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 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 observe the effect of multi-modal hand hygiene(HH)intervention on HH compliance,as well as the relationship between HH compliance and the healthcare-associated(HA)case infection incidence.Methods From 2014 to 2022,the infection control team in a tertiary first-class hospital implemented multi-modal HH intervention for health care workers(HCWs).The changing trend of HH monitoring data,the correlation be-tween HH compliance rate and HA case infection incidence were analyzed retrospectively.Results The consump-tion of HH products in the wards showed a stable upward trend;HH compliance rate increased from 64.98％in 2014 to 85.01％in 2022(P＜0.001),and HA case infection incidence decreased from 1.21％to 0.83％(P＜0.05).HH compliance rate was negatively correlated with HA case infection incidence(r=-0.369,P=0.027).HH compliance rates in different regions and job posts in each quarter were increased(P＜0.001).For 5 different HH moments in each quarter,HH compliance rate fluctuated slightly before sterile manipulation and after touching patient;presented rising trend after touching surroundings around patient,and decreased before touching patient and after touching patient's body fluid since 2020(P＜0.001).Conclusion Multi-modal HH intervention can im-prove the HH compliance of HCWs,improving their HH awareness is conducive to reducing HA case infection incidence.

OBJECTIVE:The rabbit model of steroid-induced osteonecrosis of femoral head is the most commonly used animal model of femoral head necrosis.The pathological changes of the femoral head are close to clinical practice,however,the conditions,methods and evaluation standards of animal models reported in and outside China are not uniform,which leads to the low scientific value of animal models and is difficult to popularize.This study aimed to clarify the influence of different mold-making conditions on the establishment of steroid-induced osteonecrosis of femoral head rabbit model and analyze the appropriate conditions for the successful model establishment. METHODS:We searched the CNKI,WanFang,VIP,CBM,WoS,PubMed and EMbsae databases for the literature on the modeling of steroid-induced osteonecrosis of femoral head rabbits up to April 1,2022,completed the screening of the literature according to the inclusion and exclusion criteria and literature quality evaluation,and extracted the outcome index data in the literature.RevMan Stata and ADDIS statistical software were used to conduct a meta-analysis of the included data. RESULTS:(1)A total of 82 articles with 1 366 rabbits were included in the study.The steroid-induced osteonecrosis of femoral head modeling methods were divided into three types:steroid-alone method,steroid combined lipopolysaccharide method and steroid combined serum method.Among these,33 articles used steroid-alone method;20 articles used steroid combined lipopolysaccharide method;29 articles used steroid combined serum method.(2)Meta-analysis results showed that the three modeling methods significantly increased the rate of empty bone lacunae in the femoral head of steroid-induced osteonecrosis of femoral head rabbits(P<0.001),and significantly decreased the ratio of the trabecular bone area in the femoral head of steroid-induced osteonecrosis of femoral head rabbits(P<0.001).The order of empty bone lacunae rate of each modeling method was:steroid combined with lipopolysaccharide method>steroid-alone method>steroid combined with serum method>normal group,and the order of trabecular bone area rate of each modeling method was:normal group>steroid combined with serum method>steroid-alone method>steroid combined with lipopolysaccharide method.(3)The results of subgroup analysis suggested that the rate of empty bone lacunae in the rabbit model induced by steroid alone might be related to the rabbit variety and the type of steroid used for modeling(difference between groups P<0.05),in which the combined effect amount of New Zealand white rabbits was higher than that of Chinese white rabbits(P<0.05)and Japanese white rabbits,and the combined effect amount of dexamethasone was higher than that of other steroids.The rate of empty bone lacunae induced by steroid combined with lipopolysaccharide was related to the administration mode of lipopolysaccharide and the type of steroid(P<0.05),among which the combined effect of methylprednisolone sodium succinate was significantly higher than that of other steroids(P<0.05),and the combined effect of prednisolone was significantly lower than that of other steroids(P<0.05).The combined effect of lipopolysaccharide 100 μg/kg×twice was significantly lower than 10 μg/kg×twice and 50 μg/kg×twice(P<0.05).The rate of empty bone lacunae in the model induced by steroid combined with serum was related to serum dose and steroid type(P<0.05),among which the combined effect amount of dexamethasone sodium phosphate was significantly higher than other steroid types(P<0.05),and the combined effect amount of dexamethasone was significantly lower than other steroid types(P<0.05);the combined effect amount of serum"10 mL/kg+6 mL/kg"combined dose was lower than other serum doses(P<0.05). CONCLUSION:(1)With the rate of empty bone lacunae and the ratio of trabecular bone area as the judgment standard for the successful establishment of the model,the three modeling methods can successfully construct the rabbit steroid-induced osteonecrosis of femoral head model,of which the steroid combined with lipopolysaccharide method is the best.(2)New Zealand white rabbits and dexamethasone are recommended when selecting the steroid-alone method.Methylprednisolone sodium succinate and low-dose lipopolysaccharide are recommended when selecting the steroid combined with lipopolysaccharide method.Dexamethasone sodium phosphate is recommended when selecting the steroid combined with serum modeling method.

