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.

ObjectiveTo investigate the mechanism by which Wumeiwan suppresses the development and progression of colorectal cancer（CRC） through the regulation of fatty acid metabolic reprogramming， thereby providing new experimental evidence for the prevention and treatment of CRC. MethodsA total of 120 C57BL/6 mice were randomly divided into the blank group， model group， Wumeiwan high-， medium-， and low-dose groups（54， 27， 13.5 g·kg^-1）， and the mesalazine group（0.01 g·kg^-1）， with 20 mice in each group. Except for the blank group， all mice were subjected to azoxymethane（AOM）/dextran sulfate sodium（DSS） treatment to establish an inflammation-associated CRC model. One week after AOM injection， mice in the treatment groups received intragastric administration of the designated drugs， while the blank and model groups received an equal volume of purified water， continuing until 20 d after the intervention endpoint. Hematoxylin-eosin（HE） staining was used to observe colonic histopathological alterations， and immunohistochemistry for vascular endothelial growth factor（VEGF） was performed to evaluate neovascularization and tumor invasion. Metabolomics combined with Kyoto Encyclopedia of Genes and Genomes（KEGG） and metabolite set enrichment analysis（MSEA） was applied to identify key CRC-related metabolic pathways， which were further validated by transcriptomic Gene Ontology（GO） enrichment and gene heatmap analysis. Subsequently， Western blot was performed to determine the expression levels of core proteins in these pathways， and immunofluorescence was used to analyze their localization and co-expression patterns in tissues， thereby elucidating the mechanism of Wumeiwan from multiple biological dimensions. ResultsCompared with the blank group， mice in the model group exhibited a significant decrease in body weight and a significant increase in the disease activity index（DAI） score（P<0.05）， with pronounced colonic mucosal damage accompanied by aggravated tumor invasion. Compared with the model group， Wumeiwan intervention markedly improved body weight loss and reduced DAI score， attenuated mucosal injury， and significantly decreased VEGF expression level（P<0.05）. Multi-omics analysis revealed that differential metabolites and genes across groups were commonly enriched in fatty acid metabolism， fatty acid biosynthesis， and other lipid-related pathways. Relative to the blank group， the model group showed significant upregulation levels of fatty acid synthesis-related genes， including sterol regulatory element-binding protein 1（SREBP1）， fatty acid synthase（FASN）， stearoyl-CoA desaturase 1（SCD1）， as well as saturated fatty acids（P<0.05）. Compared with the model group， treatment with Wumeiwan significantly reduced the expression of key genes involved in fatty acid metabolic pathways， including SREBP1， FASN， and SCD1（P<0.05）. Western blot results further confirmed that proteins in this pathway were significantly elevated in the model group， whereas they were markedly downregulated following Wumeiwan treatment（P<0.05）. Immunofluorescence analysis demonstrated enhanced co-localization of SREBP1 with the cancer-associated fibroblast（CAF） marker α-smooth muscle actin（SMA） in the model group， whereas this co-localization signal was attenuated after Wumeiwan intervention（P<0.05）. ConclusionWumeiwan can improve survival outcomes and alleviate colonic pathological damage in CRC mice， its therapeutic mechanism may be closely associated with the regulation of fatty acid metabolic reprogramming mediated by the SREBP1/FASN/SCD1 signaling pathway.

This study investigated the prevalence of hepatitis E virus(HEV)in rodents within the Inner Mongolia Autonomous Region.In 2024,liver,spleen,kidney,and lung tissue samples were collected from rodents in 11 leagues and cities across the Inner Mongolia Autonomous Region,including Hohhot,Baotou,Hulunbuir,Xing'an League,Tongliao,Chifeng,Xilin Gol League,Ulan-qab,Ordos,Bayannur,and Wuhai.Nested PCR(RT-PCR)was used to detect the conserved regions of the HEV open reading frame 1(ORF1)gene.The RT-PCR-positive products were sequenced,and phylogenetic and homology analysis of the obtained sequences was performed.A total of 816 rodents were captured in this investigation,including 319 Rattus norvegicus(39.09%,319/816),206 Musmusculus(25.25%,206/816),and 140 Mongolian gerbils(17.16%,140/816).The HEV infection rate among rodents in the In-ner Mongolia region was 3.68%(30/816).Sequencing of the RT-PCR-positive results and analysis of the nucleotide sequences yielded 30 HEV-positive rodent samples.Phylogenetic analysis identified these sequences as belonging to the HEV-C1 genotype.The prevalence of HEV was observed in brown rats(Rattus norvegicus)in five leagues and cities within the Inner Mongolia region,includ-ing Xing'an League,Chifeng City,Hulunbuir City,Xilin Gol League,and Tongliao City,with infection rates of 16.67%,10.00%,5.98%,3.30%,and 2.50%,respectively.Brown rats,a species of house rats,frequently inhabit areas near human residences and have close interactions with humans and livestock.Studies have shown that multiple subtypes of HEV can cause zoonotic infections.Therefore,strengthening the monitoring of pathogens carried by rodents in residential environments and optimizing the prevention and control of rodent-borne diseases will be essential.Timely dissemination of relevant infectious disease knowledge to local communities will also be crucial,to decrease the risk of human infection.

Objective To observe the effects of a stepped early activity program combined with lower limb joint rehabilitation devices in mechanically ventilated patients in the intensive care unit(ICU).Methods Sixty mechanically ventilated patients admitted to the ICU of Tianjin First Central Hospital from October 2022 to June 2023 were selected as study subjects and randomly divided into an intervention group(n=30)and a control group(n=30)using a random number table.The control group received routine rehabilitation nursing combined with lower limb joint rehabilitation devices,while the intervention group was additionally treated with the stepped early activity program.The duration of mechanical ventilation,length of ICU stay,incidence of delirium,Medical Research Council(MRC)muscle strength scores,phase angle(PA),and skeletal muscle mass index(SMI)were compared between the two groups.Results The intervention group showed significantly shorter durations of mechanical ventilation and the length of ICU stay compared to the control group[mechanical ventilation time(days):9.20±4.51 vs.11.73±4.59,the length of ICU stay(days):10.73±5.37 vs.14.00±6.03,both P<0.05].Post-intervention MRC muscle strength scores,PA,and SMI significantly increased in both groups,with greater improvements observed in the intervention group[MRC muscle strength score:54.17±2.10 vs.50.17±3.51;PA(°):5.80±0.60 vs.5.49±0.54;SMI(kg/m2):6.87±0.46 vs.6.62±0.45,all P<0.05].No statistically significant difference was found in delirium incidence between the two groups[26.7%(8/30)vs.33.3%(10/30),P>0.05].Conclusion The combination of a stepped early activity program and lower limb joint rehabilitation devices effectively shortens mechanical ventilation time and the length of ICU stay,restores muscle strength,and promotes recovery in mechanically ventilated ICU patients,demonstrating significant clinical value.

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.

This study investigated the prevalence of hepatitis E virus(HEV)in rodents within the Inner Mongolia Autonomous Region.In 2024,liver,spleen,kidney,and lung tissue samples were collected from rodents in 11 leagues and cities across the Inner Mongolia Autonomous Region,including Hohhot,Baotou,Hulunbuir,Xing'an League,Tongliao,Chifeng,Xilin Gol League,Ulan-qab,Ordos,Bayannur,and Wuhai.Nested PCR(RT-PCR)was used to detect the conserved regions of the HEV open reading frame 1(ORF1)gene.The RT-PCR-positive products were sequenced,and phylogenetic and homology analysis of the obtained sequences was performed.A total of 816 rodents were captured in this investigation,including 319 Rattus norvegicus(39.09%,319/816),206 Musmusculus(25.25%,206/816),and 140 Mongolian gerbils(17.16%,140/816).The HEV infection rate among rodents in the In-ner Mongolia region was 3.68%(30/816).Sequencing of the RT-PCR-positive results and analysis of the nucleotide sequences yielded 30 HEV-positive rodent samples.Phylogenetic analysis identified these sequences as belonging to the HEV-C1 genotype.The prevalence of HEV was observed in brown rats(Rattus norvegicus)in five leagues and cities within the Inner Mongolia region,includ-ing Xing'an League,Chifeng City,Hulunbuir City,Xilin Gol League,and Tongliao City,with infection rates of 16.67%,10.00%,5.98%,3.30%,and 2.50%,respectively.Brown rats,a species of house rats,frequently inhabit areas near human residences and have close interactions with humans and livestock.Studies have shown that multiple subtypes of HEV can cause zoonotic infections.Therefore,strengthening the monitoring of pathogens carried by rodents in residential environments and optimizing the prevention and control of rodent-borne diseases will be essential.Timely dissemination of relevant infectious disease knowledge to local communities will also be crucial,to decrease the risk of human infection.

Clinical teaching managers are the designers, implementers, and supervisors of clinical medical education. Their competence level directly affects the quality of hospital teaching management and clinical medical education. The competence evaluation systems for medical education managers in countries such as the United States and the United Kingdom are well-established, which provides a reference for the competence evaluation of clinical teaching managers in China. This research systematically reviews the construction process and current situation of the competence evaluation systems for medical education managers in the world, and summarizes the basis, methods, and dimensions of competence evaluation. According to the actual situation of clinical teaching management, suggestions were put forward, including developing systematic scientific evaluation tools, carrying out competence-oriented training and assessment, focusing on student-centered education, and creating a career path of sustainable development.

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.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.