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.

OBJECTIVE To investigate the potential mechanism by which Juanxiao decoction improves bronchial asthma （hereinafter referred to as “asthma”） based on the nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3） inflammasome signaling pathway. METHODS Female SD rats were randomly assigned to normal group， model group and Juanxiao decoction low-， medium- and high-dose groups （0.36， 0.72 and 1.44 g/kg， calculated based on crude drug weight）， as well as positive control group （Dexamethasone acetate tablets， 0.2 mg/kg）， with 10 rats in each group. Except for the normal group， asthma models were established in the remaining groups via intraperitoneal injection of ovalbumin combined with aluminum hydroxide， followed by nebulized inhalation of ovalbumin. On day 14 of the experiment， rats in each group received intragastric administration of the corresponding solution or normal saline， once a day， for 7 consecutive days. Following the final administration， the following parameters were measured in each group： lung function indexes （forced vital capacity， forced expiratory volume in 0.3 second， peak expiratory flow）， serum levels of inflammatory markers （interleukin-1β， interleukin- 18）， and the percentages of inflammatory cells （lymphocytes， eosinophils， neutrophils） in bronchoalveolar lavage fluid. Histopathological changes in lung tissue were observed， and the protein and mRNA expressions of nuclear factor-kappa B （NF- κB）， NLRP3 and caspase-1 in lung tissue were detected. RESULTS Compared with the normal group， pathological changes such as alveolar wall thickening and inflammatory cell infiltration were observed in rats in the model group. All pulmonary function indicators were significantly reduced in rats in the model group and the administration groups. The levels of inflammatory markers， the percentages of inflammatory cells， and the protein and mRNA expressions of NF-κB， NLRP3 and caspase-1 were significantly elevated or up-regulated （P＜0.05）. Compared with the model group， pathological changes in rats in each dosage group of Juanxiao decoction were significantly alleviated， and all quantitative indicators showed dose-dependent improvements （P＜0.05）. CONCLUSIONS Juanxiao decoction can reduce airway inflammatory responses in asthmatic rats， alleviate lung function impairment， and improve pathological changes such as inflammatory cell infiltration. Those effects may be related to the inhibition of the NLRP3 inflammasome signaling pathway.

Objective:To investigate the current status of standardized residency training (SRT) teaching activities at Zhongshan Hospital affiliated to Fudan University, and to explore optimization strategies.Methods:We collected behavioral data from the SRT course selection platform and resident questionnaire survey data throughout 2024. Descriptive analysis, chi-square test, Mann-Whitney U test, and multivariable logistic regression analysis were performed. Results:A total of 170 teaching sessions were conducted in 2024, with interactive practice-based sessions accounting for 42.35% and lecture-based sessions accounting for 47.06%. According to 536 questionnaires, residents' overall satisfaction with teaching activities scored 87.83 points (high satisfaction, ≥85 points; moderate satisfaction, <85 points). The proportion of high satisfaction with interactive practice-based sessions was significantly higher than that with lecture-based sessions (82.81% vs. 75.46%, P=0.034). The enrollment for weekday evening courses filled up significantly faster than that for weekday daytime courses [4 (2, 6) seconds vs. 12 (8, 15) seconds, P<0.001]. Interactive practice-based sessions [odds ratio ( OR)=1.6, 95% CI=1.1-2.3, P=0.018] and weekday evening sessions ( OR=1.4, 95% CI=1.0-2.0, P=0.048) significantly improved resident satisfaction. Conclusions:Optimizing course formats and scheduling can enhance the quality of SRT teaching activities.

Transjugular intrahepatic portosystemic shunt(TIPS)is an important intervention for portal hypertension,and the degree of reduction in portal venous pressure is closely associated with the prognosis of patients.While a greater reduction in portal venous pressure may lead to more effective alleviation of portal hypertensive symptoms in cirrhotic patients,it also increases the risk of hepatic encephalopathy and liver failure.Therefore,appropriate control of the degree of reduction in portal venous pressure is essential for optimizing therapeutic outcomes.This article reviews the methods for measuring portal venous pressure,the factors affecting the reduction in portal venous pressure,the optimal range for reduction in different indications,and the impact of varying degrees of pressure reduction on complications,in order to provide guidance for improving the treatment outcome of TIPS and the prognosis of patients after surgery.

Objective To explore the role of pseudogene AC106872.1 in maintaining the self-renewal capacity of human embryonic stem cells(hESCs).Methods AC106872.1 was knocked out in hESCs and knockout effi-ciency was validated by PCR and agarose gel electrophoresis.The colony formation of hESCs was assessed through colony formation assays and alkaline phosphatase(AP)staining.The expression level of pluripotency and differ-entiation marker genes was analyzed by qPCR and flow cytometry.RNA sequencing(RNA-seq)was performed to assess transcriptomic changes upon AC106872.1 knockout.Results Knockout of AC106872.1 significantly in-hibited the colony formation of hESCs(P＜0.05).The expression level of pluripotency marker genes was signifi-cantly reduced(P＜0.000 1),while the expression of differentiation marker genes was markedly increased(P＜0.000 1).Conclusions The pseudogene AC 1 06872.1 plays a crucial role in maintaining human embryonic stem cell self-renewal through regulation of pluripotency genes expression.

