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.

Objective To investigate the dosimetric difference between manual and inverse optimization in 3-dimensional (3D) brachytherapy for gynecologic tumors. Methods This retrospective study was conducted among a total of 110 patients with gynecologic tumors undergoing intracavitary combined with interstitial brachytherapy or interstitial brachytherapy. Based on the original images, the brachytherapy plans were optimized for each patient using Gro, IPSA1, IPSA2 (with increased volumetric dose limits on the basis of IPSA1) and HIPO algorithms. The dose-volume histogram (DVH) parameters of the clinical target volume (CTV) including V200, V150, V100, D90, D98 and CI, and the dosimetric parameters D2cc, D1cc, and D0.1cc for the bladder, rectum, and sigmoid colon were compared among the 4 plans. Results Among the 4 plans, Gro optimization took the longest time, followed by HIPO, IPSA2 and IPSA1 optimization. The mean D90, D98, and V100 of HIPO plans were significantly higher than those of Gro and IPSA plans, and D90 and V100 of IPSA1, IPSA2 and HIPO plans were higher than those of Gro plans (P<0.05), but the CI of the 4 plans were similar (P>0.05). For the organs at risk (OARs), the HIPO plan had the lowest D2cc of the bladder and rectum;the bladder absorbed dose of Gro plans were significantly greater than those of IPSA1 and HIPO (P<0.05). The D2cc and D1cc of the rectum in IPSA1, IPSA2 and HIPO plans were better than Gro (P<0.05). The D2cc and D1cc of the sigmoid colon did not differ significantly among the 4 plans. Conclusion Among the 4 algorithms, the HIPO algorithm can better improve dose coverage of the target and lower the radiation dose of the OARs, and is thus recommended for the initial plan optimization. Clinically, the combination of manual optimization can achieve more individualized dose distribution of the plan.

Objective To analyze the changes in the disease spectrum of hospitalized patients with neurological diseases in a tertiary hospital in the past 5 years,in order to effectively develop targeted disease prevention and treatment strategies.Methods Collect case data of neurological diseases in a tertiary hospital from January 1,2018 to December 31,2022,and use ICD-10 coding for disease classification,and analyze the disease type,gender,age groups,and other factors.Results A total of 9060 patients with neurological diseases were admitted in the past five years.In 2020,the number of discharged patients affected by the COVID-19 was the smallest,accounting for 15.96% ,and in 2022,the number was the largest,accounting for 24.05% .The number of cases showed an increasing trend.There was no statistically significant difference in the composition of male and female patients;There is a statistically significant difference in the number of cases among patients of different age groups,and the incidence categories are different;The top 10 diseases in the ranking of neurological diseases are:transient ischemic attack,headache,spinal nerve disease,neurological disorders,epilepsy,Parkinson's disease,sleep disorders,paralysis,other brain diseases,hydrocephalus.The distribution of the top 10 diseases by gender has statistical significance.Conclusion The hospital can formulate the diagnosis and treatment technology for different age groups according to the distribution characteristics of disease spectrum,carry out comprehensive prevention and treatment measures for key groups,strengthen the construction of key special-ties and allocate health resources properly.

Objective To investigate the dosimetric difference between manual and inverse optimization in 3-dimensional (3D) brachytherapy for gynecologic tumors. Methods This retrospective study was conducted among a total of 110 patients with gynecologic tumors undergoing intracavitary combined with interstitial brachytherapy or interstitial brachytherapy. Based on the original images, the brachytherapy plans were optimized for each patient using Gro, IPSA1, IPSA2 (with increased volumetric dose limits on the basis of IPSA1) and HIPO algorithms. The dose-volume histogram (DVH) parameters of the clinical target volume (CTV) including V200, V150, V100, D90, D98 and CI, and the dosimetric parameters D2cc, D1cc, and D0.1cc for the bladder, rectum, and sigmoid colon were compared among the 4 plans. Results Among the 4 plans, Gro optimization took the longest time, followed by HIPO, IPSA2 and IPSA1 optimization. The mean D90, D98, and V100 of HIPO plans were significantly higher than those of Gro and IPSA plans, and D90 and V100 of IPSA1, IPSA2 and HIPO plans were higher than those of Gro plans (P<0.05), but the CI of the 4 plans were similar (P>0.05). For the organs at risk (OARs), the HIPO plan had the lowest D2cc of the bladder and rectum;the bladder absorbed dose of Gro plans were significantly greater than those of IPSA1 and HIPO (P<0.05). The D2cc and D1cc of the rectum in IPSA1, IPSA2 and HIPO plans were better than Gro (P<0.05). The D2cc and D1cc of the sigmoid colon did not differ significantly among the 4 plans. Conclusion Among the 4 algorithms, the HIPO algorithm can better improve dose coverage of the target and lower the radiation dose of the OARs, and is thus recommended for the initial plan optimization. Clinically, the combination of manual optimization can achieve more individualized dose distribution of the plan.

