ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objective To explore the motor coordination characteristics of the attack leg of the athletes under scoring actions in the front roundhouse kick of competitive taekwondo,and provide a theoretical basis for coaches to formulate precise training strategies in stages and segments so as to enhance the efficiency and success rate of the athletes' movements.Methods Kinematic data and surface electromyography signals were collected from 15 elite Taekwondo athletes during different phases of the front roundhouse kick.The continuous relative phase(CRP)method was used to calculate the joint coordination and variability of continuous relative phase(VCRP),while non-negative matrix factorization and k-means clustering were used to analyze muscle synergy characteristics.Results The coupling of the neural launch phase was dominated by knee-ankle coupling in coronal axis and hip-ankle coupling in sagittal axis.The coupling of the kicking phase was dominated by hip-knee,hip-ankle in coronal axis,and knee-ankle coupling in vertical axis.The coupling of the recovery phase was dominated by hip-knee,hip-ankle coupling in coronal axis,and knee-ankle coupling in sagittal axis.These coupling relationships remained relatively stable around 0 rad.Approximately 80.0％VCRP remained stable across all phases,with minor fluctuations occurring at phase transitions.A total of 4,5,and 4 muscle synergy clusters were identified in neural launch,kicking,recovery phases,respectively.There were significant differences in the mean gap values among phases(P＜0.001).However,there were no significant differences in the mean sparsity values among phases(P＞0.05).Some muscle synergies were shared across phases,while others differentiated to form phase-specific coordination patterns.Conclusions Joint coordination in each phase exhibited 1-3 primary stable patterns with flexibility during transitions.Muscle coordination was dynamically adjusted throughout the motion,and a general muscle synergy pattern functioned consistently across different phases,whereas a differentiated muscle synergy pattern fulfilled the phase-specific functional demands.The neural launch and kicking phases should be focused on during training,with the emphasis on controling over critical points to optimize performance.

Objective:To study the etiological relationship between Yunnan sudden unexplained death (hereinafter referred to as YNSUD) and the desmosomal protein gene mutation of arrhythmogenic right ventricular cardiomyopathy (ARVC).Methods:From September 2019 to August 2020, a cross-sectional survey method was used to select 9 key counties (cities) of YNSUD in Yunnan Province as survey sites. Autopsy cardiac blood samples of YNSUD cases ( n = 11) were collected, and peripheral venous blood samples of co-occurring case ( n = 1), case relatives ( n = 128), and control population ( n = 60) were collected. Genomic DNA from blood was extracted. After PCR amplification, 97 exons of 5 ARVC desmosomal protein genes, including plakophilin-2 (PKP2), desmoglein-2 (DSG2), desmocollin-2 (DSC2), desmoplakin (DSP), and junction plakoglobin (JUP) were sequenced by Sanger method, and the gene mutation was analyzed. Results:Compared with the control population, YNSUD cases, co-occurring case and case relatives carried 52 gene mutation sites in 36 exons of the ARVC desmosomal protein gene, with a total mutation rate of 37.11% (36/97). Among them, there were 21 in DSP gene, 10 in DSG2 gene, 8 in PKP2 gene, 8 in DSC2 gene, and 5 in JUP gene. YNSUD cases, co-occurring case and case relatives carried two same gene mutation sites: DSG2 gene exon 15 c.3321 T>C synonymous mutation and JUP gene exon 3 c.213 T>C synonymous mutation.Conclusions:The mutation rate of ARVC desmosomal protein gene is relatively high in the population of YNSUD. The two same gene mutation sites (DSG2 gene c.3321 T>C and JUP gene c.213 T>C) carried by YNSUD cases, co-occurring case and case relatives may be associated with the pathogenesis of YNSUD.

Objective To explore the role of pseudogene AC106872.1 in maintaining the self-renewal capacity of human embryonic stem cells(hESCs).Methods AC106872.1 was knocked out in hESCs and knockout effi-ciency was validated by PCR and agarose gel electrophoresis.The colony formation of hESCs was assessed through colony formation assays and alkaline phosphatase(AP)staining.The expression level of pluripotency and differ-entiation marker genes was analyzed by qPCR and flow cytometry.RNA sequencing(RNA-seq)was performed to assess transcriptomic changes upon AC106872.1 knockout.Results Knockout of AC106872.1 significantly in-hibited the colony formation of hESCs(P＜0.05).The expression level of pluripotency marker genes was signifi-cantly reduced(P＜0.000 1),while the expression of differentiation marker genes was markedly increased(P＜0.000 1).Conclusions The pseudogene AC 1 06872.1 plays a crucial role in maintaining human embryonic stem cell self-renewal through regulation of pluripotency genes expression.

