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 understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

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 understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective　To explore the application of time series models based on meteorological factors in the population density of Aedes albopictus in Hainan Province, and to provide a scientific basis for the prevention and control of dengue fever in Hainan Province. Methods　The density of Aedes albopictus in different habitats in 18 cities and counties of Hainan Province from 2017 to 2022 was monitored monthly using the double-mosquito net trapping index and the Breteau index. Mann-Kendall trend test was used to analyze the temporal trends of the two density indices; Spearman's correlation analysis was employed to assess the correlation strength between each meteorological factor and the two indexes, eliminating unrelated variables, and further selecting the final variables through the full-subset regression method. Three time-series models were constructed for the two density indices, with root mean square error (RMSE), mean absolute error (MAE), and other accuracy metrics used to determine the optimal model; predictions for the density indices for 2023-2024 were made. All statistical analyses were performed in R (4.3.1). Results　The net trapping and Breteau indices showed an overall decrease over the years (Z-values of Mann-Kendall trend test were -6.15 and -4.03, respectively, and P<0.05). The meteorological factor most strongly associated with the trap index was the monthly average minimum temperature; monthly mean minimum temperature and monthly mean relative humidity were strongly correlated with the Breteau index. Based on various evaluation indicators, the multivariate time series model demonstrated the highest accuracy. The study predicts one to two peaks in both the trap index and Breteau Index for the years 2023 and 2024, with peak periods occurring between June to September and May to September, respectively. The predicted value for 2023 aligns with the measured value, demonstrating outstanding predictive accuracy. Conclusions　This study has introduced meteorological factors into the seasonal time series model, allowing for more accurate predictions of the density of Aedes albopictus in Hainan Province from 2023 to 2024, providing a model framework for the prevention and control of dengue fever in Hainan Province.

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.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

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.

OBJECTIVE: To evaluate the efficacy and safety of Cidan Capsule combined with adjuvant transarterial chemoembolization (TACE) in patients with a high risk of early recurrence after curative resection of hepatocellular carcinoma (HCC). METHODS: A multicenter, randomized controlled trial was conducted in patients with high-risk recurrence factors after curative resection of HCC from 9 medical centers between July 2014 and July 2018. Totally 249 patients were randomly assigned to TACE with or without Cidan Capsule administration groups by stratified block in a 1:1 ratio. Postoperative adjuvant TACE was given 4-5 weeks after hepatic resection in both groups. Additionally, 125 patients in the TACE plus Cidan group were administrated Cidan Capsule (0.27 g/capsule, 5 capsules every time, 4 times a day) for 6 months with a 24-month follow-up. Primary endpoints included disease-free survival (DFS) and tumor recurrence rate (TRR). Secondary endpoint was overall survival (OS). Any drug-related adverse events (AEs) were observed and recorded. RESULTS: As the data cutoff in July 9th, 2018, the median DFS was not reached in the TACE plus Cidan group and 234.0 days in the TACE group (hazard ratio, 0.420, 95% confidence interval, 0.290-0.608; P<0.01). The 1- and 2-year TRR in the TACE plus Cidan and TACE groups were 31.5%, 37.1%, and 60.8%, 63.4%, respectively (P<0.01). Median OS was not reached in both groups. The 1- and 2-year OS rates in TACE plus Cidan and TACE groups were 98.4%, 98.4%, and 89.5%, 87.9%, respectively (P<0.05). The most common grade 3-4 AEs included fatigue, abdominal pain, lumbar pain, and nausea. One serious AE was reported in 1 patient in the TACE plus Cidan group, the death was due to retroperitoneal mass hemorrhage and hemorrhagic shock, and was not related to study drug. CONCLUSIONS Cidan Capsule in combination with TACE can reduce the incidence of early recurrence in HCC patients at high-risk of recurrence after radical hepatectomy and may be an appropriate option in postoperative anti-recurrence treatment. (Registration No. NCT02253511).

Abstract: Objective　To understand the density changes and seasonal fluctuation of larvae and adults of Aedes albopictus in Hainan Province from 2017 to 2021, and to provide a scientific basis for the prevention and control of dengue fever and other vector-borne diseases in Hainan Province. Methods　The Breteau index method was used to monitor the larvae of Aedes mosquitoes, and the breeding sites of all small indoor and outdoor water containers and their larvae was checked and recorded. The adult mosquitoes were monitored by double lamination and light trap. Results　A total of 1 962 adult female Aedes albopictus mosquitoes were captured in Hainan Province from 2017 to 2021, accounting for 2.17% of the total captured mosquitoes. There were significant differences in mosquito species composition in different habitats in different years (χ2=312.258, P<0.01). In 2017, the density of mosquitoes in livestock sheds was the highest (9.71 per lamp·night), but the composition ratio of Aedes albopictus was the lowest (1.29%). In 2020, the mosquito density in hospitals was the lowest (2.22 mosquitoes per lamp·night), and in 2019, the proportion of Aedes albopictus in residential areas and hospitals was the highest (3.27% on average).The mosquito density in different habitats was the lowest in 2020. The proportion of Aedes albopictus in residential areas and livestock sheds showed an increasing trend from 2017 to 2021, while the proportion of other habitats showed significant fluctuations. The proportion of Aedes albopictus in hospitals showed an obvious decreasing trend in 2020. From 2017 to 2021, the average mosquito density was 5.97, 4.26, 3.82, 3.39 and 3.68 mosquitoes per lamp·night, respectively, showing a decreasing trend year by year except 2021. Except for 2019, the lure index also showed a decreasing trend, with an average value of 1.5/(hour·net), showing a decreasing trend year by year. From 2017 to 2021, the annual average density of Aedes albopictus in Hainan Province was 0.09 mosquitoes per lamp·night, showing obvious seasonal fluctuation. The Breteau index showed a slow decline from 2017 to 2021, and its annual peak was between June and August, which was 1-2 months later than the peak of adult mosquito density. Conclusions　The population density of Aedes albopictus in Hainan shows obvious seasonal characteristics. Mosquito control activities should be carried out according to the seasonal characteristics of mosquitoes to reduce the risk of dengue fever and other infectious diseases.