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.

BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

OBJECTIVE To study the efficacy of Tianjiang xueshuantong pills in the treatment of coronary heart disease. METHODS In accordance with the common pathogenesis of coronary heart disease， acute myocardial ischemia model， hyperlipidemia model， blood stasis model， and carotid artery thrombosis model were established using Wistar rats or SD rats as the experimental subjects. The effects of Tianjiang xueshuantong pills administered at high， medium， and low doses （0.6， 1.2 and 2.4 g/kg） on hemodynamic parameters and myocardial enzyme markers [lactate dehydrogenase （LDH）， creatine kinase-MB （CK- MB）]， oxidative stress factors [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione （GSH）]， inflammatory cytokines [tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， IL-1β， monocyte chemotactic protein-1 （MCP-1）， intercellular adhesion molecule-1 （ICAM-1）]， myocardial infarction percentage， serum lipid indexes [total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）]， platelet aggregation function 话：022-84845240。E-mail：jiangx@tjipr.com [maximum aggregation rate （MAR）]， and thrombus formation indexes [thrombosis time， thrombus mass， thrombus protein content， plasminogen activator inhibitor-1 （PAI-1）， and tissue-type plasminogen activator （t-PA）] were evaluated in the rat models. RESULTS In myocardial ischemia tests， Tianjiang xueshuantong pills significantly reduced the percentage of myocardial infarction and the levels of CK-MB， LDH， MDA， GSH， IL-6， TNF-α， IL- 1β， and MCP-1 in serum （P＜0.05 or P＜0.01）. In hyperlipidemia tests， high dose of Tianjiang xueshuantong pills significantly reduced the serum levels of TC， LDL and significantly increased the level of HDL in rats after 2 weeks and 4 weeks of administration. In blood stasis tests， different doses of Tianjiang xueshuantong pills significantly reduced MAR of rats （P＜0.01）. In artery thrombosis tests， high dose of Tianjiang xueshuantong pills significantly prolonged the time of thrombosis formation （P＜ 0.01）， significantly reduced the weight and protein content of thrombus and the level of PAI-1 in serum （P＜0.01）. CONCLUSIONS Tianjiang xueshuantong pills exert therapeutic effects on coronary heart disease through multi-dimensional synergistic actions， including anti-myocardial ischemia， lipid-lowering， and anti-thrombotic effects.

Objective:To conduct a scoping review of research on the application of mobile health technology in patients undergoing bariatric and metabolic surgery, providing a reference for related practice.Methods:PubMed, Embase, Web of Science, CINAHL, Wanfang data, China National Knowledge Infrastructure, VIP, and China Biology Medicine disc were searched using terms including mobile, smart, remote, internet, bariatric, and metabolic. The search timeframe was from database inception to October 30, 2024. According to inclusion and exclusion criteria, literature was screened, and two researchers independently extracted, summarized, and analyzed the information.Results:A total of 31 studies were included. Mobile health technology was mainly applied in the form of smartphone applications for patients undergoing bariatric and metabolic surgery. The main content included postoperative dietary management, exercise guidance, and health data monitoring. The main evaluation elements involved effectiveness (behavioral change and weight loss outcomes, readmission rate, quality of life, psychological status, adherence, and economic benefits) and patient satisfaction.Conclusions:Currently, mobile health technology is mainly used via smartphone applications to manage diet and exercise for postoperative bariatric patients. It can improve postoperative weight loss outcomes, reduce negative emotions, enhance adherence, and achieve good self-management. In the future, multidisciplinary teams should be established to conduct large-scale high-quality studies, continuously improve the forms and content of mobile health management, and implement comprehensive preoperative and postoperative management for bariatric patients.

To perform the phylogenetic characterization of an isolated porcine rotavirus(PoRV)and investigate its pathogenicity in suckling mice and piglets.A G4P[23]genotype PoRV strain JSJR2023 was successfully isolated from the diarrheic piglet feces through propagation in MA104 cells.The viral proliferation kinetics were analyzed using TCID50 assays,followed by complete genome sequencing through Sanger sequencing platforms.Comprehensive genotyping and phylogenetic reconstruction were conducted using MEGA7.0 with maximum likelihood algorithms.Pathogenicity was assessed in the following animal models:5-day-old C57BL/6 mice and 3-day-old piglets.Multidimensional evaluation included clinical monitoring(diarrhea scoring,growth parameters),virological detection,and histopathological analysis of intestinal tissues.The virus strain JSJR2023 could replicate efficiently in MA104 cells,achieving peak titers of 107.5 TCID50/mL.Whole genome genotype analysis showed that the strain belonged to G4-P[23]-I5-R1-C1-M1-A8-N1-T1-E1-H1.Phylogenetic analysis indicated that the VP3 and NSP4 genes of JSJR2023 strain were most closedrelated to human species rotaviruses,suggesting genetic reassortment between human and porcine RV strains.The animal experiments in suckling mice showed that the JSJR2023 strain infection caused diarrhea symptoms,intestinal edema and congestion,and shedding of intestinal villus epithelial cells.The pathogenicity experiments in piglets showed that compared with the control group,the challenged group of pig-lets had severe diarrhea symptoms,accompanied by reduced appetite and listlessness.Post-mortem examination revealed that the intes-tines were significantly thinner,congested,and filled with yellow watery contents.The challenged piglets showed typical pathological changes such as thinning of the intestinal wall and shortening and shedding of intestinal villi.In conclusion,this study successfully iso-lated a human-porcine recombinant G4P[23]PoRV strain and established the infection models in suckling mice and piglets,providing important tools for investigating the pathogenic mechanism of PoRV,evaluating vaccines and developing antiviral drug.

