detection of pathogen nucleic acids in biological samples can be used to diagnose diseases. Attached Figure Description

[0003] Figure 1 This is a block diagram of an example result verification circuit that can be operated to verify the results of nucleic acid amplification tests.

[0004] Figure 2A -D shows an example curve for a nucleic acid amplification reaction.

[0005] Figure 2E -G is Figure 2A A graph of the mathematical transformation of the example curve of -D.

[0006] Figure 3 and 4 This indicates that it can be implemented, illustrated, and / or carried out by an example programmable circuit. Figure 1 The results verify the flowchart of example machine-readable instructions and / or example operations of the circuit.

[0007] Figure 5 This is a block diagram of an example processing platform including programmable circuitry configured to execute, executor, and / or implement example machine-readable instructions and / or perform... Figure 3 and 4 Example operations to implement Figure 1 The result verification circuit.

[0008] Figure 6 It is used for distributing software, instructions, and / or firmware (e.g., corresponding to...). Figure 3 and Figure 4 A block diagram of an example machine-readable instruction distribution platform (e.g., one or more servers) for client devices associated with end users and / or consumers (e.g., for licensing, selling and / or using), retailers (e.g., for selling, reselling, licensing and / or sub-licensing), and / or original equipment manufacturers (OEMs) (e.g., for inclusion in products to be distributed to, for example, retailers and / or other end users such as direct-purchase consumers).

[0009] Generally, the same reference numerals will be used throughout the accompanying drawings and written description to denote the same or similar parts. The drawings are not necessarily to scale. Detailed Implementation

[0010] This document discloses example apparatus, systems, methods, and articles for analyzing biological samples containing nucleic acids or other analytes. During the testing of the biological sample, copies of nucleic acids are prepared in an amplification reaction to generate a detectable signal. This signal is related to the amount of nucleic acid in the biological sample or the amount of copies of nucleic acid produced by the amplification reaction.

[0011] An example amplification reaction is polymerase chain reaction (PCR). In a PCR test, a nucleic acid sample (e.g., such as DNA or RNA) is amplified to millions to billions of copies. In a PCR test, a reaction mixture including the sample, primers (e.g., oligonucleotides that are complementary sequences to the target nucleic acid), and an enzyme (e.g., DNA polymerase) undergoes thermal cycling, which results in the exponential amplification of the target nucleic acid. Detection of the amplified nucleic acid can be based on fluorescent labels, probes, primers, or dyes bound to the nucleic acid. The fluorescence intensity depends on the concentration or amount of the target nucleic acid in the sample. Therefore, fluorescent materials are used to quantify the PCR test results. The amplitude of the fluorescence signal is recorded for each thermal cycle. In this disclosure, the amplitude of the fluorescence signal refers to the intensity, value, magnitude, or strength of the fluorescence signal. In some examples, the fluorescence signal is measured via an optical reader and in units of measurement called relative fluorescence units (RFUs).

[0012] Ligase chain reaction (LCR) is another amplification method. LCR is similar to PCR. LCR uses two enzymes (e.g., ligase and polymerase). Another amplification method includes isothermal amplification. Isothermal amplification assays are performed at a constant temperature. These and other amplification or detection systems or processes produce signals that can be measured in a time-dependent or cycle-dependent manner, and said signals indicate the amount of target nucleic acid. Although this disclosure refers to examples involving PCR, the teachings of this disclosure can be applied to other amplification or detection systems or processes.

[0013] Signal data representing fluorescence intensity from a PCR test can be plotted as a function of time or cycle number (CN) (or both) in a two-dimensional graph (y vs. x). In some examples, this plot is commonly referred to as a PCR amplification curve or growth curve, and the plotted data may be referred to as PCR amplification data. In some examples, the plot includes multiple PCR amplification curves from multiple reactions. Multiple reactions can include, for example, reactions in different wells of a multi-well plate or in different channels (collectively, channels) of a multi-channel cassette. Different reactions in different channels can be, for example, different assays testing different analytes (e.g., different nucleic acids). For example, Abbott Laboratories has a multiplex assay for testing SARS-CoV-2, fluA (influenza A), fluB (influenza B), and RSV, which is called the Resp-4-Plex assay.

[0014] In typical PCR test results, when the amplification is insufficient to produce a detectable signal, the growth curve characteristically begins to be substantially flat or constant during the early reaction cycles, then rises exponentially until one or more reaction limiting conditions begin to affect the amplification reaction or detection process. Example limiting conditions include the depletion of one or more reactants. Typically, the curve flattens again at or near the end of the reaction.

[0015] In some examples, the fluorescence signal can be altered by noise. For instance, physical bubbles in the reaction mixture may move in front of the reader and cause a rapid increase in the fluorescence signal. Additionally or alternatively, background noise from the environment may be present. Noise in the signal can lead to false positives, in which the fluorescence signal incorrectly indicates the presence of the target nucleic acid in the biological sample. To address noise, in some examples, a control or reference dye is used in one of the channels. The signal obtained from the reference dye can be used as a control to identify and normalize the background noise, which can then be subtracted from other curves. However, including a reference dye uses a dedicated fluorescence channel, which limits the capability of multiplexing because one channel is reserved for the reference dye.

[0016] Furthermore, within the parameter space defined by existing PCR validity checks, it can be difficult to effectively separate positive, negative, and noisy signals from each other in order to identify false positives due to abnormal and / or noisy PCR curves. This may force undesirable trade-offs between sensitivity and specificity. Sensitivity and specificity are measures of a test's ability to correctly classify the presence or absence of a target nucleic acid (which can be used to diagnose whether a subject has a disease or not). Sensitivity reflects the test's ability to identify positive results. High-sensitivity tests have very few false negatives. Specificity reflects the test's ability to identify negative results. Highly specific tests have very few false positives. Highly sensitive tests miss fewer diseases, and highly specific tests avoid misdiagnosing people as positive, which can lead to unnecessary treatment.

[0017] Choosing a high fluorescence signal positivity threshold can prevent noise-related false positives at the cost of reduced sensitivity. Conversely, choosing a low fluorescence signal positivity threshold ensures high sensitivity but exposes the assay to the risk of noise-related false positives. While false positives can have many underlying causes, in this disclosure, "false positive" specifically refers to a subset of false positives caused by fluorescence signal noise. Similarly, "true positive" specifically refers to a subset of true positives that have a standard amplification curve without abnormal fluorescence signal noise.

[0018] The examples disclosed herein provide validity checks that ensure high sensitivity and a low risk of noise-related false positives. Furthermore, the examples disclosed herein can validate nucleic acid amplification (e.g., PCR) test results without the use of reference dyes. Therefore, in some examples, greater reusability is facilitated because additional channels are freely available for additional assays rather than being dedicated to controls or reference signals.

[0019] Figure 1 This is a block diagram of an example result verification circuit 100, operable to verify nucleic acid amplification test results and reduce the number and / or likelihood of false positive results. The result verification circuit 100 includes an example interface circuit 102, an example signal processing circuit 104, an example computation circuit 106, an example evaluation circuit 108, and an example database 110.

[0020] Interface circuit 102 receives, accesses, or otherwise acquires signal data, including fluorescence amplitude data, cycle number data, and time data for nucleic acid amplification assays. In some examples, the data has been processed with noise reduction techniques, such as signal normalization relative to a passive reference dye. Fluorescence signal data from a single PCR reaction can be represented as the data sequence shown in Equation 1.

[0021] F 全长 = [F1, F2, F3, ..., F n Equation (1) In Equation 1, F corresponds to fluorescence, and 1, 2, 3…n correspond to the number of cycles in the amplification reaction. The value of the variable n is based on the type of assay in which the amplification reaction is performed. For example, for a Resp-4-plex assay, there can be 42 cycles. Therefore, in this example, the value of n is 42.

[0022] Signal processing circuit 104 processes signal data. In some examples, signal processing circuit 104 plots the signal data as, for example... Figure 2A The xy curve shown in -D. In some examples, the signal processing circuit 104 plots the inter-cycle differences in the fluorescence signal, such as... Figure 2E -H is shown. Figure 2A In the -H graph, the x-axis corresponds to the number of cycles. Figure 2A The y-axis of -D corresponds to the amplitude of the fluorescence. Figure 2E The y-axis of -H corresponds to the intercycle difference in fluorescence signal. Figure 2B , 2D 2F and 2H are respectively Figure 2A , 2C A magnified version of 2E and 2G. The graph shows the results of the five tests, labeled A, B, C, D, and E. Figure 2A and 2BThe curve is labeled F 全长 It shows the test results for five tests over the full length of the test (i.e., over all cycles).

[0023] In some examples, the signal processing circuit 104 trims the signal data by excluding data from multiple initial cycles. Initial transient variations may exist in the fluorescence readings used for measurement, which can skew the results because the initial readings do not indicate nucleic acid amplification. Therefore, the signal processing circuit 104 creates another dataset for further analysis, i.e., a truncated dataset, as represented by Equation 2.

