The data from outpatient prescriptions of small-size aspirin enteric-coated tablets(25 mg/tablet)in a community hospital were analyzed to provide reference for rational clinical drug use.Patients'medication information of 1 325 prescriptions was collected and analyzed by defined daily dose system(DDDs)and drug utilization index(DUI),and the rationality of drug use was analyzed according to drug instructions and literature.The mean age of males and females were(73.70±8.33)years old and(72.95±8.34)years old,respectively.The top 3 DDDs age groups were women aged 60-79 years,men aged 60-79 years and women aged 80-99 years.The proportion of prescriptions in female patients was 59.62%.DUI ranges from 0.75 to 0.85.Irrational drug use was found in 123 prescriptions,including 89 prescriptions(72.35%)of inappropriate drug selection,19 prescriptions(15.45%)with low dose,6 prescriptions(4.88%)with contraindication,5 prescriptions(4.06%)with inconsistent frequency of administration,2 prescriptions(1.63%)of out-of-indication drug use,and 2 prescriptions(1.63%)of high dose.For the phenomenon of irrational drug use,it is necessary to conduct real-time intervention to ensure the safety and effectiveness of drug use.

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.

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

We aimed to explore the value of personalized narrative intervention in the nursing care of elderly patients with stroke hemiplegia(SH).A total of 68 elderly patients with SH were selected and divided into two groups using the ball-rolling method,with 34 cases in each group.The control group received routine nursing care,while the observation group received routine care and personalized narrative nursing.The nursing outcomes of the two groups were compared.Compared with the control group,the observation group had lower scores in anxiety and depression(P<0.05),and higher scores in the Functional Evaluation of Cognitive State-Short Screening(FECS-SS)(P<0.05).The rehabilitation effects of normal rate in the observation group was higher than that in the control group(P<0.05).Personalized narrative nursing for SH patients can effectively relieve the patients'negative emotions,enhance their compliance with rehabilitation,and improve the outcomes of rehabilitation.

Blood from a case of group B epidemic cerebrospinal meningitis identified in February 2024 in Ganzhou City,Jiangxi Province,and throat swabs from close contacts were collected for isolation and culture.The isolates were subjected to serogrouping,drug sensitivity testing,and whole genome sequencing and analysis,to provide a basis for epidemiological inves-tigation and clinical drug use.One strain of Neisseria meningitidis was isolated from the blood of the case and denoted group B.The MLST type was ST-7962,with no clonal group attribution.The phylogenetic tree showed that it was genetically close to the 1977 Shanghai carrier isolate(id-52231).Drug sensitivity results indicated that the strain was sensitive to 8 drugs:azithro-mycin,cefotaxime,minocycline,ceftriaxone,chloramphenicol,meropenem,rifampicin,and benzylpenicillin;resistant to cot-rimoxazole,levofloxacin,and ciprofloxacin;and showed an intermediate response to penicillin.This report describes the first case of ST-7962 group B meningoencephalitis found in Jiangxi Province.Monitoring of Neisseria meningitidis carriage,drug re-sistance,and molecular characteristics of strains in the healthy population in this region should be strengthened,to provide la-boratory support for the clinical use of medications,traceability,and control of the pathogen underlying meningoencephalitis infection.

The data from outpatient prescriptions of small-size aspirin enteric-coated tablets(25 mg/tablet)in a community hospital were analyzed to provide reference for rational clinical drug use.Patients'medication information of 1 325 prescriptions was collected and analyzed by defined daily dose system(DDDs)and drug utilization index(DUI),and the rationality of drug use was analyzed according to drug instructions and literature.The mean age of males and females were(73.70±8.33)years old and(72.95±8.34)years old,respectively.The top 3 DDDs age groups were women aged 60-79 years,men aged 60-79 years and women aged 80-99 years.The proportion of prescriptions in female patients was 59.62%.DUI ranges from 0.75 to 0.85.Irrational drug use was found in 123 prescriptions,including 89 prescriptions(72.35%)of inappropriate drug selection,19 prescriptions(15.45%)with low dose,6 prescriptions(4.88%)with contraindication,5 prescriptions(4.06%)with inconsistent frequency of administration,2 prescriptions(1.63%)of out-of-indication drug use,and 2 prescriptions(1.63%)of high dose.For the phenomenon of irrational drug use,it is necessary to conduct real-time intervention to ensure the safety and effectiveness of drug use.

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.