Objective: To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. Methods: A multidisciplinary collaborative model was adopted to develop a preoperative anemia management system that integrates intelligent early warning, standardized treatment pathways, and quality control. The system utilizes natural language processing technology to automatically capture laboratory data and establish evidence-based medical decision support functions. A pre-post study design was employed to compare changes in preoperative anemia screening rates, preoperative anemia intervention rates, reasonable use of iron supplements, and perioperative red blood cell transfusion rates before and after system implementation. Results: After system implementation, the standardization of anemia diagnosis and treatment significantly improved: 1) Screening effectiveness: The anemia screening rate increased to 50.00% (an increase of 27.24%); 2) Intervention effectiveness: The anemia treatment rate rose to 56.30% (an increase of 14.02%); 3) Treatment standardization: The reasonable use rate of iron supplements increased to 55.33% (an increase of 21.02%); the red blood cell transfusion rate decreased to 18.29% (a decrease of 4.07%), and the amount of red blood cell transfusions was reduced by 291 units. Conclusion: This system achieves full-process management of preoperative anemia through information technology, significantly enhancing the standardization of diagnosis and treatment as well as intervention effectiveness, providing an effective solution for perioperative anemia management.

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.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

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:Based on the background of high-quality development,we analyze the operational efficiency of traditional Chinese medicine(TCM)hospitals in China's Yangtze River Economic Belt in 2021 and explore the impact of external environmental factors on operational efficiency,so as to provide a reference for promoting the high-quality development of TCM hospitals in the Yangtze River Economic Belt.Methods:The three-stage DEA model was used to analyze the operational efficiency of TCM hospitals in 11 provinces and cities in the Yangtze River Economic Zone in China in 2021.Results:After three-stage DEA analysis,the values of comprehensive efficiency,pure technical efficiency and scale efficiency of TCM hospitals in China's Yangtze River Economic Belt are 0.976,0.986 and 0.990,respectively.5 provinces and cities,Shanghai,Jiangsu,Hunan,Chongqing and Guizhou,are efficient before and after the adjustment,and the comprehensive efficiency of Zhejiang,Anhui,Hubei,Jiangxi,Sichuan and Yunnan have increased compared with that before the adjustment.Ranking of the average value of the comprehensive efficiency of TCM hospitals operation in the three major city clusters of the Yangtze River Economic Belt after adjustment:Chengdu-Chongqing city cluster(0.998)>city cluster in the Yangtze River Delta(0.964)>city cluster in the middle reaches of the Yangtze River(0.962).Conclusion:The operational efficiency of TCM hospitals in the Yangtze River Economic Zone has been underestimated,and the comprehensive efficiency is mainly affected by scale efficiency;there are differences in the operational efficiency of TCM hospitals in the three major urban agglomerations,and balanced development is needed between regions;the operational efficiency of TCM hospitals is affected by the external environment,and it is necessary to improve the external environment;it is necessary to strengthen the construction of digital and informatization of TCM,and to pay attention to the role of talents in TCM,so as to promote the high-quality development of TCM hospitals.

Objective:To analyze the current development status and spatial distribution characteristics of traditional Chinese medicine (TCM) hospitals in China, predict the changing trends of the number of TCM hospitals, the number of beds, and the number of physicians, and provide references for the development of TCM hospitals and the formulation of related policies.Methods:From the official websites of the National Bureau of Statistics and the State Administration of Traditional Chinese Medicine, the total population and number of TCM hospitals of 31 provinces (excluding China′s Hong Kong, Macao, and Taiwan) in China from 2013 to 2022 were included, as well as the number of beds and practicing (assistant) physicians in TCM hospitals from 2013 to 2021. The grey prediction model was applied to predict the changing trends of the number of TCM hospitals, beds and physicians. Using the global Moran′s I index in spatial autocorrelation analysis, the distribution of TCM hospitals per 10 000 people in China was analyzed by spatial correlation analysis, and local G coefficient was analyzed by local hot spots.Results:From 2013 to 2027, the number of TCM hospitals, beds and practicing (assistant) TCM physicians in China all showed an increasing trend year by year. The number of TCM hospitals per 10 000 people in China showed a spatial correlation between 2013 and 2022 ( P<0.05). The hot spots of TCM hospitals were mainly concentrated in North China and Northeast China, while the cold spots were mainly concentrated in southeast coastal areas and Northwest China. Conclusions:The number of TCM hospitals in China is increasing year by year, but it is necessary to control the reasonable increase and avoid blind expansion. It is necessary to formulate regional policies of TCM hospitals according to local conditions and pay attention to the individuation of policies. Focus on hot and cold areas to promote balanced development of TCM hospitals.

