Based on ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology and network pharmacology, this study explored the pharmacodynamic substances and potential mechanisms of Huazhuo Sanjie Chubi Decoction in the treatment of gouty arthritis(GA). UPLC-Q-Exactive Orbitrap-MS technology was used to identify the components in Huazhuo Sanjie Chubi Decoction, and the qualitative analysis of its active ingredients was carried out, with a total of 184 active ingredients identified. A total of 897 active ingredient targets were screened through the PharmMapper database, and 491 GA-related disease targets were obtained from the OMIM, GeneCards, CTD databases. After Venn analysis, 60 intersecting targets were obtained. The component target-GA target network was constructed through the Cytoscape platform, and the STRING database was used to construct a protein-protein interaction network, with 16 core targets screened. The core targets were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses, and the component-target-pathway network was constructed. It was found that the main active ingredients of the formula for the treatment of GA were phenols, flavonoids, alkaloids, and terpenoids, and the key targets were SRC, MMP3, MMP9, REN, ALB, IGF1R, PPARG, MAPK1, HPRT1, and CASP1. Through GO analysis, it was found that the treatment of GA mainly involved biological processes such as lipid response, bacterial response, and biostimulus response. KEGG analysis showed that the pathways related to the treatment of GA included lipids and atherosclerosis, neutrophil extracellular traps(NETs), IL-17, and so on. In summary, phenols, flavonoids, alkaloids, and terpenoids may be the core pharmacodynamic substances of Huazhuo Sanjie Chubi Decoction in the treatment of GA, and the pharmacodynamic mechanism may be related to SRC, MMP3, MMP9, and other targets, as well as lipids and atherosclerosis, NETs, IL-17, and other pathways.
Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Arthritis, Gouty/metabolism* ; Chromatography, High Pressure Liquid/methods* ; Humans ; Mass Spectrometry/methods* ; Protein Interaction Maps/drug effects*

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

Cytotoxicity, usually represented by cell viability, is a crucial parameter for evaluating drug safety in vitro. Accurate prediction of cell viability/cytotoxicity could accelerate drug development in the early stage. In this study, by integrating cellular transcriptome and cell viability data using four machine learning algorithms (support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM)) and two ensemble algorithms (voting and stacking), highly accurate prediction models of 50% and 80% cell viability were developed with area under the receiver operating characteristic curve (AUROC) of 0.90 and 0.84, respectively; these models also showed good performance when utilized for diverse cell lines. Concerning the characterization of the employed Feature Genes, the models were interpreted, and the mechanisms of bioactive compounds with a narrow therapeutic index (NTI) can also be analyzed. In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. Moreover, for the first time, Cytotoxicity Signature (CTS) genes were identified, which could provide additional clues for further study of mechanisms of action (MOA), especially for NTI compounds.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To describe the clinical features of patients with primary sclerosing cholangitis(PSC)in China based on a nationwide multicenter patient cohort,and to investigate the risk factors for prognosis.Methods A retrospective cohort study was conducted among the patients with a confirmed diagnosis of PSC based on the electronic medical record system of seven grade A tertiary hospitals across the country,and related data were extracted.The Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.The Kaplan-Meier method was used to estimate liver transplant-free survival,and the log-rank test was used for comparison of survival rate between PSC patients with different features.The Cox regression model was used to identify independent risk factors for the prognosis of PSC patients and the interactions between key factors.Results A total of 107 patients were enrolled,among whom 55.6%(55/99)had large-duct PSC and 29.0%(31/107)had comorbidity with inflammatory bowel disease(IBD).The positivity rate of anti-neutrophil cytoplasmic antibody(ANCA)was 