Objective:To evaluate and summary the relevant evidence of emergency target blood pressure management in acute aortic dissection, so as to provide guidance for the evidence-based practice of emergency target blood pressure management.Methods:According to the "6S" evidence pyramid model, the evidence about emergency target blood pressure management of acute aortic dissection in various databases and professional association websites at home and abroad was retrieved, including clinical decision, guidelines, expert consensus, systematic evaluation, randomized controlled trial, cohort study, case series, etc. Two researchers used corresponding literature quality evaluation tools to evaluate the quality of the included literature, extracted and summarized the evidence of the literature above grade B.Results:A total of 22 articles were included in this study, including 6 clinical decisions, 5 guidelines, 7 expert consensus, 1 systematic evaluation, 1 randomized controlled trial, 1 cohort study and 1 case series, forming 37 best evidences, including 9 topics such as target value setting, management strategies, disease observation, medical history collection, monitoring methods, vasoactive drugs, non vasoactive drugs, auxiliary examination, health education.Conclusions:The summarized best evidence provides a reference for emergency medical staff to manage the emergency target blood pressure of acute aortic dissection. It is recommended that emergency medical staff follow the summarized best evidence to formulate an individualized target blood pressure management scheme for patients.

Objective:To construct a prediction model of gastric cancer related methylation using machine learning algorithms based on genomic data.Methods:The gene mutation data, gene expression data and methylation chip data of gastric cancer were downloaded from The Caner Genome Atlas database, feature selection was conducted, and support vector machine (radial basis function), random forest and error back propagation (BP) neural network models were constructed; the model was verified in the new data set.Results:Among the three machine learning models, BP neural network had the highest test efficiency (F1 score=0.89,Kappa=0.66, area under curve=0.93).Conclusion:Machine learning algorithms, particularly BP neural network, can be used to take advantages of the genomic data for discovering molecular markers, and to help identify characteristic methylation sites of gastric cancer.

Long non-coding RNAs (lncRNAs) regulate various biological processes ranging from gene expression to animal behavior. Although protein-coding genes, microRNAs, and neuropep-tides play important roles in the regulation of phenotypic plasticity in migratory locust, empirical studies on the function of lncRNAs in this process remain limited. Here, we applied high-throughput RNA-seq to compare the expression patterns of lncRNAs and mRNAs in the time course of locust phase change. We found that lncRNAs responded more rapidly at the early stages of phase transition. Functional annotations demonstrated that early changed lncRNAs employed different pathways in isolation and crowding phases to cope with changes in the population density. Two overlapping hub lncRNA loci in the crowding and isolation networks were screened for func-tional verification. One of them, LNC1010057, was validated as a potential regulator of locust phase change. This work offers insights into the molecular mechanism underlying locust phase change and expands the scope of lncRNA functions in animal behavior.

Under the policy background of zero addition of drugs and consumables in public hospitals, with clinical practice as the guide and information platform as the means, the hospital constructed an intelligent management system for hospitals′ drugs and consumables through the Internet of things. The hospital adopted the intelligent medicine cabinet extended ward management, consumables " one material, one code" two-level warehouse management mode, reengineering the material supply process.Finally, it can realize the whole process traceability of information, unify the flow of goods and data, save human resources, improve the efficiency of operation and management, and achieve the purpose of ensuring safety, reducing costs and increasing benefits.

Edong Healthcare Group is cited as an example to summarize its practice of centralized purchasing of supplies in the recent two years.In addition to a success in its process and mechanism, the authors analyzed some challenges for the purpose of furthering the group-based reform of public hospitals.