Chromatography-mass spectrometry combined endocrine disorder typing system for gynecological tuberculosis

Abstract

The present application relates to the technical field of chromatographic analysis detection, in particular to a gynecological tuberculosis endocrine disorder typing system based on chromatography-mass spectrometry. The system comprises a memory and a processor, and the processor executes a computer program stored in the memory to realize the following steps: evaluating the compound identification accuracy according to the number of compounds in different reference samples in each specimen source, determining the sample weight of each specimen source in combination with the ideal effect of the specimen source and the proportion of the number of reference samples; evaluating the mixed similarity in combination with the retention time and response intensity of the compounds in the chromatographic data segment in each compound set; obtaining the correction weight by comprehensively considering the number of compounds, the mixed similarity and the sample weight of each compound set in each reference sample, and further determining the gynecological tuberculosis endocrine disorder typing. The present application overcomes the identification deviation problem caused by insufficient reference samples and similar compound structures, and improves the accuracy of gynecological tuberculosis endocrine disorder typing.

Description

Technical Field

[0001] This invention relates to the field of chromatographic analysis and detection technology, specifically to a gynecological tuberculosis endocrine disorder classification system using chromatography-mass spectrometry. Background Technology

[0002] Gynecological tuberculosis is a chronic inflammatory disease caused by Mycobacterium tuberculosis infecting the female reproductive system. It is usually a secondary infection, meaning that the pathogen comes from tuberculosis lesions in other parts of the body and is an endocrine disorder that spreads to the reproductive organs through the blood or lymphatic system.

[0003] In clinical manifestations, endocrine disorders in gynecological tuberculosis are mainly classified into three types: 1. Target organ failure type: Tuberculosis bacteria directly invade and destroy the fallopian tube / endometrium / ovarian structure, leading to damage to the basal layer of the endometrium, forming extensive scars and intrauterine adhesions, making the endometrium unable to respond to hormones secreted by the ovaries; 2. Ovarian dysfunction type: Pelvic tuberculosis causes the ovaries to be tightly wrapped and adhered, affecting their blood supply and normal follicle development; 3. Hypothalamic-pituitary-ovarian axis suppression type: As a chronic wasting disease, tuberculosis is accompanied by long-term low-grade fever, malnutrition, weight loss, and mental stress. These factors inhibit the hypothalamus from pulsatilely secreting gonadotropin-releasing hormone, leading to suppression of pituitary function. The three types mentioned above each have corresponding indicators for the manifestation of endocrine compounds. Current detection technologies typically collect patient sample solutions and use a chromatography-mass spectrometry (GC-MS) instrument to perform multi-layer physical separation of the sample solutions. The data analysis module built into the device displays the intensity of the compound components contained in the sample solution, providing data support for subsequent classification of endocrine disorders in gynecological tuberculosis patients.

[0004] However, in real-world scenarios, some compounds in a patient's sample solution may have similar physical structures (such as estradiol and estrone). During the analysis, the number of reference samples may be too small, making it impossible for the chromatography-mass spectrometry (GC-MS) instrument to completely separate these compounds. This can lead to the contents of other compounds being incorrectly identified as a certain compound index, resulting in significant distortion of the actual compound index. Summary of the Invention

[0005] To address the discrepancy between detected and actual compound values ​​in existing methods for classifying endocrine disorders in gynecological tuberculosis, this invention aims to provide a chromatography-mass spectrometry (GC-MS) system for classifying endocrine disorders in gynecological tuberculosis. The specific technical solution adopted is as follows:

[0006] This invention provides a gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry. The system includes a memory and a processor. The processor executes a computer program stored in the memory to perform the following steps:

[0007] Obtain reference specimens and test samples from different specimen sources in the historical gynecological tuberculosis testing process;

[0008] The compound identification accuracy of each sample source is evaluated based on the number of compounds in different reference standards within each sample source; the sample weight of each sample source is determined based on the compound identification accuracy, the ideal performance of each sample source, and the proportion of reference standards.

[0009] Compounds with similar structures in a reference standard constitute a set of compounds; the mixing similarity of each set of compounds is evaluated by combining the distribution of retention time and response intensity of each compound in the corresponding chromatographic data segment.

[0010] By combining the number of compounds in each compound set of each reference standard, the degree of mixing similarity, and the sample weight, the correction weight of each reference standard is obtained; based on the correction weight and the test sample, the endocrine disorder subtype of gynecological tuberculosis in the patient to be tested is determined.

[0011] Preferably, the evaluation of compound identification accuracy for each sample source based on the number of compounds in different reference standards from each sample source includes:

[0012] The ratio of the number of compounds in each reference standard in the candidate sample source to the total number of compounds in all reference standards in all sample sources is taken as the proportion of the number of compounds in each reference standard in the candidate sample source.

[0013] The compound identification accuracy of the candidate sample source is obtained by combining the proportion of compounds in all reference standards in the candidate sample source;

[0014] The candidate specimens can be from any specimen source.

[0015] Preferably, determining the sample weight for each sample source based on the compound identification accuracy, the ideal effect of each sample source, and the proportion of reference standards includes:

[0016] The ratio of the number of reference samples in the candidate specimen sources to the total number of reference samples in all specimen sources is taken as the proportion of the number of reference samples in the candidate specimen sources.

[0017] The recognition accuracy of compounds from all sample sources was sorted in descending order to obtain the recognition accuracy sequence; the sample source sequence was sorted in descending order of the ideal effect of all sample sources.

[0018] The sample weights of candidate sample sources are obtained based on the proportion of reference standards in the candidate sample sources, the order of the compound recognition accuracy of the candidate sample sources in the recognition accuracy sequence, and the order of the candidate sample sources in the sample source sequence.

[0019] Preferably, the step of obtaining the sample weight of a candidate sample source based on the proportion of reference standards in the candidate sample source, the order of the compound recognition accuracy of the candidate sample source in the recognition accuracy sequence, and the order of the candidate sample source in the sample source sequence includes:

[0020] Calculate the first ratio between the order of the candidate sample source in the recognition accuracy sequence and the number of species in the sample source, and the second ratio between the order of the candidate sample source in the sample source sequence and the number of species in the sample source, respectively.

[0021] The sample weight of a candidate specimen source is obtained based on the proportion of reference samples in the candidate specimen source, the first ratio, and the second ratio. The proportion of reference samples in the candidate specimen source is positively correlated with the sample weight, while the first ratio and the second ratio are both negatively correlated with the sample weight.

[0022] Preferably, the evaluation of the mixing similarity of each compound set by combining the distribution of retention time and response intensity of each compound in the corresponding chromatographic data segment includes:

[0023] For any set of compounds:

[0024] Calculate the first difference between the x-coordinate of the compound to be analyzed in the corresponding chromatographic data segment and the mean of the x-coordinates of all other compounds in the chromatographic data segment of any given compound set, and the second difference between the y-coordinate of the compound to be analyzed in the corresponding chromatographic data segment and the mean of the y-coordinates of all other compounds in the chromatographic data segment of any given compound set, wherein the compound to be analyzed is any compound in any given compound set; combine the first difference and the second difference corresponding to the compound to be analyzed to obtain the comprehensive difference value corresponding to the compound to be analyzed; wherein, the x-coordinate in the chromatographic data segment is the retention time, and the y-coordinate is the response intensity;

[0025] The degree of mixed similarity of any set of compounds is evaluated based on the overall difference value corresponding to all compounds in any given set of compounds.

[0026] Preferably, the step of combining the first difference and the second difference corresponding to the compound to be analyzed to obtain the comprehensive difference value corresponding to the compound to be analyzed includes:

[0027] The product of the normalized result of the first difference corresponding to the compound to be analyzed and the normalized result of the second difference corresponding to the compound to be analyzed is used as the comprehensive difference value corresponding to the compound to be analyzed.

[0028] Preferably, evaluating the mixing similarity of any set of compounds based on the comprehensive difference value corresponding to all compounds in any set of compounds includes:

[0029] Calculate the average of the comprehensive difference values ​​corresponding to all compounds in any given set of compounds;

[0030] The negative correlation mapping value of the average value is used as the mixed similarity of any set of compounds.

[0031] Preferably, the step of obtaining the correction weight for each reference standard by comprehensively considering the number of compounds in each compound set, the degree of mixing similarity, and the sample weight, includes:

[0032] For any reference standard:

[0033] By combining the number of compounds in the set of all compounds in any reference standard with the corresponding degree of mixing similarity, the degree of influence corresponding to any reference standard can be obtained;

[0034] The correction weight of any reference standard is obtained based on the sample weight of the specimen source where the reference standard is located and the degree of influence.

[0035] Preferably, obtaining the correction weight of any reference standard based on the sample weight of the specimen source and the degree of influence includes:

[0036] The product of the sample weight of the specimen source where any reference standard is located and the degree of influence is used as the correction weight of any reference standard.

[0037] Preferably, the step of determining the endocrine disorder classification of gynecological tuberculosis in the patient to be tested based on the corrected weights and the test samples includes:

[0038] The chromatographic and mass spectrometric data of each reference standard are corrected using a correction weight. Based on the corrected data, the test samples are analyzed using a chromatography-mass spectrometry system to determine the endocrine disorder subtype of gynecological tuberculosis in the patient to be tested.

[0039] The present invention has at least the following beneficial effects:

[0040] This invention obtains reference standards from different specimen sources and test samples from patients undergoing gynecological tuberculosis testing in historical trials. Based on this, it evaluates the compound identification accuracy of various specimen sources. Since reference standards from different sources have varying degrees of ideality for test results, the ideal effect and sample proportion of each specimen source are considered to determine the sample weight, improving the representativeness of sample selection and the rationality of weight allocation. Furthermore, compounds with similar structures within each reference standard are grouped into compound sets. By analyzing the distribution of retention time and response intensity of each compound in the chromatographic data segment, the degree of mixing similarity within the compound set is objectively evaluated, thus accurately reflecting the distinguishability between structurally similar compounds. Finally, by comprehensively considering the number of compound sets in each reference standard, the degree of mixing similarity, and the sample weight of the respective specimen source, a correction weight for each reference standard is calculated. Based on this correction weight, compound identification and typing of the test sample are performed. This overcomes the identification bias caused by insufficient reference samples and similar compound structures, improving the accuracy and reliability of endocrine disorder typing in gynecological tuberculosis. Attached Figure Description

[0041] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the method performed by a gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry, as provided in an embodiment of the present invention. Detailed Implementation

[0043] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description of the gynecological tuberculosis endocrine disorder typing system based on the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0045] The following description, in conjunction with the accompanying drawings, details the specific scheme of the gynecological tuberculosis endocrine disorder classification system provided by this invention, which uses chromatography-mass spectrometry.

[0046] Example of a gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry:

[0047] The specific scenario addressed in this embodiment is as follows: When classifying endocrine disorders caused by gynecological tuberculosis in patients to be tested, it is necessary to analyze the compounds in reference samples from historical gynecological tuberculosis testing processes. Based on the analysis results, the corresponding chromatographic and mass spectrometric data are corrected to determine the content of various compounds in the test sample of the patient to be tested, thereby achieving the classification of endocrine disorders caused by gynecological tuberculosis in the patient to be tested.

[0048] This embodiment proposes a chromatographic-mass spectrometric (GC-MS) system for classifying endocrine disorders in gynecological tuberculosis, such as... Figure 1 As shown, the method performed by the gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry in this embodiment includes the following steps:

[0049] Step S1: Obtain reference specimens and test samples from different specimen sources in the historical gynecological tuberculosis testing process.

[0050] Given that gynecological tuberculosis is a relatively rare disease with a small number of patients, the number of reference samples in historical gynecological tuberculosis testing is limited. The endocrine disorders caused by gynecological tuberculosis are complex and diverse. Since the primary target of gynecological tuberculosis is the uterus, the ideal sample for studying the endometrial microenvironment is an endometrial tissue biopsy. However, collecting such a sample is an invasive procedure, which patients often resist. Therefore, gentler methods are usually used, such as obtaining endometrial fluid through uterine perfusion. While this method can analyze the endometrial microenvironment, it only partially reflects the environmental state. In summary, the limited number of reference samples is constrained by practical conditions, making it difficult to collect large quantities for typing reference. Therefore, a more detailed analysis of existing reference samples is needed to increase their reference value and improve the accuracy of compound identification.

[0051] First, multiple reference samples from three specimen sources were retrieved from the database during historical gynecological tuberculosis testing. These three sources were samples obtained from endometrial aspiration, menstrual blood collection, and uterine cavity infusion. Based on experience, the ideal efficacy was set at 0.9 for endometrial aspiration, 0.8 for menstrual blood collection, and 0.65 for uterine cavity infusion. The number of reference samples for each specimen source was set by the implementer according to specific circumstances. Then, test samples were obtained from the patients to be tested. It should be noted that all data in this embodiment were obtained with full authorization.

[0052] Thus, through the above methods, multiple reference specimens and test samples from each specimen source in the historical gynecological tuberculosis testing process were obtained.

[0053] Step S2: Evaluate the compound identification accuracy of each sample source based on the number of compounds in different reference standards in each sample source; determine the sample weight of each sample source based on the compound identification accuracy of each sample source, the ideal effect of the sample source, and the proportion of reference standards.

[0054] Considering that a higher proportion of compounds in a sample source indicates higher accuracy in identifying reference standards from that sample source using chromatography-mass spectrometry, we will analyze the distribution of compounds in different reference standards from each sample source to evaluate the accuracy of compound identification.

[0055] The following explanation uses one specimen source as an example. Other specimen sources can be processed using the method provided in this embodiment.

[0056] Specifically, any sample source is designated as a candidate sample source. The ratio of the number of compounds in each reference standard from a candidate sample source to the total number of compounds in all reference standards from all sample sources is taken as the compound count percentage of each reference standard from the candidate sample source. The compound identification accuracy of the candidate sample source is obtained by combining the compound count percentages of all reference standards from all sample sources.

[0057] In this embodiment, a specific formula for calculating the compound recognition accuracy is given. The compound recognition accuracy of the candidate sample source can be expressed as:

[0058]

[0059] in, This indicates the accuracy of compound identification from the candidate sample source. Indicates the number of reference standards in the candidate specimen source. This indicates the number of compounds in the m-th reference standard from the candidate sample sources. This indicates the total number of compounds in all reference standards from all candidate specimen sources across all specimen sources. This represents the normalization function.

[0060] This can be approximated as the ratio of the number of compounds in the m-th reference standard from the candidate sample source to the total number of compounds in all reference standards from all sample sources. A higher average percentage of compounds in the reference standards from the candidate sample source indicates a greater overall concentration of compounds that the chromatography-mass spectrometry (GC-MS) instrument can identify when analyzing sample data from the candidate sample source, and thus higher accuracy in compound identification.

[0061] Under normal circumstances, higher compound identification accuracy generally leads to better ideal results for identifying compounds from the corresponding sample source. However, in real-world scenarios, there may be an inverse relationship between identification accuracy and ideal results. This is because the sample source is directly affected by changes in the patient's condition. When a patient's condition is severe, the number of compounds related to the condition (especially those that characterize the severity of the condition) in the uterus will significantly increase, making detection easier. In this case, compared to a sample source with higher ideal results and a milder condition, the actual reference value of the sample source with higher ideal results and a milder condition will be relatively reduced. Therefore, it is necessary to combine compound identification accuracy with the ideal results of the sample source to comprehensively evaluate the sample weight of each sample source.

[0062] In one specific implementation, the ratio of the number of reference samples in candidate specimen sources to the total number of reference samples in all specimen sources is used as the proportion of reference samples in candidate specimen sources. A larger proportion indicates a greater amount of reference data provided by the candidate specimen source, and a greater influence the candidate specimen source has on the combined analysis of the current patient's sample data. The compound identification accuracy of all specimen sources is arranged in descending order to obtain an identification accuracy sequence; all specimen sources are arranged in descending order of their ideal performance to obtain a specimen source sequence.

[0063] Furthermore, the ratio between the order of the candidate sample source's compound identification accuracy in the identification accuracy sequence and the number of species in the sample source is denoted as the first ratio, and the ratio between the order of the candidate sample source in the sample source sequence and the number of species in the sample source is denoted as the second ratio. Based on the proportion of reference samples in the candidate sample sources, the first ratio, and the second ratio, the sample weight of the candidate sample sources is obtained. The proportion of reference samples in the candidate sample sources is positively correlated with the sample weight, while both the first ratio and the second ratio are negatively correlated with the sample weight.

[0064] It should be noted that, from left to right, if the recognition precision of the compound from the candidate sample is the first element in the recognition precision sequence, then the sequence number of the recognition precision of the compound from the candidate sample in the recognition precision sequence is 1; if the recognition precision of the compound from the candidate sample is the second element in the recognition precision sequence, then the sequence number of the recognition precision of the compound from the candidate sample in the recognition precision sequence is 2; if the recognition precision of the compound from the candidate sample is the 31st element in the recognition precision sequence, then the sequence number of the recognition precision of the compound from the candidate sample in the recognition precision sequence is 3, and so on. If the candidate specimen source is the first element in the specimen source sequence, then the candidate specimen source's sequence number in the specimen source sequence is 1; if the candidate specimen source is the second element in the specimen source sequence, then the candidate specimen source's sequence number in the specimen source sequence is 2; if the candidate specimen source is the third element in the specimen source sequence, then the candidate specimen source's sequence number in the specimen source sequence is 3.

[0065] In this embodiment, a specific formula for calculating sample weights is given, and the sample weights of candidate specimen sources can be expressed as:

[0066]

[0067] in, The sample weights representing the sources of candidate specimens. Indicates the number of reference standards in the candidate specimen source. This indicates the total number of reference specimens from all specimen sources. This indicates the order of the compound recognition accuracy from the candidate sample source within the recognition accuracy sequence. This indicates the sequence number of the candidate specimen source within the specimen source sequence. Indicates the number of species from which the specimen originated. This represents the normalization function.

[0068] This indicates the proportion of reference samples in the candidate specimen source. The larger the value, the greater the relative proportion of reference samples in the candidate specimen source. The first ratio reflects the relative position of the compound recognition accuracy of the candidate sample in the recognition accuracy sequence. The smaller the value, the higher the position, indicating that the compound recognition accuracy is higher. The second ratio reflects the relative position of the candidate sample source within the sample source sequence. A smaller value indicates a higher ranking, signifying better performance. A higher proportion of reference standards within the candidate sample source, higher compound identification accuracy from the candidate sample source, and better overall performance from the candidate sample source indicate that the reference correction standard from that sample source has a greater impact on the identification results when the chromatography-mass spectrometry (GC-MS) instrument identifies compounds in the current patient sample; in other words, the candidate sample source has a greater sample weight.

[0069] The above methods can be used to determine the sample weight of each specimen source.

[0070] Step S3: Compounds with similar structures in a reference standard form a set of compounds; the mixing similarity of each set of compounds is evaluated by combining the distribution of retention time and response intensity of each compound in the corresponding chromatographic data segment.

[0071] While assigning sample weights to each specimen source through the above steps can alleviate the compound identification problem caused by insufficient reference data to some extent, it does not completely solve the problem. This is because the main interferences to the accuracy of compound identification using a chromatography-mass spectrometry (GC-MS) instrument for current patient samples fall into two categories: First, insufficient reference data means there are not enough data samples to distinguish compounds with similar physical structures (such as estradiol and estrone), making it difficult to maintain high-precision identification. Second, sufficient reference data means the GC-MS instrument uses consistent processing procedures (such as consistent flow, solutions, and test strips) when identifying compounds with similar physical structures, making effective identification of compounds with similar physical structures (such as estradiol and estrone) impossible. Furthermore, both types of accuracy interference may exist simultaneously when using GC-MS. For example, when distinguishing compounds with similar physical structures (such as estradiol and estrone), the GC-MS instrument may lack sufficient data samples, and due to its own process limitations, it may not effectively separate and identify compounds with similar physical structures. Therefore, it is necessary to analyze the compound mixing in different reference standards, adjust the sample weights, and obtain the correction weight for each reference standard.

[0072] For any reference standard from any specimen source, based on the structural similarity of the compounds, the set of compounds with similar structures in the reference standard is considered as a single compound set. Whether the structures are similar is determined manually; that is, the compounds in the reference standard are divided into multiple compound sets. Using this method, the compound sets in each reference standard from each specimen source can be divided. Each reference standard may contain multiple sets of structurally similar compounds. The compounds within each set are physically similar, while the physical structures of different sets of compounds may differ significantly.

[0073] For compounds with similar physical structures, since the physical structure of the compound is mainly expressed by the mass spectrum, their appearance in the mass spectrum is basically the same. However, there may be some slight differences in the retention time in the chromatogram. Therefore, by observing the distribution of the compound in the mass spectrum and chromatogram, it can be determined whether these compounds with similar physical structures originally had a relatively obvious mixing and identification situation.

[0074] The following explanation uses a set of compounds as an example. Other sets of compounds can be processed using the method provided in this embodiment.

[0075] Specifically, for any set of compounds: In the chromatogram, obtain the x-axis and y-axis of each compound in the chromatographic data segment, where the x-axis represents retention time and the y-axis represents response intensity. Denote any compound in the set as the analyte. Calculate the first difference between the x-axis of the analyte in its corresponding chromatographic data segment and the mean of the x-axis of all other compounds in the set, and the second difference between the y-axis of the analyte in its corresponding chromatographic data segment and the mean of the y-axis of all other compounds in the set. The product of the normalized result of the first difference and the normalized result of the second difference is used as the comprehensive difference value for the analyte. Calculate the average of the comprehensive difference values ​​for all compounds in the set. The negative correlation mapping value of this average is used as the mixing similarity of the set. Each reference standard corresponds to one chromatogram and one mass spectrum. The methods for obtaining the chromatograms and mass spectra are existing technologies and will not be elaborated further here.

[0076] In this embodiment, a specific formula for calculating the degree of mixing similarity is given. The degree of mixing similarity of the compound set can be expressed as:

[0077]

[0078] in, This indicates the degree of mixing similarity of the compound set. This indicates the number of compounds in the set of compounds. This represents the x-coordinate of the h-th compound in the corresponding chromatographic data segment. This indicates that the set of compounds excluding the first one... The mean of the x-axis of all compounds other than the specified compound in the chromatographic data segment. This indicates the first compound in the set. The ordinate of each compound in the corresponding chromatographic data segment; This indicates that the set of compounds excluding the first one... The mean of the ordinate of all compounds other than the specified compound in the chromatographic data segment. Represents the normalization function. This represents an exponential function with the natural constant as its base.

[0079] This represents the first difference corresponding to the h-th compound in the compound set, which reflects the difference between the retention time of the h-th compound and the overall retention time of other compounds in the compound set. The larger the value, the greater the difference in retention time between the two. This represents the second difference corresponding to the h-th compound in the compound set, which reflects the difference between the response intensity of the h-th compound and the overall response intensity of other compounds in the compound set. The larger the value, the greater the difference in response intensity between the two. This represents the overall difference value corresponding to the h-th compound. The smaller the average level of the overall difference values ​​for compounds in this set, the weaker the differences between the compounds in the set. When used as reference data to assist in the identification of compounds in the current patient's test sample, the weaker the ability to identify related compounds, and the more easily the compounds in this set are affected by the large differences in the distribution content within the patient's sample. The possibility of misidentifying one compound in the set as another increases, that is, the greater the mixed similarity of the compound set.

[0080] The mixing similarity of each compound set can be determined using the above methods.

[0081] Step S4: Combine the number of compounds, mixing similarity and sample weight in each compound set of each reference standard to obtain the correction weight of each reference standard; Based on the correction weight and the test sample, determine the endocrine disorder subtype of gynecological tuberculosis in the patient to be tested.

[0082] In the above steps, the mixing similarity of each compound set of each reference standard and the sample weight of each sample source were obtained. Next, the mixing similarity, sample weight and the number of compounds will be combined to determine the correction weight of each reference standard, thereby realizing the correction of chromatographic data and mass spectrometry data.

[0083] The following explanation uses a reference standard as an example. Other reference standards can be processed using the method provided in this embodiment.

[0084] For any reference standard: combine the number of compounds in all compounds in the set of the reference standard with the corresponding mixing similarity to obtain the influence degree of the reference standard; use the product of the sample weight of the specimen source of the reference standard and the influence degree as the correction weight of the reference standard.

[0085] In this embodiment, a specific formula for calculating the correction weight is given, and the correction weight of the reference standard can be expressed as:

[0086]

[0087] in, This indicates the correction weight of the reference standard. This indicates the sample weight of the specimen source from which the reference standard is located. This indicates the number of compounds in the reference standard. This indicates the degree of mixing similarity of the g-th compound set in the reference standard. This indicates the number of compounds in the g-th compound set of the reference standard.

