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.

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 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.

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.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0％ were gram-positive and 71.0％ were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6％,81.9％ and 78.5％,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9％ of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4％ of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1％ in the isolates from children and and 95.9％ in the isolates from adults.The resistance rate to carbapenems was lower than 15.0％ for most Enterobacterales species except for Klebsiella,22.5％ and 23.6％ of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6％ to 10.0％.The resistance rate to imipenem and meropenem was 21.9％ and 17.4％ for Pseudomonas aeruginosa,respectively,and 67.5％ and 68.1％ for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

The outer membrane composed predominantly of lipopolysaccharide (LPS) is an essential biological barrier for most Gram-negative (G^-) bacteria. Lipopolysaccharide transport protein (Lpt) complex LptDE is responsible for the critical final stage of LPS transport and outer membrane assembly. The structure and function of LptDE are highly conserved in most G^- bacteria but absent in mammalian cells, and thus LptDE complex is regarded as an attractive antibacterial target. In recent 10 years, the deciphering of the three-dimensional structure of LptDE protein facilities the drug discovery based on such "non-enzyme" proteins. Murepavadin, a peptidomimetic compound, was reported to be the first compound able to target LptD, enlightening a new class of antibacterial molecules with novel mechanisms of action. This article is devoted to summarize the molecular characteristics, structure-function of LptDE protein complex and review the development of murepavadin and related peptidomimetic compounds, in order to provide references for relevant researches.