ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

OBJECTIVE: High-altitude hypoxia exposure often damages hippocampus-dependent learning and memory. Nogo-A is an important axonal growth inhibitory factor. However, its function in high-altitude hypoxia and its mechanism of action remain unclear. METHODS: In an in vivo study, a low-pressure oxygen chamber was used to simulate high-altitude hypoxia, and genetic or pharmacological intervention was used to block the Nogo-A/NgR1 signaling pathway. Contextual fear conditioning and Morris water maze behavioral tests were used to assess learning and memory in rats, and synaptic damage in the hippocampus and changes in oxidative stress levels were observed. In vitro, SH-SY5Y cells were used to assess oxidative stress and mitochondrial function with or without Nogo-A knockdown in Oxygen Glucose-Deprivation/Reperfusion (OGD/R) models. RESULTS: Exposure to acute high-altitude hypoxia for 3 or 7 days impaired learning and memory in rats, triggered oxidative stress in the hippocampal tissue, and reduced the dendritic spine density of hippocampal neurons. Blocking the Nogo-A/NgR1 pathway ameliorated oxidative stress, synaptic damage, and the learning and memory impairment induced by high-altitude exposure. CONCLUSION: Our results demonstrate the detrimental role of Nogo-A protein in mediating learning and memory impairment under high-altitude hypoxia and suggest the potential of the Nogo-A/NgR1 signaling pathway as a crucial therapeutic target for alleviating learning and memory dysfunction induced by high-altitude exposure. GRAPHICAL ABSTRACT available in www.besjournal.com.
Animals ; Oxidative Stress ; Hippocampus/metabolism* ; Rats ; Nogo Proteins/genetics* ; Male ; Rats, Sprague-Dawley ; Hypoxia/metabolism* ; Altitude ; Synapses ; Humans ; Altitude Sickness/metabolism*

Objective:To understand the incidence trend of brucellosis over time in Shandong Province from 2004 to 2023, and provide evidence for the prevention and control of brucellosis.Methods:The incidence data of brucellosis in Shandong from 2004 to 2023 were collected from China Disease Prevention and Control Information System. The annual change percentage (APC) and annual average change percentage (AAPC) of the incidence rate were calculated by using Joinpoint regression model. A age-period-cohort model was used to analyze changes in brucellosis incidence with age, period, and birth cohort.Results:The average annual incidence of brucellosis was 1.76/100 000 in Shandong from 2004 to 2023. The Joinpoint regression analysis results showed that the reported incidence of brucellosis increased by an average of 92.0% and 18.9% each year from 2004 to 2010 and from 2010 to 2014, respectively, and decreased by an average of 0.2% each year from 2014 to 2023. The results of APC model showed that the incidence of brucellosis increased first and then decreased with age ( χ2=176.92, P<0.001), and incidence of brucellosis showed slow increase and rapid increase first, then decrease ( χ2=2 921.03, P<0.001) over time. The risk for brucellosis reached peak in 2016 ( RR=5.29, 95% CI: 4.96-5.65) and became the lowest in 2006 ( RR=0.24, 95% CI: 0.21-0.28). The incidence increased in later birth cohort ( χ2=348.88, P<0.001), the AAPCs of all the age groups were between 15.0% and 40.0%, and the older the age, the greater the risk ( χ2=348.77, P<0.001). Conclusions:From 2004 to 2023, the reported incidence of brucellosis in Shandong showed a significant age-period-cohort effect, which increased first and then decreased, first increased and then decreased with age, increased slowly and rapidly first, then decreased over time, and increased in later birth cohort. It is necessary to conduct targeted prevention and control, health education to reduce the risk for brucellosis.

In recent years,the number of Chest Pain Centers in China has increased rapidly.As of December 2024,there were 5 947 registered units of Chest Pain Centers nationwide,2 994 of which had passed the acceptance.As of April 2025,18.34 million acute chest pain cases have been treated at Chest Pain Centers nationwide,according to the Chest Pain Center reporting platform.The Chest Pain Centers treated more than 3.62 million patients with acute chest pain in 2024,including more than 770 000 patients with acute myocardial infarction,and achieved positive results:significantly increasing the proportion of reperfusion therapy for acute ST-segment elevation myocardial infarction patients,ensuring the treatment of myocardial infarction patients in a short time,shortening the length of patient hospitalization,and reducing the hospitalization costs and mortality of patients.Through the construction of Chest Pain Center,the treatment process was significantly optimized and the prognosis of patients was improved.At present,the construction and quality control of Chest Pain Centers still need to be further promoted.In some areas,the construction proportion of Chest Pain Centers and the level of diagnosis and treatment of chest pain need to be improved,patient delay is still an important challenge for the treatment of acute chest pain in China.

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.

In recent years,the number of Chest Pain Centers in China has increased rapidly.As of December 2024,there were 5 947 registered units of Chest Pain Centers nationwide,2 994 of which had passed the acceptance.As of April 2025,18.34 million acute chest pain cases have been treated at Chest Pain Centers nationwide,according to the Chest Pain Center reporting platform.The Chest Pain Centers treated more than 3.62 million patients with acute chest pain in 2024,including more than 770 000 patients with acute myocardial infarction,and achieved positive results:significantly increasing the proportion of reperfusion therapy for acute ST-segment elevation myocardial infarction patients,ensuring the treatment of myocardial infarction patients in a short time,shortening the length of patient hospitalization,and reducing the hospitalization costs and mortality of patients.Through the construction of Chest Pain Center,the treatment process was significantly optimized and the prognosis of patients was improved.At present,the construction and quality control of Chest Pain Centers still need to be further promoted.In some areas,the construction proportion of Chest Pain Centers and the level of diagnosis and treatment of chest pain need to be improved,patient delay is still an important challenge for the treatment of acute chest pain in China.

Objective:To understand the incidence trend of brucellosis over time in Shandong Province from 2004 to 2023, and provide evidence for the prevention and control of brucellosis.Methods:The incidence data of brucellosis in Shandong from 2004 to 2023 were collected from China Disease Prevention and Control Information System. The annual change percentage (APC) and annual average change percentage (AAPC) of the incidence rate were calculated by using Joinpoint regression model. A age-period-cohort model was used to analyze changes in brucellosis incidence with age, period, and birth cohort.Results:The average annual incidence of brucellosis was 1.76/100 000 in Shandong from 2004 to 2023. The Joinpoint regression analysis results showed that the reported incidence of brucellosis increased by an average of 92.0% and 18.9% each year from 2004 to 2010 and from 2010 to 2014, respectively, and decreased by an average of 0.2% each year from 2014 to 2023. The results of APC model showed that the incidence of brucellosis increased first and then decreased with age ( χ2=176.92, P<0.001), and incidence of brucellosis showed slow increase and rapid increase first, then decrease ( χ2=2 921.03, P<0.001) over time. The risk for brucellosis reached peak in 2016 ( RR=5.29, 95% CI: 4.96-5.65) and became the lowest in 2006 ( RR=0.24, 95% CI: 0.21-0.28). The incidence increased in later birth cohort ( χ2=348.88, P<0.001), the AAPCs of all the age groups were between 15.0% and 40.0%, and the older the age, the greater the risk ( χ2=348.77, P<0.001). Conclusions:From 2004 to 2023, the reported incidence of brucellosis in Shandong showed a significant age-period-cohort effect, which increased first and then decreased, first increased and then decreased with age, increased slowly and rapidly first, then decreased over time, and increased in later birth cohort. It is necessary to conduct targeted prevention and control, health education to reduce the risk for brucellosis.

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.