[0024] F = [F α , F α+1 , F α+2 , …, F n Equation (2) In Equation 2, α corresponds to the cycle (or index) of the first fluorescence reading to be included in the analysis. The value of the variable α depends on the type of assay for which the amplification reaction is performed. For example, for a Resp-4-Plex assay, the value of α is 11. Therefore, in this example, the signal processing circuit 104 excludes data from the first 11 cycles from further analysis. In other examples, α has other values, such as 10. The value of α depends on the needs and characteristics of the assay. In some examples, the value of α is determined empirically based on analysis of previously known results. Figure 2C and 2D The curve is marked with F, and the first α cycles are excluded.

[0025] Figure 2A All five tests shown in -H are classified as positive results. However, some are noise-related false positives. Noise-related false positives can take many forms. For example, Figure 2A Curve C is an example of a sawtooth curve caused by noise. Curve D is an example of a single-cycle step curve caused by noise. Furthermore, curve E is an example of two-cycle step curves caused by noise. If these curves have a reference dye, the reference dye will have a very similar fluorescence curve, resulting in a flat, relatively noise-free normalized signal. However, without normalization, these types of PCR curves may escape current validity checks because they appear similar to normal positive PCR curves in dimensions of evaluation, such as the number of cycles the signal crosses above a threshold above the background signal.

[0026] The calculation circuit 106 calculates the intercycle difference in the fluorescence data. The intercycle difference in the fluorescence data is also called the amplitude difference or amplitude variation. The calculation circuit 106 generates a data sequence T of intercycle differences in the fluorescence signal values, as shown in Equation 3.

[0027] T = [F α+1 - F α , F α+2 - F α+1 , …, F n - F n-1 Equation (3) Figure 2E and 2F The curve is labeled with T, which is a curve of the inter-cycle differences in five tests.

[0028] The calculation circuit 106 sorts the inter-cycle differences from highest to lowest, or from most to least. The calculation circuit 106 generates a data sequence S of the sorted inter-cycle differences in the fluorescence signal values, which is represented by Equation 4.

[0029] S = [T α+1 , T α+2 , …, T n Equation (4) S1 will be the biggest difference, S2 will be the second biggest difference, and so on. Figure 2G and 2H The graph is labeled with an 'S', which is a graph of the intercycle differences ranked in the five tests.

[0030] The result validation circuit 100 performs one or more validity checks on the nucleic acid amplification results to verify that a positive result is a true positive indicating the presence of the target nucleic acid in the biological sample, rather than a noise-related false positive. The validity checks expand the dimensions of evaluation using the data series disclosed herein to identify noisy PCR curves as anomalies, thus preventing false positive PCR results due to fluorescence noise.

[0031] The first validity check performed by the result verification circuit 100 utilizes the inter-cycle difference data sequence T. In the first validity check, the calculation circuit 106 calculates the total distance of the inter-cycle differences. As shown in Equation 5, the total distance is the sum of the absolute values ​​of the inter-cycle differences.

[0032] Total distance = Equation (5) The calculation circuit 106 calculates the upward distance. The upward distance is the difference between the amplitude or intensity of the fluorescence signal in the last cycle and the minimum amplitude, as shown in Equation 6.

[0033] Upward distance = F n – min (F α … F n Equation (6) The calculation circuit 106 calculates the total distance ratio (TDR) as shown in Equation 7.

[0034] Total distance ratio = Total distance / Upward distance, equation (7) Evaluation circuit 108 compares the total distance ratio to a threshold total distance ratio. The threshold total distance ratio is based on the type of assay performed to conduct the nucleic acid amplification reaction. In some examples, the threshold total distance ratio is determined empirically. In some examples, the threshold total distance ratio is based on the distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold total distance ratio just exceeds the maximum value of true positive results. In some examples, the threshold total distance ratio just falls below the minimum value of false positive results. In some examples, the threshold total distance ratio is derived from or based on statistical methods, such as a specific number of standard deviations of the average total distance ratio away from the true positive population. In some examples, "just exceeds" the maximum value indicates a range of 0.1% to 0.9% of the maximum value. In some examples, "just exceeds" the maximum value indicates a range of 1% of the maximum value. In some examples, "just falls below" the minimum value indicates a range of 0.1% to 0.9% of the minimum value. In some examples, "just falls below" the minimum value indicates a range of 1% of the minimum value.

[0035] If the total distance ratio meets the threshold (e.g., the total distance ratio is less than the threshold total distance ratio), the result of the nucleic acid amplification reaction test is considered valid. If the total distance ratio does not meet the threshold (e.g., the total distance ratio is greater than the threshold total distance ratio), the result of the nucleic acid amplification reaction test is considered invalid. An invalid result indicates a false positive.

[0036] The second validity check performed by the result verification circuit 100 utilizes the sorted inter-cycle difference data sequence S. In the second validity check, the calculation circuit 106 identifies the largest and second largest inter-cycle differences. The calculation circuit 106 calculates the maximum Δ ratio (LDR), which is the ratio of the largest distance to the second largest distance, as shown in Equation 8.

[0037] Maximum Δ ratio = S1 / S2 = (maximum inter-cycle difference) / (second largest inter-cycle difference) Equation (8) Evaluation circuit 108 compares the maximum Δ ratio to the threshold maximum Δ ratio. The threshold maximum Δ ratio is determined based on the type of assay performed for nucleic acid amplification. In some examples, the threshold maximum Δ ratio is determined empirically. In some examples, the threshold maximum Δ ratio is determined based on the distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold maximum Δ ratio just exceeds the maximum value of true positive results. In some examples, the threshold maximum Δ ratio just falls below the minimum value of false positive results. In some examples, the threshold maximum Δ ratio is derived from or based on statistical methods, such as, for example, a specific number of standard deviations from the average maximum Δ ratio of the true positive population. In some examples, "just exceeding" the maximum value indicates within 0.1% to 0.9% of the maximum value. In some examples, "just exceeding" the maximum value indicates within 1% of the maximum value. In some examples, "just below" the minimum value indicates within 0.1% to 0.9% of the minimum value. In some examples, "just below" the minimum value indicates within 1% of the minimum value.

[0038] If the maximum Δ ratio meets the threshold (e.g., the maximum Δ ratio is less than the threshold maximum Δ ratio), the result of the nucleic acid amplification reaction test is considered valid. If the maximum Δ ratio does not meet the threshold (e.g., the maximum Δ ratio is greater than the threshold maximum Δ distance ratio), the result of the nucleic acid amplification reaction test is considered invalid. Invalid results indicate false positives.

[0039] The third validity check, performed by the result verification circuit 100, utilizes the sorted inter-cycle difference data sequence S. In the third validity check, the calculation circuit 106 identifies the second and third largest inter-cycle differences. The calculation circuit 106 calculates the second largest Δ ratio (2LDR), which is the ratio of the second largest distance to the third largest distance, as shown in Equation 9.

[0040] Second largest Δ ratio = S2 / S3 = (Second largest inter-cycle difference) / (Third largest inter-cycle difference) Equation (9) Evaluation circuit 108 compares the second largest Δ ratio to a threshold second largest Δ ratio. The threshold second largest Δ ratio is determined based on the type of assay performed for nucleic acid amplification. In some examples, the threshold second largest Δ ratio is determined empirically. In some examples, the threshold second largest Δ ratio is based on the distribution of normal or known positive nucleic acid amplification curves compared to known false positives. In some examples, the threshold second largest Δ ratio just exceeds the maximum value of true positive results. In some examples, the threshold second largest Δ ratio just falls below the minimum value of false positive results. In some examples, the threshold second largest Δ ratio is derived from or based on statistical methods, such as a specific number of standard deviations from the average second largest Δ ratio of the true positive population. In some examples, "just exceeds" the maximum value indicates it is within 0.1% to 0.9% of the maximum value. In some examples, "just exceeds" the maximum value indicates it is within 1% of the maximum value. In some examples, "just falls below" the minimum value indicates it is within 0.1% to 0.9% of the minimum value. In some examples, "just falls below" the minimum value indicates it is within 1% of the minimum value.

[0041] If the second largest Δ ratio meets the threshold (e.g., the second largest Δ ratio is less than the threshold second largest Δ ratio), the nucleic acid amplification reaction test result is considered valid. If the second largest Δ ratio does not meet the threshold (e.g., the second largest Δ ratio is greater than the threshold second largest Δ ratio), the nucleic acid amplification reaction test result is considered invalid. Invalid results indicate false positives.

[0042] Figure 2A The five example curves in -H all show positive test results. In this example, measurements C, D, and E are false positives due to noise, while measurements A and B are true positives as legitimate PCR amplification curves. Example data are shown in Table 1. Example Measurement noise TDR LDR 2LDR A None (strong) 1.004 1.010 1.193 B None (weak) 1.163 1.246 1.317 C have 5.937 1.094 1.499 D have 1.329 17.233 1.536 E have 1.581 1.129 24.146 Table 1.

