Traditional Chinese medicine cold-heat syndrome type identification method, device and system and storage medium

Abstract

The invention discloses a traditional Chinese medicine cold-heat syndrome type identification method, device and system and a storage medium, and the method comprises the steps: S1, constructing a biological sample library according to the tongue coating flora of healthy people, cold-cold syndrome people and cold-heat syndrome people; s2, according to the biological sample library and the traditional Chinese medicine syndrome integral scale, constructing a cold-cold-heat syndrome classification model; and S3, inputting the to-be-processed tongue coating flora of the tested person into the cold and cold-heat syndrome classification model for traditional Chinese medicine cold-heat syndrome type identification. By adopting the technical scheme provided by the invention, an objective basis is provided for the judgment and curative effect evaluation of the cold-heat syndrome in the traditional Chinese medicine by detecting the tongue coating flora.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, specifically relating to a method, device, system, and storage medium for identifying cold and heat syndromes in traditional Chinese medicine. Background Technology

[0002] "Syndrome differentiation and treatment" is the core of traditional Chinese medicine (TCM) diagnosis and treatment. It requires clinicians to collect patient information through "inspection, auscultation and olfaction, inquiry, and palpation," conduct comprehensive analysis, clearly analyze and judge the syndrome elements at the current stage of the patient's disease development, ultimately determine the syndrome diagnosis, and then formulate treatment based on the prescribed formula. Tongue coating, as a product formed by the upward accumulation of turbid qi from the stomach on the tongue surface after the transformation of stomach qi, is considered an external projection of the body's internal environment. It is an important component of TCM tongue diagnosis and a crucial reference for syndrome differentiation and treatment. Modern medicine has discovered that the tongue coating in the oral cavity is a complex biological thin layer tightly bound to epithelial cells on the surface of the tongue, densely covered with microorganisms. Related research has found that the tongue coating is a potential oral microbial reservoir; changes in its microbial composition and abundance can be used to diagnose and monitor disease changes, serving as a "barometer" of human health and a biomarker for TCM cold and heat syndromes.

[0003] The common cold is a common exogenous disease caused by exposure to wind and pathogens, which invade the body's defensive qi. It can occur in all seasons, but is most prevalent in spring and winter, and falls under the category of upper respiratory tract infections. With the fast pace of modern life, convenient traditional Chinese medicine (TCM) preparations have become a common choice for treating colds. Among the common cold syndromes, cold and heat syndromes are frequently observed. Accurately identifying these syndromes is crucial for selecting the right TCM preparations and is also an important way to improve the efficacy of TCM treatments.

[0004] At present, traditional Chinese medicines in my country are no longer only obtained through prescriptions from TCM doctors, but can also be easily obtained through major pharmacies and online channels. Without basic TCM theoretical knowledge and clinical practice guidance, it is possible to take the wrong medicine for the wrong condition, which will affect the treatment effect. In severe cases, adverse drug reactions unrelated to the disease itself may occur, indirectly increasing the medical burden. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method, device, system, and storage medium for identifying cold and heat syndromes in Traditional Chinese Medicine.

[0006] To achieve the above objectives, the present invention provides the following solution: A method for differentiating cold and heat syndromes in Traditional Chinese Medicine includes: Step S1: Construct a biobank based on the historical tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome; Step S2: Construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale; Step S3: Input the tongue flora of the test subjects into the cold and fever syndrome classification model for TCM cold and fever syndrome identification. Preferably, in step S1, the diversity and distribution characteristics of tongue flora in different populations are obtained by 16S rRNA sequencing to find the marker tongue flora of different stage syndromes.

[0007] As a preferred option, in step S2, a Logistic regression analysis model is trained using the biosample bank and the TCM syndrome scoring scale to construct a classification model for cold and fever syndromes.

[0008] This invention also provides a device for identifying cold and heat syndromes in Traditional Chinese Medicine, comprising: The first processing module is used to construct a biobank based on the historical tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome. The second processing module is used to construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale. The third processing module is used to input the tongue flora of the test subjects into the cold and fever syndrome classification model for TCM cold and fever syndrome identification.

[0009] As a preferred option, the first processing module obtains the diversity and distribution characteristics of tongue flora in different populations through 16S rRNA sequencing, and finds the marker tongue flora of different stage syndromes.

[0010] As a preferred option, the second processing module trains a Logistic regression analysis model using the biobank and the TCM syndrome scoring scale to construct a classification model for cold and fever syndromes.

[0011] The present invention also provides a TCM cold and heat syndrome identification system, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes the TCM cold and heat syndrome identification method when executed by the processor.

[0012] The present invention also provides a storage medium storing a computer program, which executes a method for identifying cold and heat syndromes in traditional Chinese medicine when running.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Based on the tongue coating flora, a convenient and non-invasive detection method is used to obtain objective indicators for classifying cold and heat syndromes in people with colds, so as to better guide doctors and patients in choosing drugs and avoid drug abuse.