Objective To investigate the correlation between G protein-coupled receptor family C group 6 member A(GPRC6A)gene polymorphisms and their expression and pulmonary infections in elderly patients with chronic heart failure(CHF).Methods 138 elderly CHF patients admitted to the Xianyang First People's Hospital from January 2021 to January 2024 were selected as the research subjects,and were divided into an infected group(n=42)and an uninfected group(n=96)based on their lung infection status.Polymerase chain reaction(PCR)was used to detect polymorphisms at the rs6901250 and rs1606365 loci of the GPRC6A gene.The allele and genotype frequency distributions of the infected and uninfected groups were compared.Logistic regression modeling was used to analyze the s6901250 and rs1606365 loci under three genetic models(co-dominant,dominant and reces-sive)and lung infections in elderly patients with CHF.Real-time fluorescence quantitative PCR(RT-qPCR)method was used to detect the expression level of GPRC6A gene.The predictive value of the mRNA expression level of the GPRC6A gene for the development of pulmonary infections in elderly patients with CHF was analyzed by applying the receiver operator characteristic(ROC)curve.Results The distribution of genotypes at loci rs6901250 and rs1606365 of the GPRC6A gene in both the infected and uninfected groups of the lungs of elderly CHF patients conformed to the Hardy-Weinberg equilibrium law(χ2=0.199～0.376,all P>0.05),which was representative of the population.Compared with the uninfected group,the frequency of allele A at locus rs6901250(57.14%vs 41.67%)was significantly higher in the infected group,Allele G(54.76%vs.37.50%)and genotype GG(14.06%vs 29.99%)frequencies were significantly higher at locus rs1606365,and the differences were statistically significant(χ2=5.628,7.114,6.849,all P<0.05).At locus rs6901250,in the co-dominant model(GG vs AA)and the dominant model(GA+AA vs GG),the elderly CHF patients with AA genotype the risk of lung infection was higher than that of GG genotype(OR=1.753,1.546,all P<0.05);.rs1606365 locus showed that the risk of lung infection was higher than that of CC genotype in el-derly CHF patients with GG genotype under all three genetic models of co-dominant model(CC vs GG),dominant model(CG+GG vs CC)and recessive model(CG+CC vs GG)(OR=1.833,1.741,0.695,all P<0.05).The mRNA expression level of GPR-C6A gene in the lung-infected group of elderly CHF patients(1.43±0.35)was significantly higher than that in the uninfected group(1.02±0.21),and the difference was statistically significant(t=8.515,P<0.001).The results of the ROC curve analysis showed that the GPRC6A gene expression level predicted lung infection in elderly CHF patients with an AUC value of 0.895,a cut-offvalue of 1.37,and sensitivity and specificity of 85.7%and 66.7%,respectively.Conclusion The AA genotype at the rs6901250 locus and the GG genotype at the rs1606365 locus of the GPRC6A gene increased the risk of developing lung infec-tions in elderly patients with CHF.MRNA expression levels of the GPRC6A gene were elevated in the infected group,and its ex-pression level could be used as a predictive indicator for the development of lung infections in elderly patients with CHF.

