Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

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.

Objective:To investigate the influencing mechanisms and driving pathways of chronic disease management efficiency for older adults under community-and home-based integrated health and social care.Methods:Guided by the Framework for Countries to Achieve an Integrated Continuum of Long-term Care and the Integrated Care for Older People framework,35 cities/counties/districts from eastern,central,and western China were selected.Data envelopment analysis(DEA)was employed to evaluate comprehensive efficiency,complemented by fuzzy-set qualitative comparative analysis(fsQCA)to identify conditional configurations of high-and low-efficiency pathways.Results:DEA identified six of the 35 regions(17.1%)as DEA-efficient(θ=1,S-/S+=0).fsQCA identified three high-efficiency pathways and four low-efficiency pathways.Governance mechanisms emerged as the core condition across all high-efficiency pathways.Low-efficiency pathways exhibited systemic deficiencies,including governance gaps,fragmented financing,and inadequate health information systems.Conclusion:Under integrated long-term care,governance systems form the cornerstone for enhancing chronic disease management efficacy.Cross-sectoral collaboration is critical to institutional integration,while dynamic resource allocation can mitigate technical limitations.Sustainable financing and interoperable health information systems are pivotal to addressing regional disparities.

AIM To evaluate the quality of Croci Stigma from different producing areas.METHODS The analysis was performed on a 25 ℃ thermostatic Waters Acquity UPLC HSS T3 column(2.1 mm× 100 mm,1.8μm),with the mobile phase comprising of 0.1％phosphoric acid-acetonitrile flowing at 0.35 mL/min in a gradient elution manner,and the detection wavelengths were set at 254,440 nm.The UPLC fingerprints were established,after which orthogonal partial least squares discriminant analysis was performed,picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅲ,crocin-Ⅳ contents and chromaticity values(L*,a*,b*,E*ab)were determined,Pearson correlation analysis was adopted in the investigation of correlations between chromaticity values and internal constituent contents.RESULTS There were 14 common peaks in the fingerprints for 22 batches of medicinal materials with the similarities of more than 0.98.Various batches of medicinal materials were clustered into 2 types,7 quality difference components were screened.crocin-Ⅰ content in medicinal materials from different producing areas demonstrated significant differences(P＜0.05);the redder the color of medicinal material,the higher the contents of crocins.Picrocrocin,crocin-Ⅰ,crocin-Ⅱ,crocin-Ⅳ contents displayed highly significant correlations with colorimetric values(P＜0.01),while crocin-Ⅲ content exhibited no significant correlation with the latter(P＞0.05).CONCLUSION This accurate and reliable method can provide references for the quality control and color-quality relationship elucidation of Croci Stigma.

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 investigate the clinical outcome differences between robotic-assisted intramedullary nailing and traditional manual surgery,and to analyze the advantages and feasibility of robotic-assisted intramedullary nail fixation in the treatment of intertrochanteric fractures in elderly patients.Methods From December 2023 to December 2024,elderly patients with intertrochanteric fractures who underwent surgery at Department of Trauma Orthopedics,Beijing Luhe Hospital,Capital Medical University were included.Patients were divided into two groups based on the surgical method.The robotic-assisted group underwent robotic-assisted intramedullary nail fixation,while the traditional group received manual intramedullary nail fixation.Baseline data and observation indicators were collected and compared between the two groups to assess any differences.Results There were no statistically significant differences in baseline data between the two groups(P>0.05).The intraoperative blood loss in the robotic-assisted group was(94.28±9.43)mL,compared to(143.00±11.11)mL in the traditional group(P<0.001).The operative time in the robotic-assisted group was(53.06±9.89)min,while in the traditional group,it was(66.74±10.18)min(P<0.001).The skin incision length for the main nail in the robotic-assisted group was(3.23±0.64)cm,whereas in the traditional group,it was(4.03±0.79)cm(P<0.01).Postoperative hemoglobin levels in the robotic-assisted group decreased by(12.63±4.27)g/L,compared to(17.29±4.32)g/L in the traditional group(P=0.018).At 6 months postoperatively,the Harris hip scores in the robotic-assisted group showed 30 cases of excellent,10 good,and 3 poor outcomes,while in the traditional group,there were 22 excellent,15 good,and 6 poor cases(P=0.198).Conclusion Robotic-assisted intramedullary nailing for intertrochanteric fractures offers advantages such as minimally invasive and precise procedures,shorter operative times,and reduced blood loss.Compared to traditional surgical methods,it demonstrates certain benefits in reducing postoperative complications in elderly patients.

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.