[0088] The greater the mixing similarity of each compound set in the reference standard and the greater the number of compounds in the compound set, the greater the influence of the patient sample solution on the identification results of the compounds in the reference standard. This indicates the degree of influence of the reference standard, reflecting the extent to which the compound identification results of the reference standard are affected by the patient sample solution (unstable content, unstable reagents, etc.). The smaller the value, the less reference value the reference standard has for compound identification in the current patient sample solution. The smaller the sample weight of the specimen source of the reference standard and the smaller the degree of influence of the reference standard, the greater the correction weight of the reference standard.

[0089] The correction weight of each reference standard can be obtained using the above method.

[0090] After obtaining the correction weight for each reference standard, the chromatographic and mass spectrometric data are corrected using this weight. Specifically, the correction weight is multiplied by the ordinate of both the chromatogram and the mass spectrum, and the result is used as the corrected data. Each reference standard corresponds to a mass spectrum, with the x-axis representing the mass-to-charge ratio and the ordinate representing relative abundance. Based on all the corrected data, the data analysis module of the chromatography-mass spectrometry (GC-MS) instrument analyzes the test samples from the patients under investigation, outputting the types of compounds and the content of each compound in the samples. Subsequently, professionals, based on experience, classify the gynecological tuberculosis endocrine disorders in the patients under investigation according to the types and contents of the compounds in their samples. The process of using multiple reference standards as control groups and combining the chromatographic and mass spectrometric data of the patients under investigation for compound identification is an existing implementation process of the built-in data analysis module of the GC-MS instrument, and will not be elaborated further in this embodiment.

[0091] Thus, the method provided in this embodiment has enabled accurate classification of endocrine disorders in gynecological tuberculosis.

[0092] This embodiment acquires reference standards from different specimen sources and test samples from patients undergoing gynecological tuberculosis testing in historical trials. Based on this, it evaluates the compound identification accuracy of various specimen sources. Since reference standards from different sources have varying degrees of ideality for test results, a sample weight for each specimen source is determined by combining the ideal effect of each source with the proportion of samples, thus improving the representativeness of sample selection and the rationality of weight allocation. Furthermore, compounds with similar structures within each reference standard are grouped into compound sets. By analyzing the distribution of retention time and response intensity of each compound in the chromatographic data segment, the degree of mixed similarity within the compound set is objectively evaluated, thereby accurately reflecting the distinguishability between structurally similar compounds. Finally, by comprehensively considering the number of compound sets in each reference standard, the degree of mixed similarity, and the sample weight of the respective specimen source, a corrected weight for each reference standard is calculated. Based on this corrected weight, compound identification and typing of the test sample are performed, overcoming the identification bias caused by insufficient reference samples and similar compound structures, and improving the accuracy and reliability of endocrine disorder typing in gynecological tuberculosis.

[0093] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A chromatographic-mass spectrometric (GC-MS) system for classifying endocrine disorders in gynecological tuberculosis, characterized in that, The system includes a memory and a processor, the processor executing a computer program stored in the memory to perform the following steps: Obtain reference specimens and test samples from different specimen sources in the historical gynecological tuberculosis testing process; The compound identification accuracy of each sample source is evaluated based on the number of compounds in different reference standards within each sample source; the sample weight of each sample source is determined based on the compound identification accuracy, the ideal performance of each sample source, and the proportion of reference standards. Compounds with similar structures in a reference standard constitute a set of compounds; the mixing similarity of each set of compounds is evaluated by combining the distribution of retention time and response intensity of each compound in the corresponding chromatographic data segment. The correction weight for each reference standard is obtained by combining the number of compounds in each compound set, the degree of mixing similarity, and the sample weight. Based on the corrected weights and the test samples, the endocrine disorder subtype of gynecological tuberculosis in the patients to be tested was determined.

2. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 1, characterized in that, The evaluation of compound identification accuracy for each sample source based on the number of compounds in different reference standards from each sample source includes: The ratio of the number of compounds in each reference standard in the candidate sample source to the total number of compounds in all reference standards in all sample sources is taken as the proportion of the number of compounds in each reference standard in the candidate sample source. The compound identification accuracy of the candidate sample source is obtained by combining the proportion of compounds in all reference standards in the candidate sample source; The candidate specimens can be from any specimen source.

3. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 2, characterized in that, The determination of sample weight for each sample source based on its compound identification accuracy, ideal performance, and the proportion of reference standards includes: The ratio of the number of reference samples in the candidate specimen sources to the total number of reference samples in all specimen sources is taken as the proportion of the number of reference samples in the candidate specimen sources. The recognition accuracy of compounds from all sample sources was sorted in descending order to obtain the recognition accuracy sequence; the sample source sequence was sorted in descending order of the ideal effect of all sample sources. The sample weights of candidate sample sources are obtained based on the proportion of reference standards in the candidate sample sources, the order of the compound recognition accuracy of the candidate sample sources in the recognition accuracy sequence, and the order of the candidate sample sources in the sample source sequence.

4. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 3, characterized in that, The sample weight of a candidate sample source is obtained based on the proportion of reference standards in the candidate sample sources, the order of the compound recognition accuracy of the candidate sample source in the recognition accuracy sequence, and the order of the candidate sample source in the sample source sequence, including: Calculate the first ratio between the order of the candidate sample source in the recognition accuracy sequence and the number of species in the sample source, and the second ratio between the order of the candidate sample source in the sample source sequence and the number of species in the sample source. The sample weight of a candidate specimen source is obtained based on the proportion of reference samples in the candidate specimen source, the first ratio, and the second ratio. The proportion of reference samples in the candidate specimen source is positively correlated with the sample weight, while the first ratio and the second ratio are both negatively correlated with the sample weight.

5. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 1, characterized in that, The evaluation of the mixing similarity of each compound set by combining the distribution of retention time and response intensity of each compound in the corresponding chromatographic data segment includes: For any set of compounds: Calculate the first difference between the x-coordinate of the compound to be analyzed in the corresponding chromatographic data segment and the mean of the x-coordinates of all other compounds in the chromatographic data segment of any given compound set, and the second difference between the y-coordinate of the compound to be analyzed in the corresponding chromatographic data segment and the mean of the y-coordinates of all other compounds in the chromatographic data segment of any given compound set, wherein the compound to be analyzed is any compound in any given compound set; combine the first difference and the second difference corresponding to the compound to be analyzed to obtain the comprehensive difference value corresponding to the compound to be analyzed; wherein, the x-coordinate in the chromatographic data segment is the retention time, and the y-coordinate is the response intensity; The degree of mixed similarity of any set of compounds is evaluated based on the overall difference value corresponding to all compounds in any given set of compounds.

6. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 5, characterized in that, The step of combining the first difference and the second difference corresponding to the compound to be analyzed to obtain the comprehensive difference value corresponding to the compound to be analyzed includes: The product of the normalized result of the first difference corresponding to the compound to be analyzed and the normalized result of the second difference corresponding to the compound to be analyzed is used as the comprehensive difference value corresponding to the compound to be analyzed.

7. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 5, characterized in that, The evaluation of the mixed similarity of any set of compounds based on the comprehensive difference value corresponding to all compounds in any set of compounds includes: Calculate the average of the comprehensive difference values ​​corresponding to all compounds in any given set of compounds; The negative correlation mapping value of the average value is used as the mixed similarity of any set of compounds.

8. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 1, characterized in that, The correction weight for each reference standard is obtained by combining the number of compounds in each compound set, the degree of mixing similarity, and the sample weight, including: For any reference standard: By combining the number of compounds in the set of all compounds in any reference standard with the corresponding degree of mixing similarity, the degree of influence corresponding to any reference standard can be obtained; The correction weight of any reference standard is obtained based on the sample weight of the specimen source where the reference standard is located and the degree of influence.

9. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 8, characterized in that, The step of obtaining the correction weight of any reference standard based on the sample weight of the specimen source where the reference standard is located and the degree of influence includes: The product of the sample weight of the specimen source where any reference standard is located and the degree of influence is used as the correction weight of any reference standard.

10. The gynecological tuberculosis endocrine disorder typing system using chromatography-mass spectrometry according to claim 1, characterized in that, The method of determining the endocrine disorder subtype of gynecological tuberculosis in patients under test based on corrected weights and test samples includes: The chromatographic and mass spectrometric data of each reference standard are corrected using a correction weight. Based on the corrected data, the test samples are analyzed using a chromatography-mass spectrometry system to determine the endocrine disorder subtype of gynecological tuberculosis in the patient to be tested.

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