[0043] In some examples, positive PCR curves will have total distance ratio (TDR), maximum Δ ratio (LDR), and second largest Δ ratio (2LDR) values ​​close to one. As expected of a strong positive PCR curve, example assay A has TDR, LDR, and 2LDR values ​​close to one. Very weak positive PCR curves tend to have slightly larger TDR, LDR, and 2LDR values, as shown in example assay B. However, even the values ​​associated with weak, legitimate positive PCR curves are far removed from those associated with noisy, false-positive PCR curves. Examples C, D, and E demonstrate how significantly higher TDR, LDR, or 2LDR values ​​can be relative to normal PCR curves in noisy PCR curves.

[0044] In one example, if the threshold total distance ratio (X) TDR ), threshold maximum Δ ratio (X) LDR) and the second largest Δ ratio of the threshold (X) 2LDR If all of them have a value of 2.5, then: • Example assay A remains valid (i.e., is legally identified as a positive result) because TDR = 1.004, which is less than or equal to 2.5 (X). TDR LDR = 1.010, which is less than or equal to 2.5 (X). LDR ); and 2LDR = 1.193, which is less than or equal to 2.5(X). 2LDR ).

[0045] • Example test result B remains valid (i.e., is legally identified as a positive result) because TDR = 1.163, which is less than or equal to 2.5 (X). TDR LDR = 1.246, which is less than or equal to 2.5(X). LDR ); and 2LDR = 1.317, less than or equal to 2.5(X 2LDR ).

[0046] • Example assay C was successfully invalidated (i.e., correctly identified as a false positive) because TDR = 5.937, which is greater than 2.5 (X). TDR ).

[0047] • Example assay D was successfully invalidated (i.e., correctly identified as a false positive) because LDR = 17.233, which is greater than 2.5 (X). TDR ).

[0048] • Example determination E was successfully invalidated (i.e., correctly identified as a false positive) because 2LDR = 24.146, which is greater than 2.5 (X). 2LDR ).

[0049] This example illustrates how the TDR, LDR, and 2LDR validity checks performed by the result verification circuit 100 can selectively invalidate false positive results caused by noisy signals. Furthermore, although three types of validity checks are disclosed herein, in some examples, the failure of one validity check is sufficient to classify the result as invalid (i.e., a false positive). In other examples, two or three validity checks may be used to confirm the result.

[0050] The validity check performed by the result validation circuit 100 creates measurements that can be compared to theoretically ideal values ​​and increases the number of orthogonal assessments of PCR curve normality. For example, Figure 2ACurve C in -H does not differ sufficiently from a normal PCR curve in the dimensions of cycle difference, LDR, and 2LDR to be invalid as a false positive. However, curve C differs sufficiently in the TDR dimension to identify it as different from a normal curve and should be invalidated as a false positive. Similarly, curves D and E are relatively normal in all dimensions except LDR and 2LDR. The validity check disclosed herein prevents noise-related false positives without resorting to, for example, a higher Ct threshold that may reduce assay sensitivity.

[0051] In some examples, evaluation circuit 108 identifies whether a parameter is satisfied before implementing one or more of the validity checks disclosed herein. For example, if evaluation circuit 108 identifies that Ct (threshold cycle number) is earlier than a positive cycle cutoff number, result verification circuit 100 implements one or more of the total distance ratio, maximum Δ ratio, and / or second largest Δ ratio validity checks.

[0052] The data used by the components of the result verification circuit and the data generated by the components of the result verification circuit 100 can be stored in and / or retrieved from the database 110. Furthermore, results (e.g., true or false positive designation for nucleic acid amplification tests) can be transmitted from the result verification circuit 100 via the interface circuit 102.

[0053] Figure 1 The result verification circuit 100, interface circuit 102, signal processing circuit 104, calculation circuit 106, and / or evaluation circuit 108 can be instantiated (e.g., created as an example, made to run at any time, materialized, implemented, etc.) by a programmable circuit such as a central processing unit (CPU) that executes the first instruction. Additionally or alternatively, Figure 1 The result verification circuit 100, interface circuit 102, signal processing circuit 104, calculation circuit 106, and / or evaluation circuit 108 can be instantiated (e.g., created as an example, made concrete, implemented, etc.) by (i) an application-specific integrated circuit (ASIC) and / or (ii) a field-programmable gate array (FPGA) that is structured and / or configured to perform an operation corresponding to the first instruction in response to the execution of the second instruction. It should be understood that... Figure 1 Some or all of the circuitry can therefore be instantiated at the same or different times. For example, it can be instantiated in one or more threads that execute concurrently on the hardware and / or serially on the hardware. Figure 1 Some or all of the circuitry. Furthermore, in some examples, Figure 1 Some or all of the circuitry can be implemented by microprocessor circuitry that executes instructions and / or FPGA circuitry that performs operations to implement one or more virtual machines and / or containers.

[0054] In some examples, the device includes means for verifying the results of the nucleic acid amplification reaction. For example, the means for verification can be implemented by a result verification circuit 100. In some examples, the result verification circuit 100 can be implemented by, for example, Figure 5 The example programmable circuit 512 is used as an example to illustrate this. For example, the result verification circuit 100 can be provided by... Figure 5 This is illustrated by an example processor circuit 512, which performs actions such as those described by... Figure 3 and 4 The result verification circuit 100 is implemented by a machine-executable instruction. In some examples, the result verification circuit 100 may be exemplified by hardware logic circuitry, which may be implemented by ASIC, XPU, FPGA circuitry, configured and / or constructed to perform operations corresponding to the machine-readable instructions. Additionally or alternatively, the result verification circuit 100 may be exemplified by any other combination of hardware, software, and / or firmware. For example, the result verification circuit 100 may be implemented by at least one or more hardware circuits (e.g., processor circuitry, discrete and / or integrated analog and / or digital circuitry, FPGA, ASIC, XPU, comparator, operational amplifier, logic circuitry, etc.) configured and / or constructed to perform some or all of the machine-readable instructions, and / or perform some or all of the operations corresponding to the machine-readable instructions without executing software or firmware, but other configurations are equally suitable.

[0055] Despite Figure 1 An example of implementing the result verification circuit 100 is shown, but Figure 1 One or more of the elements, processes, and / or devices shown may be combined, divided, rearranged, omitted, eliminated, and / or implemented in any other way. Furthermore, example interface circuit 102, example signal processing circuit 104, example calculation circuit 106, example evaluation circuit 110 (and / or more generally...) Figure 1 The example result verification circuit 100 can be implemented solely by hardware, or by hardware in combination with software and / or firmware. Therefore, for example, any of the example interface circuit 102, example signal processing circuit 104, example computing circuit 106, example evaluation circuit 110 (and / or more generally, example result verification circuit 100) can be implemented by programmable circuitry combined with machine-readable instructions (e.g., firmware or software), processor circuitry, analog circuitry, digital circuitry, logic circuitry, programmable processors, programmable microcontrollers, graphics processing units (GPUs), digital signal processors (DSPs), ASICs, programmable logic devices (PLDs), and / or field-programmable logic devices (FPLDs) (such as FPGAs). Furthermore, Figure 1 Example result verification circuit 100 may include, in addition to Figure 1 One or more elements, processes and / or devices other than or in place of those elements, processes and / or devices shown, and / or may include more than one of any or all of the elements, processes and / or devices shown.

[0056] Figure 3 and Figure 4 A flowchart illustrating example machine-readable instructions is shown, which can be executed by programmable circuitry to implement and / or instantiate such instructions. Figure 1 The result verification circuit 100, and / or representation, can be implemented and / or instantiated by a programmable circuit. Figure 1 The results verify an example operation of circuit 100. Machine-readable instructions may be one or more executable programs, or portions thereof, for execution by programmable circuitry, such as those described below. Figure 5 The processor circuitry 512 shown in the example processor platform 500 discussed herein. In some examples, machine-readable instructions enable an operation, task, etc., to be performed and / or completed in a real-world manner in an automated manner. As used herein, “automation” means without human intervention.

[0057] The program may be embodied in instructions (e.g., software and / or firmware) stored on one or more non-transitory computer-readable and / or machine-readable storage media, such as cache memory, magnetic storage devices or disks (e.g., floppy disks, hard disk drives (HDDs), etc.), optical storage devices or disks (e.g., Blu-ray discs, compact discs (CDs), digital versatile discs (DVDs), etc.), redundant arrays of independent disks (RAID), registers, ROM, solid-state drives (SSDs), SSD memory, non-volatile memory (e.g., electrically erasable programmable read-only memory (EEPROM), flash memory, etc.), volatile memory (e.g., random access memory (RAM) of any type), and / or any other storage device or disk. The instructions on the non-transitory computer-readable and / or machine-readable media may be programmed and / or executed by programmable circuitry located in one or more hardware devices, but the entire program and / or portions thereof may alternatively be executed and / or instantiated and / or embodied in dedicated hardware by one or more hardware devices other than programmable circuitry. Machine-readable instructions can be distributed across multiple hardware devices and / or executed by two or more hardware devices (e.g., server and client hardware devices). For example, client hardware devices can be implemented by endpoint client hardware devices (e.g., hardware devices associated with human and / or machine users) or intermediate client hardware device gateways (e.g., radio access networks (RAN)) that facilitate communication between server and endpoint client hardware devices. Similarly, non-transitory computer-readable storage media can include one or more media. Furthermore, although references... Figure 3 and 4 The flowchart shown describes an example program, but many other methods of implementing the example result verification circuit 100 can be used alternatively. For example, the execution order of the flowchart blocks can be changed, and / or some of the described blocks can be changed, eliminated, or combined. Additionally or alternatively, any or all of the flowchart blocks may be implemented by one or more hardware circuits (e.g., processor circuits, discrete and / or integrated analog and / or digital circuits, FPGAs, ASICs, comparators, operational amplifiers (op-amps), logic circuits, etc.) structured to perform the corresponding operations without executing software or firmware. Programmable circuits may be distributed across different network locations and / or be local to one or more hardware devices (e.g., single-core processors (e.g., single-core CPUs), multi-core processors (e.g., multi-core CPUs, XPUs, etc.)). For example, programmable circuits may be CPUs and / or FPGAs located in the same package (e.g., the same integrated circuit (IC) package or two or more separate housings), one or more processors in a single machine, multiple processors distributed across multiple servers in a server rack, multiple processors distributed across one or more server racks, and / or any combination thereof.

[0058] The machine-readable instructions described herein can be stored in one or more of the following formats: compressed format, encrypted format, segmented format, compiled format, executable format, and encapsulated format. The machine-readable instructions described herein can be stored as data (e.g., computer-readable data, machine-readable data, one or more bits (e.g., one or more computer-readable bits, one or more machine-readable bits, etc.), bit streams (e.g., computer-readable bit streams, machine-readable bit streams, etc.) or data structures (e.g., as part of a representation of instructions, code, etc.), which can be used to create, manufacture, and / or produce machine-executable instructions. For example, machine-readable instructions can be segmented and stored on one or more storage devices, disks, and / or computing devices located at the same or different locations within a network or network set (e.g., in the cloud, at an edge device, etc.). (For example, on a server). Machine-readable instructions may need to be installed, modified, adapted, updated, combined, supplemented, configured, decrypted, decompressed, unpacked, distributed, redistributed, compiled, etc., to make them directly readable, interpreted, and / or executed by computing devices and / or other machines. For example, machine-readable instructions may be stored in multiple parts, which are individually compressed, encrypted, and / or stored on separate computing devices, wherein, when decrypted, decompressed, and / or combined, these parts form a set of computer-executable and / or machine-executable instructions, the implementation of which may together form one or more functions and / or operations of a program such as the program described herein.

[0059] In another example, machine-readable instructions may be stored in a state where they can be read by programmable circuitry, but libraries (e.g., dynamic link libraries (DLLs)), software development kits (SDKs), application programming interfaces (APIs), etc., need to be added to execute the machine-readable instructions on a specific computing device or other device. In another example, the machine-readable instructions (e.g., storage settings, data input, recorded network addresses, etc.) may need to be configured before they can be executed in whole or in part. Therefore, machine-readable, computer-readable, and / or machine-readable media as used herein can include instructions and / or programs, regardless of their specific format or state.

[0060] The machine-readable instructions described in this article can be represented by any past, present, or future instruction language, scripting language, programming language, etc. For example, machine-readable instructions can be represented using any of the following languages: C, C++, Java, C#, Perl, Python, JavaScript, Hypertext Markup Language (HTML), Structured Query Language (SQL), Swift, etc.

[0061] As mentioned above, Figure 3 and Figure 4 Example operations can be implemented using executable instructions (e.g., computer-readable and / or machine-readable instructions) stored on one or more non-transitory computer-readable and / or machine-readable media. As used herein, the terms non-transitory computer-readable medium, non-transitory computer-readable storage medium, non-transitory machine-readable medium, and / or non-transitory machine-readable storage medium are expressly defined to include any type of computer-readable storage device and / or storage disk, excluding propagation signals and transmission media. Examples of such non-transitory computer-readable medium, non-transitory computer-readable storage medium, non-transitory machine-readable medium, and / or non-transitory machine-readable storage medium include optical storage devices, magnetic storage devices, HDDs, flash memory, read-only memory (ROM), CDs, DVDs, caches, any type of RAM, registers, and / or any other storage device or storage disk in which information is stored for any duration (e.g., extended time period, permanent, transient, temporary buffering, and / or cache of information). As used herein, the terms "non-transitory computer-readable storage device" and "non-transitory machine-readable storage device" are defined to include any physical (mechanical, magnetic, and / or electrical) hardware for retaining information for a period of time, excluding the propagation of signals and transmission media. Examples of non-transitory computer-readable storage devices and / or non-transitory machine-readable storage devices include any type of random access memory, any type of read-only memory, solid-state memory, flash memory, optical disk, disk drive, and / or redundant array of independent disks (RAID) system. As used herein, the term "device" refers to a physical structure, such as mechanical and / or electrical equipment, hardware, and / or circuitry, which may or may not be configured by computer-readable instructions, machine-readable instructions, etc., and / or be manufactured to execute computer-readable instructions, machine-readable instructions, etc.

[0062] "Comprising" and "including" (and all their forms and tenses) are used herein as open-ended terms. Therefore, whenever a claim uses any form of "comprising" or "including" (e.g., including, containing, having, containing, having, etc.) as a preamble or within any kind of claim statement, it should be understood that additional elements, terms, etc., may be present that do not fall outside the scope of the corresponding claim or statement. As used herein, when the phrase "at least" is used as a transitional term, for example, in the preamble of a claim, it is open-ended in the same way as the terms "comprising" and "including" are open-ended. The term "and / or," when used, for example, in the form of A, B, and / or C, refers to any combination or subset of A, B, and C, such as: (1) A alone, (2) B alone, (3) C alone, (4) A and B, (5) A and C, (6) B and C, or (7) A and B and C. When used in the context of describing a structure, component, item, object, and / or thing, the phrase “at least one of A and B” is intended to refer to an implementation that includes any one of the following: (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, when used in the context of describing a structure, component, item, object, and / or thing, the phrase “at least one of A or B” is intended to refer to an implementation that includes any one of the following: (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. When used in the context of describing the execution or operation of a process, instruction, action, activity, and / or step, the phrase “at least one of A and B” is intended to refer to an implementation that includes any one of the following: (1) at least one A, (2) at least one B, or (3) at least one A and at least one B. Similarly, as used in the context of describing the execution or operation of a process, instruction, action, activity and / or step, the phrase “at least one of A or B” is intended to refer to an implementation that includes any one of: (1) at least one A, (2) at least one B, or (3) any one of at least one A and at least one B.

[0063] As used herein, singular references (e.g., “a,” “an,” “first,” “second,” etc.) do not exclude plural. As used herein, the term “an” or “a” refers to one or more of the same object. The terms “a” (or “an”), “one or more,” and “at least one” are used interchangeably herein. Furthermore, although listed separately, multiple means, elements, or actions may be implemented by, for example, the same entity or object. Additionally, although individual features may be included in different examples or claims, these features may be combined, and inclusion in different examples or claims does not imply that the combination of features is infeasible and / or disadvantageous.

[0064] Figure 3and 4 It is a flowchart representing example machine-readable instructions and / or example operations 300, which can be executed, illustrated, and / or performed by programmable circuitry to verify the results of nucleic acid amplification reactions. Figure 3 Example machine-readable instructions and / or example operations 300 include interface circuitry 102 accessing fluorescence signal data (box 302). Signal processing circuitry 104 excludes data from multiple loops (α) (box 304). For example, data from multiple initial loops is excluded from further analysis to avoid using inaccurate data that may include initial transient signal anomalies. In some examples, signal processing circuitry 104 creates a dataset according to Equation 2.

[0065] The computing circuit 106 calculates the intercycle difference in fluorescence amplitude between consecutive cycles (box 306). For example, the computing circuit 106 creates a dataset according to Equation 3. The computing circuit 106 identifies the final amplitude of the last cycle in the cycle (box 308) and the minimum amplitude of the cycle (box 310). The computing circuit 106 calculates the sum of the differences determined in box 306 (e.g., total distance) (box 312). For example, the computing circuit 106 calculates the sum according to Equation 5. The computing circuit 106 calculates the distance (e.g., upward distance) as the difference between the final amplitude and the minimum amplitude (box 314). For example, the computing circuit 106 calculates the distance according to Equation 6. The computing circuit 106 determines the ratio of the sum to the distance (e.g., total distance ratio) (box 316). For example, the computing circuit 106 determines the ratio according to Equation 7.

[0066] Evaluation circuit 108 compares the ratio to a threshold (e.g., total distance ratio threshold) (box 318). Evaluation circuit 108 determines whether the ratio meets the threshold (box 320). If and / or when evaluation circuit 108 determines that the ratio meets the threshold (box 320: yes), then evaluation circuit 108 validates the test result (box 322). For example, if and / or when evaluation circuit 108 determines that the ratio (e.g., total distance ratio) is less than a threshold ratio (e.g., threshold-total distance ratio), evaluation circuit 108 verifies the result of the nucleic acid amplification reaction (i.e., indicates or confirms the result as a true positive).