Objective:This study investigated the awareness and consumption of Trogia venenata among populations in regions affected by Yunnan unexplained sudden death (YUSD). The findings aim to support etiological research on YUSD and contribute to the formulation of preventive measures against Trogia venenata poisoning. Methods:This study was a case-control study. From 2018 to 2021, surveys were conducted in 90 villages across 25 counties within YUSD-affected areas in Yunnan Province. Households with YUSD cases were designated as case households, whereas households without YUSD cases served as controls, ande were selected through convenience sampling at a 3:1 ratio. An enhanced questionnaire was designed to collect information on the consumption of Trogia venenata, and symptoms following consumption. Frequency data were presented as percentages, and group comparisons were conducted using χ 2 tests or Fisher’s exact tests. Results:A total of 711 questionnaires were collected (response rate: 100%), comprising 175 case households and 536 control households. Trogia venenata was present in 80.82% of the villages surveyed. Among the 711 households, 15.89% reported consuming Trogia venenata, primarily through stir-frying (53.10%), followed by boiling (29.20%), boiling and stir-frying (15.93%), and steaming (1.77%). Most households (94.69%) consumed fresh fruiting bodies, with 69.02% consuming them fewer than three times annually. The consumption rates were higher among the case households than among the control households. Of the 113 households with a history of Trogia venenata consumption, 35.40% reported symptoms such as nausea, vomiting, and limb soreness. The proportions of affected families in each group were compared according to their source, cooking method, fruiting body status and consumption frequency. The proportion of affected families with high consumption frequency (≥3 times/year) was higher than that with low consumption frequency (<3 times/year). Among 421 YUSD cases, 63 cases (14.96%) had a history of Trogia venenata consumption before death, with 43 cases showing symptoms within the longest known latency period (14 d) for poisoning by this mushroom. Conclusions:Trogia venenata is prevalent in 80.82% of YUSD-affected regions, with 16.67% of the population reporting its consumption, predominantly as fresh fruiting bodies prepared by stir-frying or boiling. Confirmed Trogia venenata consumption was identified in 14.96% of YUSD cases, suggesting that mushroom poisoning is a significant risk factor for YUSD. Ongoing health education and interventions are critical for mitigating the risk of Trogia venenata poisoning.

Objective To investigate the effect of KH-type splicing regulatory protein(KHSRP)on the malignant biological behavior of lung adenocarcinoma(LUAD)by targeting the Janus kinase 1(JAK1)/signal transducer and activator of transcription 3(STAT3)signaling axis.Methods Clinical data were collected for 64 patients with LUAD,diagnosed at Huaihe Hospital from January 2017 to December 2018.Expression levels of KHSRP were detected in LUAD tissues and adjacent tissues by immunohistochemical staining.KHSRP gene expression was also detected in LUAD cell lines(SPC-A1,H1975,CL1-5,PC-9,Calu-3,H446)and normal human bronchial epithelial cells using quantitative reverse transcription-polymerase chain reaction.KHSRP expression in SPC-A1,H1975,PC-9,and Calu-3 cells was manipulated by lentivirus transfection.The effects of KHSRP on the proliferation,migration,and invasion of LUAD cells were detected by Cell Counting Kit-8 and Transwell assays.The effects of KHSRP overexpression and knockdown were also investigated in a mouse xenograft tumor model,and JAK/STAT signaling pathway proteins were detected by Western blot.Rescue experiments were conducted to verify if KHSRP promoted the malignant progression of LUAD cells by regulating the JAK1/STAT3 signaling pathway.Results KHSRP expression was significantly higher in LUAD tissues compared with adjacent tissues(P＜0.05).Overexpression of KHSRP significantly promoted the proliferation,migration,and invasion of LUAD cells in vitro(P＜0.05).KHSRP also promoted LUAD cell xenograft tumor growth and lung nodule metastasis in nude mice in vivo(P＜0.01).KHSRP knockdown significantly decreased the levels of JAK1,phospho-JAK1,and STAT3 in the JAK/STAT signaling pathway,while the situation was reversed following KHSRP overexpression(P＜0.05).Rescue experiments showed that KHSRP reversed the inhibitory effect of knockdown(P＜0.05).Conclusions KHSRP targets the JAK1/STAT3 signaling pathway and acts as an oncogene in LUAD.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

