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.

Mucosae are the primary sites of causing infectious diseases in human beings. The high transmissibility and mortality rates of infectious diseases pose a serious threat to human health. Mucosal vaccines, which induce both mucosal and systemic immune responses, have emerged as an effective method for preventing or treating infectious diseases. This paper provides an overview of the structure and response characteristics of the mucosal immune system, as well as adjuvants and delivery vectors in vaccine design. It focuses on the multi-dimensional evaluation system of immunoprotective efficacy,covering key indicators such as antibody response, neutralization ability, antibody affinity and tissue-resident memory cells,providing reference for the future development of more effective mucosal vaccines.

ObjectiveTo study the mechanism of compound Xishu granules （CXG） in inhibiting the proliferation of hepatocellular carcinoma cells by regulating ferroptosis. MethodsThe transplanted tumor model of human Huh7 was established with nude mice and the successfully modeled mice were randomized into model， Fufang Banmao （0.21 g·kg^-1）， low-dose （1.87 g·kg^-1） CXG， medium-dose （3.74 g·kg^-1） CXG， and high-dose （7.49 g·kg^-1） CXG groups. Mice were administrated with drinking water or CXG for 28 days， and the body weight and tumor volume were measured every 4 days. Hematoxylin-eosin staining was employed to observe the histopathological changes of tumors. The cell-counting kit-8 （CCK-8） was used to examine the survival rate of Huh7 cells treated with different concentrations （0， 31.25， 62.5， 125， 250， 500， 1 000 mg·L^-1） of CXG for 24 h and 48 h. CA-AM， DCFH-DA， and C11-BODIPY^581/591 fluorescent probes were used to determine the intracellular levels of ferrous ion （Fe²⁺）， reactive oxygen species （ROS）， and lipid peroxide （LPO）， respectively. The colorimetric method was employed to measure the levels of glutathione （GSH） and superoxide dismutase （SOD）. Western blot was employed to determine the protein levels of glutathione peroxidase 4 （GPX4）， transferrin receptor 1 （TFR1）， and ferritin heavy chain 1 （FTH1）， respectively. ResultsIn the animal experiment， compared with the model group， the drug treatment groups showed reductions in the tumor volume from day 12 （P<0.01）. After treatment， the Fufang Banmao and low-， medium-， and high-dose CXG groups had lower tumor volume， relative tumor volume， and tumor weight than the model group （P<0.05）， with tumor inhibition rates of 48.99%， 79.93%， 91.38%， and 97.36%， respectively. Moreover， the CXG groups had lower tumor volume and relative tumor volume （P<0.05 in all the three dose groups） and lower tumor weight （P<0.05 in medium-dose and high-dose groups） than the Fufang Banmao group. Compared with the model group， the drug treatment groups showed reduced number of tumor cells， necrotic foci with karyopyknosis， nuclear fragmentation， and nucleolysis， and the high-dose CXG group showed an increase in the proportion of interstitial fibroblasts. In the cell experiment， compared with the blank group， CXG reduced the survival rate of Huh7 cells in a dose-dependent manner after incubation for 24 h and 48 h （P<0.05）. Compared with the blank group， the RSL3 group and the low-， medium-， and high-dose CXG groups showed a decrease in the relative fluorescence intensity of CA-AM and increases in the fluorescence intensity of DCFH-DA and fluorescence ratio of C11-BODIPY^581/591， which indicated elevations in the levels of Fe²⁺ （P<0.01）， ROS （P<0.05）， and LPO （P<0.01）， respectively. Compared with the blank group， the RSL3 and low-， medium-， and high-dose CXG groups showed lowered levels of GSH and SOD （P<0.05）. In addition， the RSL3 group and the medium- and high-dose CXG groups showed down-regulated expression of GPX4 and FTH1 （P<0.05）， and the low- and high-dose CXG groups presented up-regulated expression of TFR1 （P<0.05）. ConclusionCXG suppresses the proliferation of hepatocellular carcinoma cells by inducing ferroptosis via downregulating the GSH-GPX4 signaling axis and increasing intracellular Fe²⁺and LPO levels.

By examining the records related to the Fengfu （GV 16） acupoint in BIAN Que Heart Book （《扁鹊心书》） compiled by the Song Dynasty physician DOU Cai， this study analyzed various aspects， including the differentiation of conditions treated with Fengfu （GV 16） acupoint， the theoretical foundation for selection of Fengfu （GV 16） acupoint， the application of needling manipulation， and the sensation of obtaining qi during acupuncture. The findings suggest that DOU Cai's approach to utilizing Fengfu （GV 16） acupoint differs from traditional methods， particularly emphasizing the effectiveness of achieving a sensation of heat and numbness. His unique techniques include transverse insertion at Fengfu （GV 16） acupoint and penetrated insertion to Fengchi （GB 20） and Yifeng （TE 17） acupoints. The records of Fengfu （GV 16） acupoint in BIAN Que Heart Book provide a valuable reference for its modern clinical application and further development.

Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.