[0067] If and / or when evaluation circuit 108 determines that the ratio does not meet a threshold (box 320: No), then evaluation circuit 108 invalidates the test result (box 324). For example, if and / or when evaluation circuit 108 determines that the ratio (e.g., the total distance ratio) is greater than a threshold ratio (e.g., the threshold-total distance ratio), evaluation circuit 108 invalidates the result of the nucleic acid amplification reaction (i.e., indicates or determines the result as a false positive). After evaluation circuit 108 has made the result valid (box 322) or invalid (box 324), example operation 300 ends.

[0068] Figure 4Example machine-readable instructions and / or example operations 400 include interface circuitry 102 accessing fluorescence signal data (box 402). Signal processing circuitry 104 excludes data from multiple loops (α) (box 404). For example, data from multiple initial loops is excluded from further analysis to avoid using inaccurate data that may include initial transient signal anomalies. In some examples, signal processing circuitry 104 creates a dataset according to Equation 2.

[0069] The computing circuit 106 calculates the intercycle difference in fluorescence amplitude between consecutive cycles (box 406). For example, the computing circuit 106 creates a dataset according to Equation 3. The computing circuit 106 sorts the differences from high to low (box 408). For example, the computing circuit 106 creates a dataset according to Equation 4.

[0070] The calculation circuit 106 identifies the first maximum difference in amplitude (box 410). In this example, the first maximum amplitude difference is the largest amplitude difference among the amplitude differences calculated in box 406. The calculation circuit 106 also identifies the second maximum difference in amplitude (box 412).

[0071] The result verification circuit 100 determines whether the validity check operation is performed for the maximum Δ validity check or the second maximum Δ validity check (box 414). In some examples, there is no determination of the type of validity check. Instead, operation 400 continues to perform either the maximum Δ validity check or the second maximum Δ validity check, regardless of the element used in the other of the maximum Δ validity check or the second maximum Δ validity check.

[0072] If operation 400 is for a maximum Δ validity check (box 414: LDR), then calculation circuit 106 calculates a first ratio of the first maximum difference to the second maximum difference (box 416). For example, calculation circuit 106 calculates the maximum Δ ratio according to Equation 8.

[0073] Evaluation circuit 108 compares the first ratio with a first threshold (e.g., the maximum threshold Δ ratio) (box 418). Evaluation circuit 108 determines whether the first ratio meets the first threshold (box 420). If and / or when evaluation circuit 108 determines that the first ratio meets the first threshold (box 420: Yes), then evaluation circuit 108 validates the test result (box 422). For example, if and / or when evaluation circuit 108 determines that the first ratio (e.g., the maximum Δ ratio) is less than the first threshold ratio (e.g., the maximum threshold Δ ratio), evaluation circuit 108 validates the result of the nucleic acid amplification reaction (i.e., indicates or confirms a true positive result).

[0074] If and / or when evaluation circuit 108 determines that the first ratio does not meet the first threshold (box 420: No), then evaluation circuit 108 invalidates the test result (box 424). For example, if and / or when evaluation circuit 108 determines that the first ratio (e.g., the maximum Δ ratio) is greater than the first threshold ratio (e.g., the threshold maximum Δ ratio), evaluation circuit 108 invalidates the result of the nucleic acid amplification reaction (i.e., indicates or determines the result as a false positive). After evaluation circuit 108 has made the result valid (box 422) or invalid (box 424), example operation 300 ends.

[0075] If operation 400 is for the second largest Δ validity check (box 414: 2LDR), then computation circuit 106 identifies the third largest difference in magnitude (box 426). For example, computation circuit 106 identifies the third largest magnitude difference based on the sorted dataset in box 408.

[0076] The calculation circuit 106 calculates a second ratio between the second largest difference and the third largest difference (box 428). For example, the calculation circuit 106 calculates the maximum Δ ratio according to Equation 9. The evaluation circuit 108 compares the second ratio with a second threshold (e.g., the threshold second largest Δ ratio) (box 430). The evaluation circuit 108 determines whether the second ratio meets the second threshold (box 432). If and / or when the evaluation circuit 108 determines that the second ratio meets the second threshold (box 432: yes), the evaluation circuit 108 validates the test result (box 422). For example, if and / or when the evaluation circuit 108 determines that the second ratio (e.g., the second largest Δ ratio) is less than the second threshold ratio (e.g., the threshold second largest Δ ratio), the evaluation circuit 108 validates the result of the nucleic acid amplification reaction (i.e., indicates or confirms a true positive result).

[0077] If and / or when evaluation circuit 108 determines that the second ratio does not meet the second threshold (box 432: No), then evaluation circuit 108 invalidates the test result (box 424). For example, if and / or when evaluation circuit 108 determines that the second ratio (e.g., the second largest Δ ratio) is greater than the second threshold ratio (e.g., the threshold second largest Δ ratio), evaluation circuit 108 invalidates the result of the nucleic acid amplification reaction (i.e., indicates or determines the result as a false positive). After evaluation circuit 108 has made the result valid (box 422) or invalid (box 424), example operation 300 ends.

[0078] Figure 5 It is constructed for execution and / or instantiation. Figure 3 and Figure 4 Example machine-readable instructions and / or example operations to implement Figure 1The result verification circuit 100 is an example block diagram of a programmable circuit platform 500. The programmable circuit platform 500 can be, for example, a server, personal computer, workstation, self-learning machine (e.g., neural network), mobile device (e.g., cellular phone, smartphone, such as iPad). TM Tablet computers, personal digital assistants (PDAs), internet devices, headsets (e.g., augmented reality (AR) headsets, virtual reality (VR) headsets, etc.) or other wearable devices, or any other type of computing and / or electronic device.

[0079] The programmable circuit platform 500 illustrated includes a programmable circuit 512. The programmable circuit 512 illustrated is hardware. For example, the programmable circuit 512 can be implemented by one or more integrated circuits, logic circuits, FPGAs, microprocessors, CPUs, GPUs, DSPs, and / or microcontrollers from any desired family or manufacturer. The programmable circuit 512 can be implemented by one or more semiconductor-based (e.g., silicon-based) devices. In this example, the programmable circuit 512 implements an example interface circuit 102, an example signal processing circuit 104, an example computing circuit 106, an example evaluation circuit 110, and / or more generally, an example result verification circuit 100.

[0080] The programmable circuit 512 of the illustrated example includes local memory 513 (e.g., cache, registers, etc.). The programmable circuit 512 of the illustrated example communicates via bus 518 with main memories 514, 516, including volatile memory 514 and non-volatile memory 516. Volatile memory 514 may be implemented using synchronous dynamic random access memory (SDRAM), dynamic random access memory (DRAM), RAMBUS® dynamic random access memory (RDRAM®), and / or any other type of RAM device. Non-volatile memory 516 may be implemented using flash memory and / or any other desired type of memory device. Access to the main memories 514, 516 of the illustrated example is controlled by a memory controller 517. In some examples, the memory controller 517 may be implemented using one or more integrated circuits, logic circuitry, a microcontroller from any desired series or manufacturer, or any other type of circuitry for managing the flow of data to and from the main memories 514, 516.

[0081] The programmable circuit platform 500 shown in the example also includes interface circuitry 520. Interface circuitry 520 can be implemented by hardware according to any type of interface standard, such as an Ethernet interface, a Universal Serial Bus (USB) interface, a Bluetooth® interface, a Near Field Communication (NFC) interface, a Peripheral Component Interconnect (PCI) interface, and / or a Peripheral Component Interconnect Fast (PCIe) interface.

[0082] In the example shown, one or more input devices 522 are connected to interface circuitry 520. Input devices 522 allow users (e.g., human users, machine users, etc.) to input data and / or commands into programmable circuitry 512. Input devices 522 can be implemented as, for example, audio sensors, microphones, cameras (still or video), keyboards, buttons, mice, touchscreens, trackpads, trackballs, pointing devices, and / or speech recognition systems.

[0083] One or more output devices 524 are also connected to the interface circuitry 520 of the illustrated example. The output devices 524 may be implemented, for example, by display devices (e.g., light-emitting diode (LED), organic light-emitting diode (OLED), liquid crystal display (LCD), cathode ray tube (CRT) display, in-place switching (IPS) display, touchscreen, etc.), haptic output devices, printers, and / or speakers. Therefore, the interface circuitry 520 of the illustrated example typically includes a graphics driver card, a graphics driver chip, and / or graphics processor circuitry, such as a GPU.

[0084] The interface circuit 520 of the example shown also includes communication devices such as transmitters, receivers, transceivers, modems, residential gateways, wireless access points, and / or network interfaces to facilitate the exchange of data with external machines (e.g., any kind of computing device) via network 526. Communication may be via, for example, Ethernet connections, digital subscriber line (DSL) connections, telephone line connections, coaxial cable systems, satellite systems, site-line wireless systems, cellular telephone systems, optical connections, etc.

