The continuous emergence of SARS-CoV-2 variants as well as other potential future coronavirus has challenged the effectiveness of current COVID-19 vaccines. Therefore, there remains a need for alternative antivirals that target processes less susceptible to mutations, such as the formation of six-helix bundle (6-HB) during the viral fusion step of host cell entry. In this study, a novel high-throughput screening (HTS) assay employing a yeast-two-hybrid (Y2H) system was established to identify inhibitors of HR1/HR2 interaction. The compound IMB-9C, which achieved single-digit micromolar inhibition of SARS-CoV-2 and its Omicron variants with low cytotoxicity, was selected. IMB-9C effectively blocks the HR1/HR2 interaction in vitro and inhibits SARS-CoV-2-S-mediated cell-cell fusion. It binds to both HR1 and HR2 through non-covalent interaction and influences the secondary structure of HR1/HR2 complex. In addition, virtual docking and site-mutagenesis results suggest that amino acid residues A930, I931, K933, T941, and L945 are critical for IMB-9C binding to HR1. Collectively, in this study, we have developed a novel screening method for HR1/HR2 interaction inhibitors and identified IMB-9C as a potential antiviral small molecule against COVID-19 and its variants.

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

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.

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.

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

OBJECTIVE: To observe the protective effect and mechanism of hydroxyl safflower yellow A (HSYA) from myocardial ischemia-reperfusion injury on human umbilical vein endothelial cells (HUVECs). METHODS: HUVECs were treated with oxygen-glucose deprivation reperfusion (OGD/R) to simulate the ischemia reperfusion model, and cell counting kit-8 was used to detect the protective effect of different concentrations (1.25-160 µ mol/L) of HSYA on HUVECs after OGD/R. HSYA 80 µ mol/L was used for follow-up experiments. The contents of inflammatory cytokines interleukin (IL)-18, IL-1 β, monocyte chemotactic protein 1 (MCP-1), tumor necrosis factor α (TNF-α) and IL-6 before and after administration were measured by enzyme-linked immunosorbent assay. The protein expressions of toll-like receptor, NOD-like receptor containing pyrin domain 3 (NLRP3), gasdermin D (GSDMD) and GSDMD-N-terminal domain (GSDMD-N) before and after administration were detected by Western blot. NLRP3 inflammasome inhibitor cytokine release inhibitory drug 3 sodium salt (CRID3 sodium salt, also known as MCC950) and agonist were added, and the changes of NLRP3, cysteine-aspartic acid protease 1 (Caspase-1), GSDMD and GSDMD-N protein expressions were detected by Western blot. RESULTS: HSYA inhibited OGD/R-induced inflammation and significantly decreased the contents of inflammatory cytokines IL-18, IL-1 β, MCP-1, TNF-α and IL-6 (P<0.01 or P<0.05). At the same time, by inhibiting NLRP3/Caspase-1/GSDMD pathway, HSYA can reduce the occurrence of pyroptosis after OGD/R and reduce the expression of NLRP3, Caspase-1, GSDMD and GSDMD-N proteins (P<0.01). CONCLUSIONS The protective effect of HSYA on HUVECs after OGD/R is related to down-regulating the expression of NLRP3 inflammasome and inhibiting pyroptosis.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Human Umbilical Vein Endothelial Cells/metabolism* ; Humans ; Chalcone/analogs & derivatives* ; Quinones/pharmacology* ; Pyroptosis/drug effects* ; Caspase 1/metabolism* ; Glucose ; Phosphate-Binding Proteins/metabolism* ; Signal Transduction/drug effects* ; Intracellular Signaling Peptides and Proteins/metabolism* ; Oxygen/metabolism* ; Cytokines/metabolism* ; Gasdermins

This paper briefly introduced the varying coefficient model and used the varying coefficient Cox model as an example to demonstrate its application in the fields of medicine and public health through real data analysis,thereby provided methodological references for related research.The example was based on chronic disease management data from a Center for Disease Control and Prevention,fitting a varying coefficient Cox model to explore the time-varying association between body mass index(BMI)and mortality risk among a hypertensive population.The results showed that being underweight(BMI＜18.5 kg/m2)was associated with a higher risk of mortality,but this association weakened over time;being overweight(23 kg/m2≤BMI＜25 kg/m2)was associated with a lower risk of mortality,and this association also weakened over time.The varying coefficient model captured how the impact of exposure factors on outcomes changed with other variables,helping to comprehensively understand the complex relationships between variables,and had significant application and promotion value in medical and public health research.

Propensity score weighting methods are crucial tools for adjusting confounding and conducting causal inference in observational studies.This paper introduces various propensity score weighting methods,and details the key features of each to aid researchers in selecting the most suitable method for their analyses.Additionally,the application of these methods in the fields of medicine and public health is demonstrated through an example data analysis.The example is based on data from 996 patients who underwent percutaneous coronary intervention(PCI).Different propensity score weighting methods are used to explore the effect of PCI combined with abciximab on six-month post-operative survival rates.The results indicate that different propensity score weighting methods provide treatment effect estimates tailored to different inference goals,highlighting the importance of selecting the appropriate method based on the specific inference objective.Propensity score weighting methods enhance the balance of covariate distribution between treatment and control groups,making them powerful tools for adjusting confounding factors in observational studies.Their applicability and value in medical and public health research are significant.

This paper introduces a transfer learning approach based on regression models and demonstrates its application in the medical field through an example.Using data from the 2013-2014 U.S.National Health and Nutrition Examination Survey,the study investigates the association of sleep duration with depression levels and depressive disorder.It employs demographic characteristics and lifestyle factors as predictor variables to predict depression levels and depressive disorder across different racial groups.Compared to models built solely on target racial groups,transfer learning enhances the accuracy of estimating the effect of sleep duration in the target group and improves the prediction accuracy for depression levels and depressive disorder.The results illustrate that transfer learning effectively integrates source data to significantly improve estimation and prediction capabilities of target models,especially in situations with limited target data and heterogeneous data sources.

This article introduced the basic theory of non-parametric regression and its application in medical and public health research for methodological reference.We conducted Cox proportional hazard models with restricted cubic splines using chronic disease management data from a Center for Disease Control and Prevention.We aimed to explore the separate and combined effects of mean fasting blood glucose level and glucose variability on all-cause mortality among individuals with type 2 diabetes.A non-linear association was observed between glucose variability and the risk of all-cause mortality.The association between glucose variability and all-cause mortality was stronger at higher mean fasting blood glucose levels compared to lower levels.The non-parametric regression methods comprehensively explored dose-response relationships between continuous exposure and outcome,revealing the combined effects of continuous exposures,which provided recommendations for targeted interventions.The method showed promising application value in medical and public health research.