OBJECTIVE To explore the time windows for postoperative pneumonia in patients undergoing different surgeries,providing evidence-based references for optimizing infection monitoring and prevention and control strategies.METHODS Sociodemographic characteristics,clinical information and surgical details of 263 patients with postoperative pneumonia from four different types of medical institutions between Jan.2019 and Dec.2024 were retrospectively collected.The time windows for postoperative pneumonia in patients undergoing different surgeries were analyzed.RESULTS There were no statistically significant differences in the time windows for post-operative pneumonia among groups in terms of sociodemographic factors and underlying diseases.However,sta-tistically significant differences were observed in the time windows for postoperative pneumonia based on surgery type,incision type,surgical approach and surgery duration(P＜0.05).The average time for the onset of postop-erative pneumonia in 263 patients was 2.00(1.00,7.00)days.The postoperative time windows varied for sur-geries involving different systems.The peak incidence occurred on day 0(16 cases)and day 1(17 cases)af-ter neurological surgery,while the peak incidence for digestive system and orthopedic surgeries was on day 1.The time span for the onset of pneumonia after skin surgeries was wider(0-53 days postoperatively)without a clear peak.In addition,33.33％of cardiovascular system surgery cases developed pneumonia 10 days postoperatively.There were also significant time differences in the diagnostic elements of postoperative pneumonia,with fever and abnormal white blood cell counts appearing earlier(median appearance time length:4.00 days)than lung imaging changes(median appearance time length:7.00 days).CONCLUSIONS This study demonstrates significant time differences in the on-set of postoperative pneumonia and confirms the significant spatiotemporal heterogeneity in the diagnostic elements of postoperative pneumonia.These findings provide a quantitative basis for developing dynamic,surgery-type-spe-cific monitoring protocols and prevention and control measures for postoperative pneumonia.

The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical pro-cedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sample processing,instruments,energy consumed,and the quantities of hazardous materials and waste generated during analytical procedures,need to be considered in the evaluation of the greenness of analytical assays.In this study,we propose a greenness evaluation metric for analytical methods(GEMAM).The new greenness metric is simple,flexible,and comprehensive.The evaluation criteria are based on both the 12 principles of GAC(SIGNIFICANCE)and the 10 factors of sample prep-aration,and the results are presented on a 0-10 scale.The GEMAM calculation process is easy to perform,and its results are easy to interpret.The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.

As people's attention to health continues to increase,the market demand for traditional Chinese medi-cine(TCM)is growing steadily.The quality and safety of Chinese medicinal materials have attracted unprecedent-ed social attention.In particular,the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society.The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM .This not only reflects China's high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision.Basis on this study,by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detec-tion standards in the Chinese Pharmacopoeia 2025 Edition,deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition.Moreo-ver,it interprets the future development directions of the detection of exogenous residues in TCM ,aiming to provide a reference for the formulation of TCM safety supervision policies.

ObjectiveTo observe the effect of Shenshu Fujian decoction on platelet-derived growth factor （PDGF）/naked cuticle homolog 2 （NKD2） /Wnt signaling pathway in rats with chronic renal failure （CRF）. MethodsSixty male SD rats were randomly divided into normal group， model group， Niaoduqing group （5 g·kg^-1）， low-dose Shenshu Fujian decoction group （5.5 g·kg^-1）， medium-dose Shenshu Fujian decoction group （11 g·kg^-1）， and high-dose Shenshu Fujian decoction group （22 g·kg^-1）， with 10 rats in each group. A CRF rat model was established by feeding a 0.5% adenine diet for 21 days. After successful modeling， intragastric administration was given once daily for 28 consecutive days. After treatment， the renal morphology of rats was observed. Serum creatinine （SCr） and blood urea nitrogen （BUN） levels were detected. Hematoxylin-eosin （HE） staining and Masson staining were used to detect renal histopathological changes， and collagen volume fraction （CVF） was calculated. Serum levels of inflammatory markers interleukin （IL）-1β and IL-6 were measured using enzyme-linked immunosorbent assay （ELISA）. The expressions of fibronectin 1 （FN1）， type Ⅰ collagen （ColⅠ）， α-smooth muscle actin （α-SMA）， platelet-derived growth factor receptor-β （PDGFR-β）， NKD2， dishevelled protein 2 （DVL2） and β-catenin in renal tissue were detected by immunohistochemistry and Western blot. ResultsCompared with the normal group， the model group showed significant renal pathological changes， a markedly increased kidney weight/body weight ratio （P<0.01）， significantly elevated CVF （P<0.01）， and notably increased serum levels of SCr， BUN， IL-1β， and IL-6 （P<0.01）. Expression levels of FN1， ColⅠ， α-SMA， PDGFR-β， NKD2， DVL2， and β-catenin in renal tissue were also significantly increased （P<0.01）. Compared with the model group， all treatment groups showed significantly decreased kidney weight/body weight ratios and CVF （P<0.01）， as well as markedly decreased serum SCr， BUN， IL-1β， and IL-6 levels. Protein expression levels of FN1， ColⅠ， α-SMA， PDGFR-β， NKD2， DVL2， and β-catenin in renal tissue were decreased， with more pronounced effects observed in the Niaoduqing， medium-dose， and high-dose Shenshu Fujian decoction groups （P<0.05， P<0.01）. ConclusionShenshu Fujian decoction improves renal function， reduces inflammation， and reverses renal fibrosis in CRF rats， possibly by downregulating the expression of PDGF/NKD2/Wnt signaling pathway-related proteins.