[0085] The programmable circuit platform 500 illustrated also includes one or more mass storage disks or devices 528 for storing firmware, software, and / or data. Examples of such mass storage disks or devices 528 include magnetic storage devices (e.g., floppy disks, drives, HDDs, etc.), optical storage devices (e.g., Blu-ray discs, CDs, DVDs, etc.), RAID systems, and / or solid-state storage disks or devices, such as flash memory devices and / or SSDs.

[0086] It can be by Figure 3 and Figure 4 The machine-readable instructions 532 implemented by the machine-readable instructions can be stored in mass storage device 528, volatile memory 514, non-volatile memory 516 and / or on at least one removable non-transitory computer-readable storage medium such as CD or DVD.

[0087] exist Figure 6 The diagram shows the method for using, such as Figure 5This is a block diagram of an example software distribution platform 605 that distributes software with example machine-readable instructions 532 to other hardware devices (e.g., hardware devices owned and / or operated by a third party who is the owner and / or operator of the software distribution platform). The example software distribution platform 605 can be implemented by any computer server, data facility, cloud service, etc., capable of storing software and transferring it to other computing devices. The third party can be a customer of the entity that owns and / or operates the software distribution platform 605. For example, the entity that owns and / or operates the software distribution platform 605 can be, for example, a client of, the entity that owns and / or operates the software distribution platform 605. Figure 5 The example machine-readable instruction 532 pertains to the software developer, seller, and / or licensor. A third party may be a consumer, user, retailer, OEM, etc., who purchases and / or licenses the software for use and / or resells and / or sublicenses. In the illustrated example, the software distribution platform 605 includes one or more servers and one or more storage devices. The storage devices store the machine-readable instruction 532, which may correspond to... Figure 3 and 4 The example machine-readable instructions are as described above. One or more servers of the example software distribution platform 605 communicate with the example network 610, which may correspond to the Internet and / or any one or more of the example networks described above. In some examples, one or more servers send software to a requesting party as part of a commercial transaction in response to a request. One or more servers of the software distribution platform and / or a third-party payment entity may process payments for the delivery, sale, and / or licensing of the software. The servers enable purchasers and / or licensors to download machine-readable instructions 532 from the software distribution platform 605. For example, instructions that can correspond to... Figure 3 and 4 The software, containing example machine-readable instructions, is downloaded to an example programmable circuit platform 500, which executes the machine-readable instructions 532 to implement the result verification circuit 100. In some examples, one or more servers of the software distribution platform 605 cyclically distribute software (e.g., ...) to... Figure 5 Example machine-readable instruction 532) provides, delivers, and / or forces updates to ensure that improvements, patches, updates, etc., are distributed and applied to the software at the end-user device. Although referred to above as software, distributed “software” can alternatively be firmware.

[0088] Unless otherwise specifically stated, descriptors such as “first,” “second,” and “third” are used herein without indicating any meaning of priority, physical order, arrangement in a list, and / or any kind of sorting, but merely as labels and / or arbitrary names to distinguish elements for the purpose of understanding the disclosed examples. In some examples, the descriptor “first” may be used to refer to an element in the detailed description, while the same element may be referred to in the claims by different descriptors such as “second” or “third.” In such cases, it should be understood that such descriptors are only used to clearly identify those elements in the context of the discussion (e.g., in the claims), where elements may, for example, share the same name.

[0089] As used herein, the phrase “communication (in)” includes its variations, covering direct communication and / or indirect communication via one or more intermediate components, and does not require direct physical (e.g., wired) communication and / or continuous communication, but additionally includes selective communication at cyclic intervals, scheduling intervals, non-cyclic intervals and / or one-off events.

[0090] As used herein, “programmable circuit” is defined to include: (i) one or more application-specific circuits (e.g., application-specific integrated circuits (ASICs)) configured to perform specific operations and including one or more semiconductor-based logic devices (e.g., electrical hardware implemented by one or more transistors), and / or (ii) one or more general-purpose semiconductor-based circuits programmable with instructions to perform specific functions and / or operations and including one or more semiconductor-based logic devices (e.g., electrical hardware implemented by one or more transistors). Examples of programmable circuits include programmable microprocessors, such as a central processing unit (CPU) capable of executing a first instruction to perform one or more operations and / or functions, a field-programmable gate array (FPGA) that can be programmed with second instructions to executor one or more operations and / or functions corresponding to the first instruction by configuration and / or structuring of an FPGA, a graphics processing unit (GPU) capable of executing a first instruction to perform one or more operations and / or functions, a digital signal processor (DSP) capable of executing a first instruction to perform one or more operations and / or functions, an XPU, a network processing unit (NPU) capable of executing a first instruction to perform one or more operations and / or functions, one or more microcontrollers, and / or integrated circuits such as application-specific integrated circuits (ASICs). For example, an XPU can be implemented by a heterogeneous computing system that includes multiple types of programmable circuits (e.g., one or more FPGAs, one or more CPUs, one or more GPUs, one or more NPUs, one or more DSPs, etc., and / or any combination thereof) and coordination technology (e.g., an application programming interface (API)) that can distribute computing tasks to any of the multiple types of programmable circuits that are suitable and available to perform the computing task.

[0091] As used herein, an integrated circuit / circuit is defined as one or more semiconductor packages containing one or more circuit elements, such as transistors, capacitors, inductors, resistors, current paths, diodes, etc. For example, an integrated circuit can be implemented as one or more of an ASIC, FPGA, chip, microchip, programmable circuit, semiconductor substrate coupling multiple circuit elements, system-on-a-chip (SoC), etc.

[0092] As understood above, example systems, apparatus, articles, and methods for identifying false positive results in nucleic acid amplification reactions due to fluorescence signal noise have been disclosed. Example total distance ratio, example maximum Δ ratio, and example second maximum Δ ratio validity checks can be used to prevent false positive PCR or other nucleic acid amplification test results due to fluorescence signal noise. These examples prevent noise-related false positives while keeping the fluorescence channel (which will be used by the reference dye in existing methods) open, which facilitates greater reproducibility. Furthermore, the examples disclosed herein avoid reducing the sensitivity of PCR assays because there is no need for overly restrictive data reduction parameters (e.g., excessively increasing the cycle threshold used to identify positive results).

[0093] Example systems, apparatuses, articles, and methods for verifying the results of nucleic acid amplification reaction tests are disclosed. Example 1 includes an apparatus for verifying the results of a nucleic acid amplification reaction test, the apparatus comprising: interface circuitry; machine-readable instructions; and programmable circuitry for instantiating or executing at least one of the machine-readable instructions to: calculate amplitude differences between successive cycles of a plurality of cycles of fluorescence signals obtained from the test; determine a sum of amplitude differences between successive cycles; identify a final amplitude at the last cycle of the cycles; identify a minimum amplitude of the plurality of cycles; determine a distance as the difference between the final amplitude and the minimum amplitude; determine a ratio of the sum to the distance; and verify the test results based on the ratio.

[0094] Example 2 includes the device of Example 1, wherein the programmable circuitry excludes a certain number of loops from a plurality of loops in a test, the certain number of loops being the loop at the start of the test.

[0095] Example 3 includes the device of Example 2, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0096] Example 4 includes a device of any of Examples 1-3, wherein the programmable circuitry compares the ratio to a threshold and makes the test result valid when the ratio meets the threshold.

[0097] Example 5 includes the device of Example 4, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0098] Example 6 includes an apparatus for verifying nucleic acid amplification reaction test results, the apparatus comprising: interface circuitry; machine-readable instructions; and programmable circuitry for instantiating or executing at least one of the machine-readable instructions to: calculate amplitude differences between successive cycles of a plurality of cycles of fluorescence signals obtained from the test; identify a first amplitude difference; identify a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determine a ratio of the first amplitude difference to the second amplitude difference; and verify the test results based on the ratio.

[0099] Example 7 includes the device of Example 6, wherein the first amplitude difference is the largest amplitude difference among amplitude differences, and the second amplitude difference is the second largest amplitude difference among amplitude differences.

[0100] Example 8 includes a device of either Example 6 or 7, wherein the first amplitude difference is the second largest amplitude difference among amplitude differences, and the second amplitude difference is the third largest amplitude difference among amplitude differences.

[0101] Example 9 includes a device of any one of Examples 6-8, wherein the programmable circuitry excludes a certain number of loops from the test from a plurality of loops, the certain number of loops being...

[0102] Example 10 includes the device of Example 9, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0103] Example 11 includes a device of any of Examples 6-10, wherein a programmable circuit compares the ratio to a threshold and makes the result of the test valid when the ratio meets the threshold.