Objective To investigate the expression of GJB4 gene in pancreatic cancer tissue and its correlation with clinicopathology.Methods The expression levels of GJB4 mRNA in pancreatic cancer and adjacent cancer tissues were analyzed using bioinformatics to analyze the Cancer Genome Atlas(TCGA)and Genotype-Tissue Expression(GTEx)RNA sequencing datasets.A total of 120 pancreatic cancer samples and 40 adjacent cancer samples from the Pathology Department of The Second Affiliated Hospital of Kunming Medical University from January 2019 to December 2023 were collected and sorted.Immunohistochemistry staining method was used to detect the expression difference of GJB4 protein between the two groups.RT-qPCR method was used to detect the expression levels of GJB4 in four pancreatic cancer cell lines.Univariate and multivariate Cox regression and Kaplan-Meier curves were used to analyze the clinical pathological data of GJB4 and pancreatic cancer patients.DAVID functional annotation bioinformatics and GSEA enrichment analysis were used to explore the relevant pathways of GJB4 in pancreatic cancer.Results The expression level of GJB4 mRNA in pancreatic cancer was higher than that in adjacent tissues,and the high expression of GJB4 was significantly associated with poor prognosis of patients(P<0.05).Immunohistochemical analysis showed that GJB4 protein was brown-yellow granular in pancreatic cancer tissues,mainly expressed in cytoplasm and cell membrane,and GJB4 protein expression was up-regulated in pancreatic cancer(P<0.05).The RT-qPCR test results showed that out of 4 pancreatic cancer cell lines,3 of them had upregulated expression(P<0.05).COX regression analysis showed that GJB4 gene was an independent risk factor in the prognosis of pancreatic cancer patients.The results of GO enrichment analysis showed that GJB4 was related to the transmembrane transport,ion channel,signal release and membrane potential regulation of pancreatic cancer.GSEA analysis showed that GJB4 was enriched in the Wnt/β-catenin signaling pathway.Conclusion In pancreatic cancer,the high expression level of GJB4 is closely related to the clinicopathological features of the patients,which may predict the poor prognosis of the patients.GJB4 may be involved in regulating the Wnt/β-catenin signaling pathway of pancreatic cancer,and is expected to be one of the potential biomarkers of pancreatic cancer prognosis.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Chimeric antigen receptor T (CAR-T) cells have reshaped the treatment landscape of hematological malignancies, offering a potentially curative option for patients. Despite these major milestones in the field of immuno-oncology, growing experience with CAR-T cells has also highlighted several limitations of this strategy. The production process of CAR-T cells is complex, time-consuming, and costly, thus leading to poor drug accessibility. The potential carcinogenic risk of viral transfection systems remains a matter of controversy. Treatment-related side effects, such as cytokine release syndrome, can be life-threatening. And the biggest challenge is the inadequate efficacy related to poor infiltration and retention of CAR-T cells in tumor tissues and impaired T cell activation caused by the immunosuppressive tumor microenvironment (TME). Innovative strategies are urgently needed to address these problems, and nanomedicine offers good solutions to these challenges. In this review, we provide a comprehensive summary of recent advancements in the application of nanomaterials to enhance CAR-T cell therapy. We examine the role of innovative nanoparticle-based delivery systems in the production of CAR-T cells, with a particular focus on polymeric delivery systems and lipid nanoparticles (LNPs). Furthermore, we explore various strategies for delivering immune stimulators, which significantly enhance the efficacy of CAR-T cells by modulating T cell viability and functionality or by reprogramming the immunosuppressive TME. In addition, we discuss several novel therapeutic approaches aimed at mitigating the adverse effects associated with CAR-T therapies. Finally, we offer an integrated perspective on the future challenges and opportunities facing CAR-T therapies.
Humans ; Nanomedicine/methods* ; Receptors, Chimeric Antigen/metabolism* ; Immunotherapy, Adoptive/methods* ; T-Lymphocytes/immunology* ; Nanoparticles/chemistry* ; Animals

BACKGROUND: Stroke is the leading cause of death and long-term disability worldwide, including China. This study aimed to provide timely updates on stroke burden and stroke-related risk factors to help improve population-based prevention and control strategies. METHODS: Based on the Global Burden of Disease study 2021, incidence rate, prevalence rate, mortality rate, and disability-adjusted life-year (DALY) rate were used to estimate stroke burden trend from 1990 to 2021. RESULTS: In 2021, China had 4.1 million incident stroke cases, 26.3 million prevalent stroke cases, 2.6 million stroke related deaths, and 53.2 million stroke related DALYs, compared to 11.9 million incident stroke cases, 93.8 million prevalent stroke cases, 7.3 million stroke related deaths, and 160.5 million stroke-related DALYs worldwide. In 2021, the top six risk factors contributing to stroke burden were high blood pressure, air pollution, tobacco consumption, dietary risk factors, high low-density lipoprotein cholesterol, and high fasting plasma glucose, both in China and worldwide. From 1990 to 2021, China had significant increases of incidence rate, prevalence rate, mortality rate, and DALY rate for stroke, with estimates of 100.6 (95% uncertainty intervals [UI]: 87.2, 114.1)%, 102.9 (95% UI: 95.5, 110.9)%, 40.0 (95% UI: 14.9, 72.3)% and 15.7 (95% UI: -4.6, 41.2)%, respectively, while global incidence rate, prevalence rate, mortality rate and DALY rate for total stroke showed relatively moderate increases or even decreases, with estimates of 15.0 (95% UI: 12.1,18.0)%, 25.8 (95% UI: 23.7, 28.0)%, -2.6 (95% UI: -10.6, 5.5)%, and -10.7 (95% UI: -17.7, -3.6)%, respectively. CONCLUSION Stroke remains a huge disease burden worldwide and in China, and compared to the worldwide China has a significantly higher burden of stroke.
Humans ; Stroke/etiology* ; China/epidemiology* ; Risk Factors ; Global Burden of Disease ; Disability-Adjusted Life Years ; Prevalence ; Incidence ; Female ; Quality-Adjusted Life Years ; Male