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: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

The aim of this study was to understand the internal genetic diversity and population history dynamics of ticks in Inner Mongolia,to provide data for designing effective vector control programs and revealing ticks'transmission mechanisms.From 2022 to 2023,the manual collection method was used to collect samples in Inner Mongolia.The 16S rDNA and COI gene sequences of ticks were used to identify Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus,and analyze the sequence characteristics and genetic diversity within the populations.Base composition analysis indicated that the average A+T content of the 16S rDNA gene and CO I gene in the three ticks was significantly higher than that of C+G.Moreover,22 haplotypes of the COI gene and 12 haplotypes of the 16S rDNA sequence were identified in Hyalomma marginatum.Eleven haplotypes were identified according to the COI gene,and nine haplotypes were identified according to the16S rDNA sequence of Haemaphysalis concinna.Two haplotypes were identified on the basis of the COI gene,and six haplotypes were identified on the basis of the 16S rDNA sequence of Ar gas persicus.The minimum 16S rDNA haplotype diversity was 0.264 for Ar gas persicus and 0.579 for the other two species.The nucleotide diversity of the three tick species was less than 0.05.Tajima's val-ue and Fu's Fs value of the neutrality test were negative.Base saturation substitution analysis indicated that neither of the two genes in the three tick species reached saturation.The phylogenetic tree revealed that Hyalomma marginatum,Haema physalis concinna,and Ar gas persicus in Inner Mongolia independently aggregated into branches.In conclusion,the base content of Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus genes in Inner Mongolia was consist-ent with the characteristics of insect mitochondrial DNA content.Furthermore,the three tick populations showed rapid evolu-tionary population expansion,and the phylogeny of three tick species showed independent aggregation into clades,with no pop-ulation isolation.

AIM To study the chemical constituents from Asteris Radix et Rhizoma and their anti-inflammatory activities.METHODS The extract from Asteris Radix et Rhizoma was isolated and purified by column chromatography and high performance liquid chromatography,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Thirteen compounds were isolated and identified as(Z)-9,10,11-trihydroxy-12-octadecenoic acid(1),tianshic acid(2),6,6-dimethyl-2-methlenebicyclo[3.1.1]hept-3-O-(6-O-apiofuranosyl)-β-D-glucopyranoside(3),ent-16β,17-dihydroxy-kauran-19-oic acid(4),ent-17-hydroxy-19-kauranoic acid(5),7β,17-dihydroxy-16α-ent-kauran-19-oic acid 19-O-β-D-glucopyranoside ester(6),paniculoside Ⅳ(7),thomimarine A(8),cyclo-(S-Pro-R-Leu)(9),4,5-di-O-caffeoylquinic acid 1-methyl ether(10),methyl 3,5-di-O-caffeoyl quinate(11),5-acetyl-3β-hydroxy-2β-(1-hydroxyisopropyl)-2,3-dihydrobenzofurane(12),4-ally-2,6-dimethoxyphenyl glucoside(13).Compounds 1 and 3-12 had inhibition on the release of NO in RAW264.7 cells,and 4-6,8,10-12 were better than the positive control.CONCLUSION Compounds 1,6,8-9 are isolated from Compositae family for the first time,and 2-5,7,10 and 11-13 are first isolated from this plant.Compounds 1,3-12 have anti-inflammatory activities.

Objective To propose a ventilator failure probability prediction method based on kernel ridge regression(KRR).Methods Firstly,the failure interval data of ventilators was collected and preprocessed to remove outliers.Secondly,the median rank method was used to estimate the failure probability.Finally,using the time data as the feature variable and the failure probability value as the target variable,a KRR model was established and trained by selecting the optimal kernel function and hyperparameter combination from radial basis kernel function,linear kernel function,polynomial kernel function,and S-type kernel function through grid search and cross-validation methods to predict ventilator failures.To verify the performance of the KRR model in predicting ventilator failure probability,it was compared with Weibull and its extended models.Results KRR achieved a coefficient of determination of 0.993 5,a mean squared error of 5.399 5×10-4,a root mean squared error of 0.023 2 and a mean absolute error of 0.018 3,outperforming Weibull and its extended models in prediction accuracy and error control.Conclusion The failure probability prediction method for ventilators based on KRR demonstrates exceptional performance in prediction accuracy and error control,and thus holds great potential for application.[Chinese Medical Equipment Journal,2025,46(5):73-77]