Objective:To analyze the infection status of Coxsackievirus B group (CVB) in regions affected by sudden unexplained death in Yunnan (referred to as sudden death in Yunnan), and to provide a scientific basis for formulating effective prevention and control strategies.Methods:A cross-sectional survey method was employed. The population from 16 counties (cities, districts, referred to as counties) affected by sudden death in Yunnan Province from 2002 to 2022 and the population from one non-affected county in 2021 and 2022 (control population) were classified into cases of sudden death in Yunnan (7 cases), co-occurring cases (29 cases), high-risk population (1 303 cases), and control population (270 cases). Blood samples were collected from these populations. By using enzyme-linked immunosorbent assay (ELISA), CVB immunoglobulin M (CVB-IgM) antibodies in the acute-phase serum samples of the population in the affected areas were detected, and CVB immunoglobulin G (CVB-IgG) antibodies in the convalescent-phase serum samples were detected. Both types of detections were carried out on the control population, and the test results were analyzed.Results:A total of 1 609 serum samples were tested, including 1 339 samples from the population in the affected areas (923 acute-phase samples and 416 convalescent-phase samples) and 270 samples from the control population. Among the 16 affected counties, positive CVB-IgM antibody results were detected in 9 counties. The overall positive rate of the population in the affected areas was higher than that of the control population [7.80% (72/923) vs. 4.44% (12/270), χ 2 = 40.78, P < 0.001]. The positive rates of the high-risk population in Dayao County and Lufeng City were both higher than that of the control population [(22.22% (22/99), 10.92% (25/229) vs. 4.44% (12/270), χ 2 = 27.37, 7.56, P < 0.05]. Positive CVB-IgG antibody results were detected in 7 counties. The overall positive rate of the population in the affected areas was higher than that of the control population [(4.09% (17/416) vs. 0.74% (2/270), χ 2 = 6.81, P = 0.009]. The positive rates of CVB-IgM and CVB-IgG antibodies in the population of the affected areas in Dayao County [22.22% (22/99), 9.80% (5/51)] were both higher than those of the control population ( P < 0.05). Among the five affected villages in Dayao County, the positive rates of CVB-IgM and CVB-IgG antibodies in the population of Aji Ju Village were the highest [25.49% (13/51), 3/13]. Conclusions:The positive rates of both CVB-IgM and CVB-IgG antibodies in the population of the areas affected by sudden death in Yunnan were higher than those of the control population, indicating that CVB infection occurred during the sudden death events in the above-mentioned affected areas.

Objective To investigate how dietary supplementation with tetrahydrocurcumin(THC)improves kidney injury in type 2 dia-betic mellitus(T2DM)and its mechanism of action using transcriptome sequencing(RNA-seq).Methods C57BL/6J mice were randomly assigned to the control,T2DM,and T2DM+THC groups.After a high-fat meal and streptozotocin injection,the body weights and fasting blood glucose levels of each mouse with T2DM were measured.Hematoxylin and eosin staining,Oil red O staining,and RNA-seq were performed to examine kidney pathology,lipid deposition,and differentially expressed genes,respectively,in the mice.Results Mice in T2DM group exhibited significantly higher fasting blood glucose levels(P＜0.001),renal tubule degeneration,glomeruli enlargement,disordered epithelial cells,and increased kidney lipid deposition after 12 weeks compared with those of the control group.THC adminis-tration alleviated all these conditions(P＜0.001).RNA-seq analysis revealed significant gene expression variations among the control,T2DM,and T2DM+THC groups.THC may protect against T2DM-induced kidney injury and lipid deposition by regulating the cell cycle(apoptosis),P53 signaling pathway,and PPARγ signaling path way,as indicated by Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses.In mice with T2DM,THC intervention may upregulate the expression of Cd36,Lpl,PPARγ,and Plin4 genes in renal tissues,while downregulating Ccnb1,Ccnb2,Cdk1,Bub1,and Cdc25c gene expressions.The proteins encoded by the four upregulated genes interact,as do those encoded by the five downregulated genes.Conclusion THC administration improves fasting blood glucose levels,reduces renal damage,and decreases fat deposition in mice with T2DM.The processes may involve decreasing apoptosis,blocking the P53 signaling pathway,and activating the PPARγ signaling pathway.