32.9%(24/73),and 50.0%(40/80)of the patients had an increase in IgG/IgM.The median symptom-to-diagnosis interval was 1 year(<1-4.0),and 38.3%(41/107)of the patients had progressed to decompensated cirrhosis at the time of diagnosis.The median liver transplant-free survival time was 114 months(95%confidence interval[CI]:62-166),with a 5-year survival rate of 65.7%.The multivariate analysis showed that an increase in total bile acid(TBA)(hazard ratio[HR]=1.006,95%CI:1.002-1.010,P=0.001)and a prolonged symptom-to-diagnosis interval(HR=1.252,95%CI:1.059-1.480,P=0.009)were independent risk factors for prognosis.The interaction analysis showed that compared with the female patients with TBA<50 μmol/L,both male and female patients with TBA≥50 μmol/L had a significant increase in the risk of liver transplantation or death(male:HR=16.563,95%CI:2.103-130.449,P<0.001;female:HR=17.009,95%CI:2.113-136.934,P<0.001),and compared with the patients with an age of<45 years and a TBA level of<50 μmol/L,the patients with an age of≥45 years and a TBA level of≥50 μmol/L had a significant increase in the risk of liver transplantation or death(HR=10.729,95%CI:1.325-86.859,P=0.026).Compared with the female patients with an symptom-to-diagnosis interval of≤2 years,the male patients with a symptom-to-diagnosis interval of>2 years had an increased risk of liver transplantation or death(HR=4.825,95%CI:1.725-13.644,P=0.003),and compared with the patients with an age of<45 years and a symptom-to-diagnosis interval of≤2 years,the patients with an age of<45 years and a symptom-to-diagnosis interval of>2 years had an increased risk of liver transplantation or death(HR=4.983,95%CI:1.366-18.173,P=0.015).Conclusion Compared with the reports from Western countries,large-duct PSC is also the main type of PSC in China,but with a relatively low proportion,and there is also a relatively low proportion of patients with IBD or positive ANCA.An increase in TBA and a prolonged symptom-to-diagnosis interval are independent risk factors for prognosis,with significant interactions with age and sex.This suggests that early screening and intervention should be enhanced to improve prognosis.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the correlation between the hemodynamic pattern of non-culprit vessel stenosis and long-term vessel-oriented composite outcome(VOCO) in patients with acute ST-segment elevation myocardial infarction (STEMI).Methods:From January 2019 to December 2021, 233 consecutive patients with STEMI and non-culprit vessel stenosis were prospectively enrolled at Shanghai East Hospital. The median follow-up duration was 3.9 years. The 367 non-culprit vessels of the 233 patients were divided into the VOCO group (33 vessels, 9.0%) and the non-VOCO group (334 vessels, 91.0%). Parameters pertaining to the hemodynamic pattern of non-culprit vessel stenosis between the two groups were compared. Receiver operating characteristic (ROC) curves were used to assess the correlation between hemodynamic pattern and VOCO, and Cox multivariate regression and logistic multivariate regression analyses were applied to identify independent predictors of VOCO.Results:The 233 enrolled patients were aged (62.5±12.9) years, with 193 males (82.8%). In the VOCO group, the maximum quantitative flow ratio (QFR) decreased within 20 mm of the QFR-assessed segment, the difference in QFR across the entire vessel, the length of functionally significant vessel, and the maximum gradient of QFR decrease (dQFR/dsmax) were significantly greater than those in the non-VOCO group. ROC curve analysis showed that the optimal threshold for predicting VOCO using dQFR/dsmax was 0.009 6 (area under the curve: 0.691, 95% CI: 0.606-0.775, P<0.001). Multivariable Cox regression analysis revealed that dQFR/dsmax was an independent predictor of VOCO ( HR=1.199, 95% CI: 1.070-1.343, P=0.002). When anatomical and functional stenosis severities were included in the model, a high pullback pressure gradient (PPG) index ( HR=1.572, 95% CI: 1.052-2.351, P=0.027) emerged as an independent predictor of VOCO. Multivariable logistic regression analysis revealed that a low PPG index( OR=2.851, 95% CI: 1.945-4.178, P<0.001) was an independent predictor of QFR≤0.80 without long-term VOCO. Conclusion:In patients with STEMI, localized hemodynamic patterns of coronary artery stenosis, characterized by high dQFR/dsmax and high PPG index, are associated with long-term VOCO.