Objective:To investigate the immuno-inflammatory regulatory effects of the Qing Gan San Jie Xiao Ying Formula(QGSJXYF)on Hashimoto's thyroiditis(HT)by modulating thyroid cell-derived exosomes to provide experi-mental evidence for its immunomodulatory mechanisms.Methods:Nthy-ori-3-1 thyroid cells were treated with QGSJXYF-medicated serum,with untreated cells serving as controls.Exosomes from both groups were extracted and analyzed using nanoparticle tracking analysis(NTA),transmission electron microscopy(TEM),and Western blot to assess concentration,size distribution,morphology,and the expression of characteristic exosomal markers.An inflammatory model of human T lymphocytes(H9)was established and co-incubated with normal exosomes(EXO-C group)or QGSJXYF-treated exosomes(EXO-T group).The levels of inflammatory cytokines in H9 cells were measured using Western blot(WB)and ELISA.Results:Exosome characterization showed that the particle concentration of Nthy-ori-3-1 cell-derived exosomes in both the control and QGSJXYF groups ranged from 1×109 to 1×1011/mL,with particle diameters between 80～300 nm.The exosomes exhibited a typical spherical or cup-shaped morphology with positive expression of TSG101,CD63,and HSP70.Compared with the inflammation model group and the EXO-C group,the EXO-T group significantly reduced the intracellular expression of IL-17A protein in H9 cells(P<0.05)and suppressed IL-17 and IL-6 levels in the cell supernatant(P<0.01).Conclusion:QGSJXYF may exert its anti-inflammatory and thyroid-protective effects by modulating the functional state of thyroid cell-derived exosomes,regulating the inflamma-tory microenvironment,and inhibiting the expression of inflammatory cytokines associated with Hashimoto's thyroiditis.

Objective To investigate the effects of TEK receptor tyrosine kinase(Tie2)L914F mutation on the biological behavior of vascular endothelial cells and the changes of related signaling pathways in patients with venous malformations.Methods Gene sequen-cing was used to detect Tie2-L914F mutations in venous malformations.HE staining and immunohistochemical staining were used to de-tect the expression of platelet derived growth factor subunit B gene(PDGFB)and α-smooth muscle actin(α-SMA)in venous malfor-mations caused by the mutation.Lentivirus overexpressing Tie2-wild type(Tie2-WT),Tie2-L914F and Tie2-GFP(green fluorescent protein,GFP)infected human umbilical vein endothelial cells(HUVECs).Real-time fluorescence quantitative PCR was used to detect the expression level of Tie2 in endothelial cells expressing exogenous Tie2 and Flag-tagged protein Tie2 protein was detected by western blotting to verify transfection efficiency.The proliferation,apoptosis,migration and tube-forming ability of the cells were determined by CCK-8,flow cytometry,Transwell migration assay and Matrigel matrix gel tube-forming assay.Western blotting was used to detect the expression levels of Protein Kinase B(PKB/AKT),FOXO1 and their phosphorylation,and the expression level of PDGFB was detec-ted by ELISA.Results The number of patients with venous malformations with L914F mutations was about 33.3％.HE and immuno-histochemical staining showed that the expressions of PDGFB and α-SMA were significantly down-regulated in venous malformation tis-sues with Tie2-L914F mutation,and were positively correlated with the decrease in cell coverage of the tube wall.Compared with Tie2-WT endothelial cells,the apoptosis number of Tie2-L914F endothelial cells was significantly reduced,while the proliferation and mi-gration ability was significantly increased,and the tube-forming ability was significantly decreased.Western blotting and ELISA showed that the phosphorylation levels of AKT and FOXO1 downstream of Tie2 signaling pathway in endothelial cells expressing Tie2-L914F were significantly increased,and the expression level of PDGFB was significantly decreased.Conclusion In venous malformations,Tie2-L914F mutation may downregulate the expression of PDGFB through AKT signaling pathway,which affects the biological behavior of vascular endothelial cells.

Objective:This study applies an integrated SWOT-CLPV framework combined with stakeholder analysis to systematically assess the strengths,weaknesses,opportunities,and threats of China's disease control inspector system,while identifying its control factors,leverage points,key problems,and vulnerabilities.Methods:Drawing on literature review,policy document analysis,and expert interviews with seven public health professionals,we extracted and categorized SWOT elements.A CLPV interaction analysis was conducted alongside stakeholder mapping to evaluate internal dynamics and systemic risks.Results:The inspector system demonstrates strengths in policy innovation and medical-public health integration,with external opportunities stemming from rising public health awareness and digital health advancements.However,the system faces weak endogenous momentum,limited leverage,and prominent control constraints and problem-prone areas,especially among grassroots institutions and inspectors themselves.Cross-sectoral coordination barriers and uneven local implementation contribute to significant institutional vulnerabilities.Conclusion:To enhance implementation and resilience,the system requires capacity building for key actors,improved governance structures,incentive and evaluation reforms,and strengthened coordination mechanisms to support the sustained and adaptive development of public health supervision.

Non-small cell lung cancer(NSCLC)constitutes the largest portion of lung cancer overall,with high incidence and mortality rates.Apoptosis,is a hot focus in the clinical treatment of NSCLC,its main pathways include the extrinsic death receptor pathway,intrinsic mitochondrial apoptosis pathway and endoplasmic reticulum stress pathway,collectively regulating the cellular apoptosis process.Traditional Chinese medicine(TCM)has significant efficacy in the treatment and prognosis of NSCLC,with advantages such as boosting the body's resistance and less adverse drug reactions.Studies have shown that various individual Chinese herbal medicines and compound formulas can treat NSCLC through the apoptosis pathway,alleviating the adverse drug reaction of radiotherapy and chemotherapy.Based on this,this article summarizes recent domestic and international literature,focusing on apoptosis,to summarize the research progress of TCM in treating NSCLC by regulating apoptosis,aiming to provide reference for clinical treatment for NSCLC.