[0014] 2. Objectively quantifying TCM syndrome types through tongue flora can improve the accuracy of syndrome type determination, reduce the diagnostic and treatment burden of TCM doctors, improve diagnostic and treatment efficiency, and can also serve as a basis for evaluating the efficacy of TCM. Attached Figure Description

[0015] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are 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.

[0016] Figure 1 This is a flowchart of the method for identifying cold and heat syndromes in traditional Chinese medicine in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Example 1 like Figure 1 As shown, this invention provides a method for identifying cold and heat syndromes in Traditional Chinese Medicine, comprising: Step S1: Construct a biobank based on the historical tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome; Step S2: Construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale; Step S3: Input the tongue flora of the test subjects to be processed into the cold and fever syndrome classification model for TCM cold and fever syndrome identification.

[0020] As one embodiment of the present invention, in step S1, the diversity and distribution characteristics of tongue flora in different populations are obtained by 16S rRNA sequencing, and the marker tongue flora of different stage syndromes are found.

[0021] Furthermore, high-throughput sequencing was used to process tongue coating microorganisms, including: DNA Extraction: Total genomic DNA samples were extracted using the OMEGA Soil DNA Kit (D5625-01) (Omega Bio-Tek, Norcross, GA, USA) according to the product instructions and stored at -20°C before further analysis. The concentration and quality of the extracted DNA were measured using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Scientific, Waltham, MA, USA) and agarose gel electrophoresis.

[0022] Microbiome sequencing: PCR amplification of the V3-V4 region of the bacterial 16S rRNA gene was performed using forward primer 338F (5'-ACTCCTACGGGAGGCGCAGCA-3') and reverse primer 806R (5'-GGACTACHVGGGTWTCTAAT-3'). Sample-specific 7-bp barcodes were integrated into the primers for multiplex sequencing. PCR components included 5 μl buffer (5x), 0.25 μl Fast pfu DNA polymerase (5 U / μl), 2 μl (2.5 mM) dNTPs, 1 μl (10 uM) of each forward and reverse primer, 1 μl DNA template, and 14.75 μl ddH2O. Thermal cycling consisted of initial denaturation at 98°C for 5 min, followed by 25 cycles of denaturation at 98°C for 30 s, annealing at 53°C for 30 s, and extension at 72°C for 45 s, with a final extension of 5 min at 72°C. PCR amplicones were purified using Vazyme VAHTS™ DNA Clean Beads (Vazyme, Nanjing, China) and quantified using the Quant-iT PicoGreen dsDNA assay kit (Invitrogen, Carlsbad, CA, USA). After individual quantification, amplicon volumes were pooled and sequenced at paired ends (2 × 250 bp) using the Illlumina NovaSeq platform and NovaSeq 6000SP Reagent Kit (500 cycles).

[0023] Microbial data preparation: The QIIME 2_DADA 2 analysis workflow was used to process and analyze microbial sequences, mainly including primer removal, quality filtering, denoising, splicing, and chimera removal. Specifically: ① The original sequence data was demultiplexed using the demux plugin. ② Primers were cut using the cutadapt plugin. ③ The sequences were quality filtered, denoised, merged, and dechimerized using the DADA2 plugin. ④ Non-singleton amplicon sequence variants (ASVs) were aligned using maft, and a phylogenetic tree was constructed using fasttree2. ⑤ The diversity plugin was used to evaluate α-diversity parameters (Chao1 index, Shannon index) and beta-diversity parameters (Bray Curtisdissimilarity). ⑥ Based on the Greengenes database (Release 13.8, http: / / greengenes.secondgenome.com), 99% of the reference sequences of operational taxonomic units (OTUs) were used. The classify-sklearn naïve Bayes classifier in the feature classifier plugin was used to assign ASVs to taxonomic units to complete species annotation.

[0024] Data Analysis: Microbiome bioinformatics analysis was performed using QIIME2 (2019.4) based on the publicly available tutorial (https: / / docs.qiime2.org / 2019.4 / tutorials / ). LEfSe analysis was used to detect taxa with rich and stable differences between groups. Random forest analysis was performed using QIIME2 to distinguish the contribution of samples from different groups to inter-group differences. Tongue marker bacteria were obtained from individuals with cold-type and fever-type colds. As one embodiment of the present invention, in step S2, a Logistic regression analysis model is trained using a biosample bank and a traditional Chinese medicine syndrome scoring scale to construct a cold and heat syndrome classification model for assisting in the diagnosis of cold and heat syndromes in patients with colds.