[0104] Example 12 includes the device of Example 11, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0105] Example 13 includes a machine-readable storage medium comprising instructions such that a programmable circuitry at least: calculates amplitude differences between successive cycles of a plurality of fluorescence signals obtained from a nucleic acid amplification reaction assay; determines a sum of amplitude differences between successive cycles; identifies a final amplitude at the last cycle of the assay; identifies a minimum amplitude of the plurality of cycles; determines a distance as the difference between the final amplitude and the minimum amplitude; determines a ratio of the sum to the distance; and verifies the result of the assay based on the ratio.

[0106] Example 14 includes the machine-readable storage medium of Example 13, wherein instructions cause programmable circuitry to exclude a number of cycles from a plurality of cycles in a test, the number of cycles being the cycle at the start of the test.

[0107] Example 15 includes the machine-readable storage medium of Example 14, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0108] Example 16 includes a machine-readable storage medium as described in any one of Examples 13-15, wherein the instructions cause the programmable circuitry to compare the ratio with a threshold, and to make the result of the test valid when the ratio meets the threshold.

[0109] Example 17 includes the machine-readable storage medium of Example 16, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0110] Example 18 includes a machine-readable storage medium comprising instructions such that a programmable circuitry at least: calculates amplitude differences between successive cycles of a plurality of cycles of a fluorescence signal obtained from a nucleic acid amplification reaction test; identifies a first amplitude difference; identifies a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determines a ratio of the first amplitude difference to the second amplitude difference; and verifies the result of the test based on the ratio.

[0111] Example 19 includes the machine-readable storage medium of Example 18, wherein the first amplitude difference is the largest amplitude difference among amplitude differences, and the second amplitude difference is the second largest amplitude difference among amplitude differences.

[0112] Example 20 includes a machine-readable storage medium as described in any of Examples 18 or 19, wherein the first amplitude difference is the second largest amplitude difference among the amplitude differences, and the second amplitude difference is the third largest amplitude difference among the amplitude differences.

[0113] Example 21 includes a machine-readable storage medium as described in any one of Examples 18-20, wherein the instructions cause the programmable circuitry to exclude a certain number of cycles in the test from the plurality of cycles, the certain number of cycles being the cycle at the start of the test.

[0114] Example 22 includes the machine-readable storage medium of Example 21, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0115] Example 23 includes any one of Examples 18-22, a machine-readable storage medium, wherein the instructions cause the programmable circuit to compare the ratio with a threshold, and to make the result of the test valid when the ratio meets the threshold.

[0116] Example 24 includes the machine-readable storage medium of Example 23, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0117] Example 25 includes a method for verifying the results of a nucleic acid amplification reaction test, the method comprising: calculating amplitude differences between successive cycles of a plurality of cycles of fluorescence signal obtained from the test; determining a sum of amplitude differences between successive cycles; identifying a final amplitude at the last cycle in the cycle; identifying a minimum amplitude of the plurality of cycles; determining a distance as the difference between the final amplitude and the minimum amplitude; determining a ratio of the sum to the distance; and verifying the results of the test based on the ratio. One or more elements or steps of this method and / or other methods disclosed herein can be performed by executing instructions using a processor, processor circuitry, programmable circuitry, and / or processor circuitry.

[0118] Example 26 includes the method of Example 25, and further includes: excluding a certain number of loops from the plurality of loops in the test, the certain number of loops being the loops at the start of the test.

[0119] Example 27 includes the method of Example 26, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0120] Example 28 includes the method of any one of Examples 25-27, further comprising: comparing the ratio to a threshold, and validating the result of the test when the ratio satisfies the threshold.

[0121] Example 29 includes the method of Example 28, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0122] Example 30 includes a method for verifying the results of a nucleic acid amplification reaction test, the method comprising: calculating amplitude differences between successive cycles in a plurality of cycles of a fluorescence signal obtained from the test; identifying a first amplitude difference; identifying a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determining a ratio of the first amplitude difference to the second amplitude difference; and verifying the results of the test based on the ratio.

[0123] Example 31 includes the method of Example 30, wherein the first magnitude difference is the largest magnitude difference among magnitude differences, and the second magnitude difference is the second largest magnitude difference among magnitude differences.

[0124] Example 32 includes a method of either Example 30 or 31, wherein the first magnitude difference is the second largest magnitude difference among magnitude differences, and the second magnitude difference is the third largest magnitude difference among magnitude differences.

[0125] Example 33 includes the method of any one of Examples 30-32, and further includes: excluding a certain number of loops from the plurality of loops in the test, the certain number of loops being the loops at the start of the test.

[0126] Example 34 includes the method of Example 33, wherein the quantity is based on the type of target DNA or RNA used for testing.

[0127] Example 35 includes the method of any one of Examples 30-34, further comprising: comparing the ratio to a threshold, and validating the result of the test when the ratio satisfies the threshold.

[0128] Example 36 includes the method of Example 35, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0129] Example 37 includes one or more servers for distributing a first instruction over a network, the one or more servers comprising: at least one storage device including the second instruction; and at least one processor for executing the second instruction to transmit the first instruction over the network, wherein, when executing the first instruction, the device at least: calculates amplitude differences between successive cycles of a plurality of cycles of fluorescence signals obtained from a nucleic acid amplification reaction test; determines a sum of amplitude differences between successive cycles; identifies a final amplitude at the last cycle in the cycle; identifies a minimum amplitude of the plurality of cycles; determines a distance as the difference between the final amplitude and the minimum amplitude; determines a ratio of the sum to the distance; and verifies the result of the test based on the ratio.

[0130] Example 38 includes one or more servers of Example 37, wherein a first instruction causes the device to exclude a certain number of loops in the test from a plurality of loops, the certain number of loops being the loop at the start of the test.

[0131] Example 39 includes one or more servers of Example 38, wherein the number is based on the type of target DNA or RNA used for testing.

[0132] Example 40 includes one or more servers of any of the examples 37-39, wherein a first instruction causes the device to compare a ratio with a threshold, and makes the result of the test valid when the ratio meets the threshold.

[0133] Example 41 includes one or more servers of Example 40, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0134] Example 42 includes one or more servers for distributing a first instruction over a network, the one or more servers comprising: at least one storage device including the second instruction; and at least one processor for executing the second instruction to transmit the first instruction over the network, wherein, when executing the first instruction, the device at least: calculates amplitude differences between successive cycles of a plurality of cycles of fluorescence signals obtained from a nucleic acid amplification reaction test; identifies a first amplitude difference; identifies a second amplitude difference, the second amplitude difference being lower than the first amplitude difference; determines a ratio of the first amplitude difference to the second amplitude difference; and verifies the result of the test based on the ratio.

[0135] Example 43 includes one or more servers of Example 42, wherein the first amplitude difference is the largest amplitude difference among the amplitude differences, and the second amplitude difference is the second largest amplitude difference among the amplitude differences.

[0136] Example 44 includes one or more servers of any one of Examples 42 or 43, wherein the first amplitude difference is the second largest amplitude difference among amplitude differences, and the second amplitude difference is the third largest amplitude difference among amplitude differences.

[0137] Example 45 includes one or more servers of any of Examples 42-44, wherein a first instruction causes the device to exclude a certain number of loops in the test from a plurality of loops, the certain number of loops being the loop at the start of the test.

[0138] Example 46 includes one or more servers of Example 45, wherein the number is based on the type of target DNA or RNA used for testing.

[0139] Example 47 includes one or more servers of any of Examples 42-46, wherein a first instruction causes the device to compare a ratio with a threshold, and makes the result of the test valid when the ratio meets the threshold.

[0140] Example 48 includes one or more servers of Example 47, wherein the threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

[0141] Example 49 includes an apparatus comprising means for performing the method as described in any of the preceding claims.

[0142] Example 50 includes a machine-readable storage device comprising machine-readable instructions that, when executed, implement the method as described in any of the preceding claims or the apparatus as described in any of the preceding claims.

[0143] The following claims are incorporated herein by reference in this detailed description. Although certain example systems, apparatuses, articles of manufacture, and methods are disclosed herein, the scope of this patent is not limited thereto. Rather, this patent covers all systems, apparatuses, articles of manufacture, and methods that fall fully within the scope of the claims of this patent.

Claims

1. An apparatus for verifying the results of a nucleic acid amplification reaction test, the apparatus comprising: Interface circuit; Machine-readable instructions; as well as Programmable circuitry for instantiating or executing at least one of the machine-readable instructions to: Calculate the amplitude difference between consecutive cycles of a plurality of cycles in the fluorescence signal obtained from the test; Determine the sum of the amplitude differences between consecutive cycles; Identify the final amplitude at the last loop in the loop; Identify the minimum amplitude of the multiple cycles; The distance is defined as the difference between the final amplitude and the minimum amplitude. Determine the ratio of the sum to the distance; as well as The results of the test are verified based on the ratio.

2. The device according to claim 1, wherein, The programmable circuit excludes a certain number of loops from the plurality of loops in the test, the certain number of loops being the loop at the start of the test.

3. The device according to claim 2, wherein, The quantity is based on the type of target DNA or RNA used for the test.

4. The device according to any one of claims 1-3, wherein, The programmable circuit compares the ratio to a threshold and makes the test result valid when the ratio meets the threshold.

5. The device according to claim 4, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

6. An apparatus for verifying the results of a nucleic acid amplification reaction test, the apparatus comprising: Interface circuit; Machine-readable instructions; as well as Programmable circuitry for instantiating or executing at least one of the machine-readable instructions to: Calculate the amplitude difference between consecutive cycles in a plurality of cycles of the fluorescence signal obtained from the test; Identify the first amplitude difference; Identify a second amplitude difference, which is lower than the first amplitude difference; Determine the ratio of the first amplitude difference to the second amplitude difference; as well as The results of the test are verified based on the ratio.

7. The device according to claim 6, wherein, The first amplitude difference is the largest amplitude difference among the amplitude differences, and the second amplitude difference is the second largest amplitude difference among the amplitude differences.

8. The device according to claim 6, wherein, The first amplitude difference is the second largest amplitude difference among the amplitude differences, and the second amplitude difference is the third largest amplitude difference among the amplitude differences.

9. The device according to any one of claims 6-8, wherein, The programmable circuitry is used to exclude a certain number of cycles from the plurality of cycles in the test, the certain number of cycles being the cycle at the start of the test.

10. The device according to claim 9, wherein, The quantity is based on the type of target DNA or RNA used for the test.

11. The device according to any one of claims 6-10, wherein, The programmable circuit compares the ratio to a threshold and makes the test result valid when the ratio meets the threshold.

12. The device according to claim 11, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

13. A machine-readable storage medium comprising instructions to cause a programmable circuit to perform at least the following operations: Calculate the amplitude difference between consecutive cycles in the fluorescence signal obtained from the nucleic acid amplification reaction test; Determine the sum of the amplitude differences between consecutive cycles; Identify the final amplitude at the last loop in the loop; Identify the minimum amplitude of the multiple cycles; The distance is defined as the difference between the final amplitude and the minimum amplitude. Determine the ratio of the sum to the distance; as well as The results of the test are verified based on the ratio.

14. The machine-readable storage medium according to claim 13, wherein, The instruction causes the programmable circuit to exclude a certain number of loops from the plurality of loops in the test, the certain number of loops being the loop at the start of the test.

15. The machine-readable storage medium of claim 14, wherein, The quantity is based on the type of target DNA or RNA used for the test.

16. The machine-readable storage medium according to any one of claims 13-15, wherein, The instructions cause the programmable circuit to compare the ratio with a threshold, and to make the test result valid when the ratio meets the threshold.

17. The machine-readable storage medium of claim 16, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

18. A machine-readable storage medium comprising instructions to cause a programmable circuit to perform at least the following operations: Calculate the amplitude difference between consecutive cycles of the fluorescence signal obtained from the nucleic acid amplification reaction test; Identify the first amplitude difference; Identify a second amplitude difference, which is lower than the first amplitude difference; Determine the ratio of the first amplitude difference to the second amplitude difference; as well as The results of the test are verified based on the ratio.

19. The machine-readable storage medium according to claim 18, wherein, The first amplitude difference is the largest amplitude difference among the amplitude differences, and the second amplitude difference is the second largest amplitude difference among the amplitude differences.

20. The machine-readable storage medium of claim 18, wherein, The first amplitude difference is the second largest amplitude difference among the amplitude differences, and the second amplitude difference is the third largest amplitude difference among the amplitude differences.

21. The machine-readable storage medium according to any one of claims 18-20, wherein, The instruction causes the programmable circuit to exclude a certain number of cycles from the plurality of cycles in the test, the certain number of cycles being the cycle at the start of the test.

22. The machine-readable storage medium of claim 21, wherein, The quantity is based on the type of target DNA or RNA used for the test.

23. The machine-readable storage medium according to any one of claims 18-22, wherein, The instructions cause the programmable circuit to compare the ratio with a threshold, and to make the test result valid when the ratio meets the threshold.

24. The machine-readable storage medium of claim 23, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

25. A method for verifying the results of a nucleic acid amplification reaction test, the method comprising: Calculate the amplitude difference between consecutive cycles of a plurality of cycles in the fluorescence signal obtained from the test; Determine the sum of the amplitude differences between consecutive cycles; Identify the final amplitude at the last loop in the loop; Identify the minimum amplitude of the multiple cycles; The distance is defined as the difference between the final amplitude and the minimum amplitude. Determine the ratio of the sum to the distance; as well as The results of the test are verified based on the ratio.

26. The method of claim 25, further comprising: Exclude a certain number of loops from the plurality of loops in the test, the certain number of loops being the loops that started at the beginning of the test.

27. The method according to claim 26, wherein, The quantity is based on the type of target DNA or RNA used for testing.

28. The method according to any one of claims 25-27, further comprising: The ratio is compared to a threshold, and the result of the test is valid when the ratio meets the threshold.

29. The method according to claim 28, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

30. A method for verifying the results of a nucleic acid amplification reaction test, the method comprising: Calculate the amplitude difference between consecutive cycles in a plurality of cycles of the fluorescence signal obtained from the test; Identify the first amplitude difference; Identify a second amplitude difference, which is lower than the first amplitude difference; Determine the ratio of the first amplitude difference to the second amplitude difference; as well as The results of the test are verified based on the ratio.

31. The method according to claim 30, wherein, The first amplitude difference is the largest amplitude difference among the amplitude differences, and the second amplitude difference is the second largest amplitude difference among the amplitude differences.

32. The method according to claim 30, wherein, The first amplitude difference is the second largest amplitude difference among the amplitude differences, and the second amplitude difference is the third largest amplitude difference among the amplitude differences.

33. The method according to any one of claims 30-32, further comprising: Exclude a certain number of loops from the plurality of loops in the test, the certain number of loops being the loops that started at the beginning of the test.

34. The method according to claim 33, wherein, The quantity is based on the type of target DNA or RNA used for testing.

35. The method according to any one of claims 30-34, further comprising: The ratio is compared to a threshold, and the result of the test is valid when the ratio meets the threshold.

36. The method according to claim 35, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data with known false positive nucleic acid amplification reaction data.

37. One or more servers for distributing first instructions over a network, said one or more servers comprising: At least one storage device, including the second instruction; as well as At least one processor is configured to execute the second instruction to transmit the first instruction via the network, wherein the first instruction, when executed, causes the device to perform at least the following operations: Calculate the amplitude difference between consecutive cycles in the fluorescence signal obtained from the nucleic acid amplification reaction test; Determine the sum of the amplitude differences between consecutive cycles; Identify the final amplitude at the last loop in the loop; Identify the minimum amplitude of the multiple cycles; The distance is defined as the difference between the final amplitude and the minimum amplitude. Determine the ratio of the sum to the distance; as well as The results of the test are verified based on the ratio.

38. One or more servers according to claim 37, wherein, The first instruction causes the device to exclude a certain number of cycles from the plurality of cycles in the test, the certain number of cycles being the cycle at the start of the test.

39. One or more servers according to claim 38, wherein, The quantity is based on the type of target DNA or RNA used for the test.

40. One or more servers according to any one of claims 37-39, wherein, The first instruction causes the device to compare the ratio with a threshold, and makes the test result valid when the ratio meets the threshold.

41. One or more servers according to claim 40, wherein, The threshold is based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

42. One or more servers for distributing first instructions over a network, said one or more servers comprising: At least one storage device, including the second instruction; as well as At least one processor is configured to execute the second instruction to transmit the first instruction via the network, wherein the first instruction, when executed, causes the device to perform at least the following operations: Calculate the amplitude difference between consecutive cycles of the fluorescence signal obtained from the nucleic acid amplification reaction test; Identify the first amplitude difference; Identify a second amplitude difference, which is lower than the first amplitude difference; Determine the ratio of the first amplitude difference to the second amplitude difference; as well as The results of the test are verified based on the ratio.

43. One or more servers according to claim 42, wherein, The first amplitude difference is the largest amplitude difference among the amplitude differences, and the second amplitude difference is the second largest amplitude difference among the amplitude differences.

44. One or more servers according to claim 42, wherein, The first amplitude difference is the second largest amplitude difference among the amplitude differences, and the second amplitude difference is the third largest amplitude difference among the amplitude differences.

45. One or more servers according to any one of claims 42-44, wherein, The first instruction causes the device to exclude a certain number of cycles from the plurality of cycles in the test, the certain number of cycles being the cycle number at the start of the test.

46. ​​One or more servers according to claim 45, wherein, The quantity is based on the type of target DNA or RNA used for the test.

47. One or more servers according to any one of claims 42-46, wherein, The first instruction causes the device to compare the ratio with a threshold, and makes the test result valid when the ratio meets the threshold.

48. One or more servers according to claim 47, wherein, The threshold is determined based on a comparison of known positive nucleic acid amplification reaction data and known false positive nucleic acid amplification reaction data.

49. An apparatus comprising means for performing the method as described in any of the preceding claims.

50. A machine-readable storage device comprising machine-readable instructions that, when executed, implement the method or apparatus as described in any of the preceding claims.

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