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

Objective To investigate the expression of the histone deacetylase SIRT7 in glioma cells and its impact on epithelial-mesenchymal transformation(EMT),as well as its effects on proliferative,migratory and invasive capabilities of glioma cells.Methods Bioinformatics analysis was conducted on data from glioma patients in the Cancer Genome Atlas(TCGA)and the Chinese glioma Genome Atlas(CGGA)databases to explore the expression of SIRT7 gene in gliomas and its correlation with tumor grading,molecular characteristics and patient clinical prognosis.Glioma cells were randomly divided into control,SIRT7 knockdown,SIRT7 overexpression,drug treatment(10 μmol/L hydrochlorothiazide)and drug(10 μmol/L hydrochlorothiazide)+SIRT7 overexpression groups.The CCK-8 assay,cell scratch assay and Transwell assay were used to observe the effects of upregulating and downregulating SIRT7 expression on glioma cell proliferation,migration and invasion.RT-qPCR and Western blotting were employed to detect the effects of SIRT7 on the expression of neural cadherin(N-cadherin),Vimentin,E-cadherin,transforming growth factor-β(TGF-β),Ki-67,and Smad3 protein in glioma cells.Nude mouse tumor-bearing experiments were conducted to observe the effect of SIRT7 knockdown on glioma growth.Results Higher expression levels of SIRT7 gene were associated with poorer clinical prognosis(P＜0.0001).SIRT7 expression levels were significantly correlated with tumor grading and 1p19q coding status(P＜0.01).Compared with normal HA cells,glioma cells showed significantly increased SIRT7 expression levels(P＜0.01).CCK-8 assay results indicated that,compared with control group,the proliferation activity of glioma cells in SIRT7 knockout group was significantly decreased(P＜0.01),while SIRT7 overexpression group showed significantly increased proliferation activity(P＜0.01).EdU assay results showed that,compared with control group,the proportion of glioma cells in the proliferative stage was significantly decreased in SIRT7 knockdown group(P＜0.01),and significantly increased in SIRT7 overexpression group(P＜0.01).Western blotting results revealed that,compared with control group,the protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin were significantly decreased in SIRT7 knockdown group(P＜0.01),while the expression level of E-cadherin protein was significantly increased(P＜0.05).SIRT7 overexpression group showed significantly increased protein expression levels of TGF-β,Smad3,N-cadherin and Vimentin(P＜0.05),and a significantly decrease in E-cadherin protein expression level(P＜0.05).Scratch assay results indicated that,compared with control group,the migration ability of cells in SIRT7 knockdown group and drug group was significantly decreased(P＜0.01),and SIRT7 overexpression group showed significantly increased cell migration ability(P＜0.05).Compared with drug group,drug+SIRT7 overexpression group exhibited significantly increased cell migration ability(P＜0.01).Transwell assay results showed that,compared with control group,the migration and invasion abilities of cells in SIRT7 knockdown group and drug group were significantly decreased(P＜0.01),and SIRT7 overexpression group exhibited significantly increased migration and invasion abilities(P＜0.01).Compared with drug group,drug+SIRT7 overexpression group showed significantly increased migration and invasion abilities(P＜0.01).Nude mouse tumor-bearing assay results indicated that the volume and weight of glioma in SIRT7 knockdown group were significantly reduced compared with control group(P＜0.01).Conclusions Glioma patients with high SIRT7 expression have poorer clinical prognosis.SIRT7 can regulate the TGF-β/Smad3 pathway to mediate EMT,promoting the proliferation and migration of glioma cells.SIRT7 knockdown can inhibit the growth of transplanted gliomas in nude mice.