[0025] Furthermore, using SPSS 26.0 software, a predictive model was constructed using multivariate logistic regression analysis. Based on the estimated sample size, at least 300 cases needed to be collected for analysis, with 200 cases used for model building and the remaining 100 cases used for model prediction. The specific steps are as follows: 1. Data preparation: Assign values ​​of 1, 2, and 3 to healthy individuals, those with cold symptoms of cold, and those with cold symptoms of heat, respectively.

[0026] 2. Open SPSS software, click the menu bar: Analyze → Regression → Multinomial Logistic, and open the main dialog box. Step 1: Select variables: include healthy people, cold syndrome, and hot syndrome in the dependent variable (ordinal categorical variable), and set healthy people (1) as the reference category. Step 2: Select variables, including continuous variables: syndrome score and relative abundance of tongue coating marker bacteria. Step 3: Design statistics: check: model fit, likelihood ratio test, parameter estimation, classification table, 95% confidence interval of covariates, and click Continue to return. Step 4: Save the prediction results, including the prediction category and prediction probability. Step 5: Execute the model. Obtain the regression coefficients of each factor containing tongue coating bacteria, and construct the prediction model for cold syndrome and hot syndrome.

[0027] 3. Model validation: Another 100 cases were used to validate the model and obtain the accuracy, sensitivity and specificity of the prediction model.

[0028] By employing the technical solution of this invention, the selection and use of traditional Chinese medicine preparations can be better guided through "syndrome scoring - tongue coating microbiota collection - microbiota sequencing - data joint analysis - cold and heat syndrome classification".

[0029] Example 2 This invention also provides a device for identifying cold and heat syndromes in Traditional Chinese Medicine, comprising: The first processing module is used to construct a biobank based on the historical tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome. The second processing module is used to construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale. The third processing module is used to input the tongue flora of the test subjects into the cold and fever syndrome classification model for TCM cold and fever syndrome identification.

[0030] As one embodiment of the present invention, the first processing module obtains the diversity and distribution characteristics of tongue flora in different populations through 16S rRNA sequencing, and finds the marker tongue flora of different stage syndromes.

[0031] As one embodiment of the present invention, the second processing module trains a Logistic regression analysis model using a biological sample bank and a traditional Chinese medicine syndrome scoring scale to construct a classification model for cold and fever syndromes.

[0032] Example 3 The present invention also provides a TCM cold and heat syndrome identification system, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes the TCM cold and heat syndrome identification method when executed by the processor.

[0033] Example 4 The present invention also provides a storage medium storing a computer program, which executes a method for identifying cold and heat syndromes in traditional Chinese medicine when running.

[0034] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for identifying cold and heat syndromes in Traditional Chinese Medicine, characterized in that, include: Step S1: Construct a biobank based on the tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome; Step S2: Construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale; Step S3: Input the tongue flora of the test subjects to be processed into the cold and fever syndrome classification model for TCM cold and fever syndrome identification.

2. The method for identifying cold and heat syndromes in Traditional Chinese Medicine as described in claim 1, characterized in that, In step S1, the diversity and distribution characteristics of tongue flora in different populations are obtained by 16S rRNA sequencing, and the marker tongue flora of different stage syndromes are found.

3. The method for identifying cold and heat syndromes in Traditional Chinese Medicine as described in claim 2, characterized in that, In step S2, the biosample bank and the TCM syndrome scoring scale are used to train a Logistic regression analysis model to construct a classification model for cold and fever syndromes.

4. A device for identifying cold and heat syndromes in Traditional Chinese Medicine, characterized in that, include: The first processing module is used to construct a biobank based on the historical tongue flora of healthy individuals, individuals with cold-type cold syndrome, and individuals with cold-type fever syndrome. The second processing module is used to construct a classification model for cold and fever syndromes based on the biobank and the TCM syndrome scoring scale. The third processing module is used to input the tongue flora of the test subjects into the cold and fever syndrome classification model for TCM cold and fever syndrome identification.

5. The TCM cold and heat syndrome identification device as described in claim 4, characterized in that, The first processing module obtains the diversity and distribution characteristics of tongue flora in different populations through 16S rRNA sequencing, and identifies the marker tongue flora of different stage syndromes.

6. The TCM cold and heat syndrome identification device as described in claim 5, characterized in that, The second processing module trains a Logistic regression analysis model using the biosample bank and the TCM syndrome scoring scale to construct a classification model for cold and fever syndromes.

7. A TCM cold-heat syndrome differentiation system, characterized in that, include: The system includes a memory and a processor, wherein the memory stores a computer program that is executed by the processor, and the computer program, when executed by the processor, performs the method for identifying cold and heat syndromes in traditional Chinese medicine as described in any one of claims 1-3.

8. A storage medium, characterized in that, The storage medium stores a computer program, which executes the method for identifying cold and heat syndromes in traditional Chinese medicine as described in any one of claims 1-3 when the computer program is running.

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