Objective:To evaluate the relevant factors to optimize the learning curve and the impact of the basic skills of endoscopic technology on the learning curve of gasless transaxillary posterior endoscopic thyroidectomy.Methods:A retrospective analysis was performed to evaluate the clinical outcomes of 50 patients who underwent Glandular Ultrasound-Assisted (GUA) thyroid surgery by a surgeon with a background in endoscopic thyroid surgery via the thoracic-areolar approach, and 50 patients operated on by a surgeon without such experience at the Thyroid Surgery Department of Jilin University China-Japan Union Hospital from Apr. to Dec. 2023. The patients were divided into two groups: the Endoscopic Experience Group and the Non-Endoscopic Experience Group. The Cumulative Sum Control Chart (CUSUM) was applied to construct learning curves for both groups, dividing the technical exploration period from the mastery period. The analysis compared the surgical time, postoperative first-day drainage volume, number of central lymph nodes dissected rates, and postoperative complications between the two groups and across the two phases.Results:The analysis of the learning curve revealed that the inflection point of the Endoscopic Experience Group was 15, while of the Non-Endoscopic Experience Group was 18. The learning curve was divided into the technical exploration stage and the proficient mastery stage. The operative time of technical exploration stagde was significantly longer than of proficient mastery stage of both group (183.46±36.13min vs.144.40±26.14min, P<0.001; 186.89±48.91min vs.131.59±22.90min; P<0.001) . The operative time in the proficient mastery stage of the Endoscopic Experience Group was longer than that of the Non-Endoscopic Experience Group (144.40±26.15min vs. 131.59±22.90min, P<0.05) . The postoperative drainage volume in the Endoscopic Experience Group was lower than that in Non-Endoscopic Experience Group in both stages (65.40±32.48mL vs.93.22±30.67mL, 57.40±15.35mL vs.78.50±28.30mL, P<0.05) , and the postoperative drainage volume in the proficient mastery stage of the Non-Endoscopic Experience Group was significantly lower than in the technical exploration stage (93.22±30.67mL vs.78.50±28.30mL, P<0.05) .No significant differences in central lymph node dissection numbers or postoperative complications were observed between the groups at both stages. Conclusions:There is a specific learning curve in the early stage of gasless transaxillary posterior endoscopic thyroidectomy. After crossing the learning curve, the operation time is obviously shortened with the improvement of the operator's surgical technique.Having a basic understanding of endoscopic technology in the early stage can reduce the occurrence of postoperative drainage, but has a minimal impact on the learning curve.

Objective To systematically evaluate malnutrition risk factors in diabetic foot patients through systematic review and inform evidence-based nutritional interventions.Methods A top-down search of the literature on risk factors for malnutrition in patients with diabetic foot was conducted according to the"6S"pyramid model,using a computerized decision-making system,clinical guideline websites,professional association websites and databases,with a timeframe of up to March 2025 for the search.Totally 2 researchers independently performed literature screening,quality assessment,and data extraction.Meta-analysis was conducted using Stata 18 software.Results Totally 23 studies with a total sample size of 5 068 cases were included.There were 10 influencing factors being extracted,including age(OR=2.709),BMI(MD=0.709),duration of diabetes mellitus(OR=2.589),glyco-sylated hemoglobin(OR=2.190),albumin(MD=0.578),hemoglobin(OR=2.948),infection(OR=1.816),C-reactive protein(OR=2.228),Wagner classification of diabetic foot(OR=4.620)and degree of self-care(OR=0.220).The incidence of malnutrition in DFU patients who were assessed by the MNA-SF tool,the MNA tool and GLIM tool were 52.2％,70.2％and 41.4％.Conclusion The incidence of malnutrition in DFU patients is relatively high.Healthcare providers should continuously monitor the nutritional status of diabetic foot patients and implement personalized intervention plans to prevent malnutrition.

Objective:To explore the epidemiological characteristics, imaging findings, pulmonary function changes, dust exposure situations, and treatment outcomes of accelerated silicosis through an analysis of existing literature.Methods:In December 2024, relevant literature from January 1, 1965 to December 15, 2024 was retrieved through the China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database, EMbase, and PubMed databases. Keywords included "rapidly progressive silicosis" "accelerated silicosis" "subacute silicosis""artificial stone" and related terms. By incorporating, analyzing, and retrieving data from literatures, a comprehensive review of the epidemiology, clinical features, treatment options, and prognosis of fast forward silicosis was conducted.Results:A total of 72 literatures were included, including 23 cohort studies, 28 case reports, 3 case-control studies, and 18 cross-sectional studies. The average age of all 1794 patients was 33.67 years, with an average dust exposure duration of 5.58 years. The primary occupations associated with accelerated silicosis were stone processing, mining, and artificial quartz stone manufacturing. Imaging findings predominantly included small nodules, ground-glass opacities, and massive fibrosis. Antifibrotic treatment at the early stage of the disease could clearly delay disease progression. However, dust concentrations in workplaces were significantly above safety limits, with inadequate protective measures.Conclusion:Accelerated silicosis is characterized by its rapid onset, swift progression, and unfavorable prognosis. However, it has not garnered adequate attention in the present context. Reliable standard and guidelines are urgently needed to guide clinical diagnosis and treatment.