Objective To analyze the characteristics of healthcare-associated infection(HAI)in patients in liver transplantation intensive care unit(ICU),and provide basis for the effective prevention and control of liver post-transplantation infection.Methods Targeted surveillance data of HAI in liver transplantation ICU from 2018 to 2022 were analyzed retrospectively.Incidence,incidence trend,infection site,pathogens and drug resistance were analyzed.Results A total of 3 762 liver transplantation patients were surveilled,106 patients developed 133 cases of HAI,with an incidence of 2.82％and a case incidence of 3.54％.There was no significant difference among the years(P=0.473).Infection mainly occurred within 2 weeks after admission to ICU,accounting for 85.85％.The main infection sites included blood system(26.32％),respiratory system(22.56％),and surgical site(19.55％).The average utilization rates of central veinous catheterization,urethral catheterization,and ventilator were 85.77％,70.58％,and 40.83％,respectively.The incidences of central line-associated bloodstream infection(CLABSI),catheter-associated urinary tract infection(CAUTI),and ventilator-associated pneumonia(VAP)were 0.54‰,0.33‰,and 1.84‰,respectively.A total of 131 strains of pathogens were detected,of which Gram-negative bac-teria accounted for 38.17％and Gram-positive bacteria accounted for 29.77％.The top three pathogens were Kleb-siella pneumoniae(15.27％),Enterococcus faecium(11.45％),and Acinetobacter baumannii(9.16％).Conclusion Effective prevention and control measures should be taken based on the characteristics of HAI in the liver transplan-tation ICU,so as to curb bacterial resistance and reduce liver post-transplantation HAI.

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 analyze the characteristics of healthcare-associated infection(HAI)in patients in liver transplantation intensive care unit(ICU),and provide basis for the effective prevention and control of liver post-transplantation infection.Methods Targeted surveillance data of HAI in liver transplantation ICU from 2018 to 2022 were analyzed retrospectively.Incidence,incidence trend,infection site,pathogens and drug resistance were analyzed.Results A total of 3 762 liver transplantation patients were surveilled,106 patients developed 133 cases of HAI,with an incidence of 2.82％and a case incidence of 3.54％.There was no significant difference among the years(P=0.473).Infection mainly occurred within 2 weeks after admission to ICU,accounting for 85.85％.The main infection sites included blood system(26.32％),respiratory system(22.56％),and surgical site(19.55％).The average utilization rates of central veinous catheterization,urethral catheterization,and ventilator were 85.77％,70.58％,and 40.83％,respectively.The incidences of central line-associated bloodstream infection(CLABSI),catheter-associated urinary tract infection(CAUTI),and ventilator-associated pneumonia(VAP)were 0.54‰,0.33‰,and 1.84‰,respectively.A total of 131 strains of pathogens were detected,of which Gram-negative bac-teria accounted for 38.17％and Gram-positive bacteria accounted for 29.77％.The top three pathogens were Kleb-siella pneumoniae(15.27％),Enterococcus faecium(11.45％),and Acinetobacter baumannii(9.16％).Conclusion Effective prevention and control measures should be taken based on the characteristics of HAI in the liver transplan-tation ICU,so as to curb bacterial resistance and reduce liver post-transplantation HAI.

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing