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 This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective To analyze the implementation of MPOWER tobacco control policies in different regions and populations in China,as well as the impact of perceptions of tobacco control policies on individual smoking behavior and quit intentions,to promote the fairness of policy implementation and protection for vulnerable groups.Methods A multivariable regression model was constructed utilizing raw data from the China Adult Tobacco Survey to analyze disparities in perceived MPOWER policy implementation among various social demographics and its impact on smoking behavior and quitting intentions.Results Regarding protection from tobacco smoke(P),local economic level,urban-rural divide were significantly correlated with awareness of comprehensive smoking bans.For offering help to quit smoking(O),local tobacco industry revenue and individual age were associated with the doctor's advice for quitting.As to the warning about the harm of tobacco(W),economic level,geography and urban-rural disparity were correlated with the visibility of health warnings.About the tobacco advertising,promotion and sponsorship(E),geography was related to the exposure to tobacco advertisements,local tobacco industry revenue was associated with the tobacco promotion.For tobacco taxes(R),education level and age were significantly correlated with tobacco affordability.People who perceived comprehensive smoking bans(OR=0.69,95%CI:0.59-0.81)was associated with less smoking behavior,while people perceiving tobacco promotional activities(OR=2.51,95%CI:2.00-3.17)were more likely to smoke.Additionally,people who perceived comprehensive smoking bans(OR=1.70,95%CI:1.25-2.31)and health warning(OR=2.09,95%CI:1.48-3.01)had higher intention to quit smoking.Conclusion In economically disadvantaged regions and among specific socially vulnerable groups(such as low-income individuals,rural residents,and the elderly)in China,the perception of tobacco control policy implementation is relatively low,the perception of tobacco control policies can influence smoking behavior and quitting intentions.Legislative and enforcement efforts should be increased targeting these groups with lower perceptions of the policies to enhance the fairness of tobacco control measures.

AIM To study the chemical constituents from the roots of Siraitia grosvenorii(Swingle)C.Jeffrey and their α-glucosidase inhibitory activities.METHODS The 95％ethanol extract was isolated and purified by silica gel,MCI,ODS and HSCCC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The α-glucosidase inhibitory activities were evaluated by PNPG method,after which molecular docking was performed.RESULTS Twenty-one compounds were isolated and identified as vanillin(1),siraitic acid B(2),cucurbitacin B(3),salicylic acid(4),ferulic acid(5),p-hydroxybenzaldehyde(6),(+)-lariciresinol(7),(+)-isolariciresinol(8),liballinol(9),3-(hydroxyacetyl)indole(10),2E-4-hydroxy-nonenoic acid(11),vomifolilol(12),vanillic acid(13),indole-3-carboxylic acid(14),ω-hydroxypropioguaiacone(15),p-hydroxybenzoic acid(16),p-coumaric acid(17),dehydrodipinocarpine(18),secoisolariciresinol(19),sesquimarocanol A(20),threo-guaiacylglycerol-β-O-4-lariciresinol ether(21).IC50 values of compounds 4,10,18 and 21 were(0.42±0.060)-(0.89±0.037)mg/mL.CONCLUSION Compounds 4,10-12,15,16,18,and 21 are isolated from the roots of this plant for the first time.Compounds 4,10,18,21 have α-glucosidase inhibitory activities,and 18 has the strongest activity.

Single-cell assay for transposase-accessible chromatin sequencing(scATAC-seq)is a power-ful technique for studying cellular heterogeneity and gene regulatory networks,widely applied in epigenet-ic research.However,the complexity of data analysis workflows and high programming requirements have limited its broader adoption among non-programmer researchers.To address this issue,we developed Sig-nac.UIO,a modular and visual scATAC-seq analysis platform based on the R Shiny framework,integra-ting mainstream tools such as Signac and Seurat.The platform includes ten key modules covering quality control,cell filtering,dimensionality reduction,clustering,differential analysis,cell annotation,path-way enrichment,motif analysis,and transcription factor footprinting.Through a graphical user interface,users can perform full analyses and obtain interactive visualization results.The platform's stability and u-tility have been validated using a public PBMC dataset and it is currently deployed online(https://xula-bgdpu.org.cn/Signac.UIO),providing an efficient and user-friendly tool for single-cell epigenomics re-search.

Objective To analyze the implementation of MPOWER tobacco control policies in different regions and populations in China,as well as the impact of perceptions of tobacco control policies on individual smoking behavior and quit intentions,to promote the fairness of policy implementation and protection for vulnerable groups.Methods A multivariable regression model was constructed utilizing raw data from the China Adult Tobacco Survey to analyze disparities in perceived MPOWER policy implementation among various social demographics and its impact on smoking behavior and quitting intentions.Results Regarding protection from tobacco smoke(P),local economic level,urban-rural divide were significantly correlated with awareness of comprehensive smoking bans.For offering help to quit smoking(O),local tobacco industry revenue and individual age were associated with the doctor's advice for quitting.As to the warning about the harm of tobacco(W),economic level,geography and urban-rural disparity were correlated with the visibility of health warnings.About the tobacco advertising,promotion and sponsorship(E),geography was related to the exposure to tobacco advertisements,local tobacco industry revenue was associated with the tobacco promotion.For tobacco taxes(R),education level and age were significantly correlated with tobacco affordability.People who perceived comprehensive smoking bans(OR=0.69,95%CI:0.59-0.81)was associated with less smoking behavior,while people perceiving tobacco promotional activities(OR=2.51,95%CI:2.00-3.17)were more likely to smoke.Additionally,people who perceived comprehensive smoking bans(OR=1.70,95%CI:1.25-2.31)and health warning(OR=2.09,95%CI:1.48-3.01)had higher intention to quit smoking.Conclusion In economically disadvantaged regions and among specific socially vulnerable groups(such as low-income individuals,rural residents,and the elderly)in China,the perception of tobacco control policy implementation is relatively low,the perception of tobacco control policies can influence smoking behavior and quitting intentions.Legislative and enforcement efforts should be increased targeting these groups with lower perceptions of the policies to enhance the fairness of tobacco control measures.

Aim To investigate the role and underlying mechanisms of transient receptor potential cation chan-nel 6(TRPC6)in epileptogenesis using a kainic acid(KA)-induced mouse model.Methods C57BL/6 and TRPC6-KO(KO)mice were divided into two groups and implanted with cannulas for microinjection of KA(0.03 g·L-1,5 μL)into the lateral ventricle to establish the acute epilepsy model group,with saline injection serving as the control group.The Racine score was used to record the uninterrupted seizure grade of mice within two hours after KA administration.Immunohistochemistry was used to detect neuronal loss and tissue damage in the hippocampus brain region of mice.Immunofluorescence staining,Western blot and qPCR were used to detect the expressions of TRPC6,NLRP3,ASC,Caspase-1,p62,Atg7,Atg5,Beclin-1,LC3b-Ⅱ/LC3b-Ⅰ.in the hippocampus.Results KA induced significant neuronal loss and tissue damage in the hippocampal CA3 brain region of epilep-sy mice,while the expression levels of TRPC6,NL-RP3,ASC and Caspase-1 and other proteins in the hippocampus brain area of epilepsy mice increased,and the protein expression of autophagy-related proteins Atg7,Atg5,Beclin-1,LC3b-Ⅱ/LC3b-Ⅰ increased,while the expression of p62 protein decreased.TRPC6 knockout exacerbated KA-induced epileptogenesis,neuronal injury,inflammatory response and autophagy activation.Conclusion TRPC6 is involved in KA-in-duced epileptigenesis,and the mechanism may be re-lated to the activation of NLRP3 inflammasome-autoph-agy signaling caused by TRPC6 deletion.

Objective To investigate the current situation of the ventilator use and management in secondary and tertiary medical institutions in Sichuan Province to provide references for management and training of ventilator users.Methods A questionnaire survey involving in 235 nurses from 13 secondary and tertiary medical institutions in Sichuan Province was conducted in terms of general information of the respondents,pipeline connection and parameter setup of ventilators,cleaning,sterilization and maintenance of ventilators,identification and treatment of ventilator alarms and hospital-acquired infection prevention and control.Results The results showed 20.4％of the respondents were nurses from critical care departments,and 79.6％of the respondents underwent the training for using the ventilator in their department;91.9％of the respondents could conduct ventilator self-testing by connecting the simulated lungs after the ventilator was switched on;66.4％of the respondents indicated that the initial parameters of the ventilator were set by the doctor;60.9％of the respondents proved that the performance monitoring and routine maintenance of the ventilator were carried out by the nurse;63.4％of the respondents showed disposable lines were commonly used in the departments.There were 89.8％of the respondents said the daily sterilization and management of the ventilator were performed by the nurse;46.0％of the respondents expressed the external surface of the ventilator was disinfected mainly with gamma disinfectant wipes;44.7％of the respondents indicated the external surface of the ventilator was sterilized every day;48.5％of the respondents said the internal airway of the ventilator was disinfected;57.0％of the respondents proved the disinfection was conducted after the expiratory flow sensors were used by any patient.There were 74.5％of the respondents that had paid attention to the ventilator waveform,and by the ventilator waveform only 21.3％were correct in determining whether there was secretion or fluid in the circuit and 22.1％in clarifying whether there was air leakage in the circuit.There were 59.1％of the respondents indicated that the closed suction tube was replaced once every 24 h;71.1％of the respondents could perform airbag pressure monitoring by the special pressure gauge.Conclusion Most of the nurses from secondary and tertiary medical institutions in Sichuan Province can use ventilators correctly,who have problems in disinfection specifications,infection prevention and control or recognition of ventilation waveform.It's suggested the training be strengthened to enhance the clinical nursing staffs in ventilator management.[Chinese Medical Equipment Journal,2025,46(3):75-80]

Aim To investigate the role and underlying mechanisms of transient receptor potential cation chan-nel 6(TRPC6)in epileptogenesis using a kainic acid(KA)-induced mouse model.Methods C57BL/6 and TRPC6-KO(KO)mice were divided into two groups and implanted with cannulas for microinjection of KA(0.03 g·L-1,5 μL)into the lateral ventricle to establish the acute epilepsy model group,with saline injection serving as the control group.The Racine score was used to record the uninterrupted seizure grade of mice within two hours after KA administration.Immunohistochemistry was used to detect neuronal loss and tissue damage in the hippocampus brain region of mice.Immunofluorescence staining,Western blot and qPCR were used to detect the expressions of TRPC6,NLRP3,ASC,Caspase-1,p62,Atg7,Atg5,Beclin-1,LC3b-Ⅱ/LC3b-Ⅰ.in the hippocampus.Results KA induced significant neuronal loss and tissue damage in the hippocampal CA3 brain region of epilep-sy mice,while the expression levels of TRPC6,NL-RP3,ASC and Caspase-1 and other proteins in the hippocampus brain area of epilepsy mice increased,and the protein expression of autophagy-related proteins Atg7,Atg5,Beclin-1,LC3b-Ⅱ/LC3b-Ⅰ increased,while the expression of p62 protein decreased.TRPC6 knockout exacerbated KA-induced epileptogenesis,neuronal injury,inflammatory response and autophagy activation.Conclusion TRPC6 is involved in KA-in-duced epileptigenesis,and the mechanism may be re-lated to the activation of NLRP3 inflammasome-autoph-agy signaling caused by TRPC6 deletion.