1.Deep learning-based automatic morphological assessment of the aortic root in bicuspid aortic valve patients before transcatheter aortic valve replacement
Guozhong CHEN ; Yu MAO ; Aiqing JI ; Yingsong HUO ; Qian CHEN ; Wei WANG ; Jian YANG ; Jian LIU ; Haibo ZHANG ; Chenming MA ; Yifei QU ; Hui XU ; Zhengcan WU
Chinese Journal of Radiology 2025;59(9):1029-1036
Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955
2.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
3.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
4.A random forest prediction study on the 3-year recurrence-free survival of early and middle stage esophageal cancer after total endoscopic resection
Sanhu YANG ; Yan LI ; Lijun HUANG ; Zhenke YAN ; Xu LIU ; Wanshan LI ; Xiang JI
Journal of Clinical Surgery 2025;33(5):486-492
Objective To construct a predictive model for the 3-year recurrence-free survival(RFS)after total endoscopic resection of early and mid-stage esophageal cancer,and to test it,in order to provide decision support for standardized management after total endoscopic resection of early and mid-stage esophageal cancer.Methods A retrospective study was conducted to include 306 patients with early-to-mid stage esophageal cancer who underwent total endoscopic resection in our hospital from January 2018 to December 2020.The patients were divided into a modeling set(n=204)and a validation set(n=102)according to a 2∶1 ratio.Univariate analysis and random forest algorithm were used to screen variables,and Cox regression analysis was used to analyze the factors affecting the 3-year RFS after total endoscopic resection for early-to-mid stage esophageal cancer.The R language was used to construct a nomogram prediction model for model validation,and the receiver operating characteristic curve(ROC curve)was drawn to calculate the area under the curve(AUC).The discrimination of the prediction model was evaluated,and the calibration curve and decision curve(DCA curve)were used to evaluate the predictive performance and clinical applicability of the prediction model.Results Among the 306 patients with early and mid-stage esophageal cancer who underwent total endoscopic resection,18 died 3 years after the operation,55 relapsed,233 achieved RFS,and the 3-year RFS rate was 76.14%.Through univariate and random forest algorithm screening,seven factors were identified as being associated with the RFS of patients three years after surgery.These factors were entered into a Cox regression analysis,and the results showed that positive abdominal lymph nodes,vascular cancer thrombus,clinical stage Ⅲ,gross type of erosion,age ≥ 65 years,and tumor diameter>3 cm were risk factors for RFS three years after surgery(P<0.05).Based on this,a nomogram prediction model for RFS three years after full endoscopic resection for early-to-mid stage esophageal cancer was constructed.Internal and external validation showed that the consistency index of the prediction model in the modeling set was 0.881,and the consistency index in the validation set was 0.867.The ROC curve validation showed that the AUC of the prediction model in the modeling set and validation set were 0.855(95%CI:0.778-0.932)and 0.826(95%CI:0.763-0.890),respectively.The DCA curve validation showed that the risk threshold of the modeling set and validation set were 0-0.95 and 0-0.77,respectively,when the model could achieve high net benefits.Conclusion The 3-year RFS after total endoscopic resection for early and middle stage esophageal cancer is related to multiple factors.The nomogram model based on clinical stage Ⅲ,positive abdominal lymph nodes,vascular tumor thrombus,and gross type of erosion has good clinical utility for predicting the 3-year RFS of patients after surgery,and is of guiding significance for medical staff in making decisions about the management of early and middle stage esophageal cancer after surgery.
5.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
6.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
7.Analysis of clinical and endoscopic characteristics of autoimmune gastritis
Yijun ZHANG ; Rui JIN ; Tianming XU ; Ji LI ; Jing WANG ; Aiming YANG ; Jingnan LI
Chinese Journal of Digestion 2025;45(4):235-240
Objective:To investigate the clinical and endoscopic characteristics of patients with autoimmune gastritis (AIG).Methods:From January 1, 2013 to December 31, 2023, 73 AIG patients who visited Peking Union Medical College Hospital were retrospectively enrolled. The clinical data of all the patients were analyzed, including gender, age, symptoms, laboratory examination results (such as serum hemoglobin, vitamin B 12, serum iron, gastrin, anti-parietal cell antibody (APCA), anti-intrinsic factor antibody (AIFA), Helicobacter pylori ( HP) infection status; the indicators were judged based on the normal reference value), and endoscopic and histopathological examination results. Descriptive statistical methods were used for statistical analysis. Results:Among the 73 AIG patients, there were 27 males (37.0%) and 46 females (63.0%), with a median age of 57 years old (ranged from 25 to 85 years old). Among the 73 AIG patients, 68 patients received APCA test, with a positivity rate of 88.2% (60/68); 67 patients took the AIFA test, with a positivity rate of 52.2%(35/67); 62 patients underwent both APCA and AIFA tests, of which 22 patients (35.5%) showed double positive. Serum level of vitamin B 12 was detected in 59 patients, and decreased in 27 cases (median level: 0.100 ng/L, mean level: 0.102 ng/L). Gastrin level was detected in 58 patients, and increased in 55 cases (median level: 0.930 ng/L, mean level: 1.203 ng/L). The levels of serum iron and ferritin were tested in 52 patients, the level of serum iron of 5 cases decreased, and the level of ferritin of 17 cases decreased (median level: 780.0 and 26.0 μg/L, mean level: 807.8 and 76.0 ng/L, respectively).Among the 73 AIG patients, the urea breath test was performed in 12 patients, and the result was positive in 6 cases. Endoscopic rapid urease test was performed in 69 patients, and the result was positive in 11 cases (15.9%). Regular blood analysis was performed in 71 patients, 24 cases (33.8%) were diagnosed with anemia, the median age of patients with anemia was 55 years old, and male-to-female ratio was 1∶5. There were 6 cases of iron-deficiency anemia and 5 cases of pernicious anemia. The endoscopic examination results of 73 patients indicated that 65 cases (89.0%) with mucosal atrophy under endoscopy, including 47 cases (64.4%) with mucosal atrophy in the gastric fundus and body, and 18 cases (24.7%) with whole gastric atrophy, more obviously in the gastric body. The pathological examination results showed type Ⅰ gastric neuroendocrine tumor(g-NET) in 35 cases (47.9%). Conclusions:The early clinical symptoms of AIG patients are nonspecific, often present with anemia and vitamin B 12 deficiency. Close monitoring of serological markers including APCA, AIFA and gastrin is essential. For patients diagnosed or suspected with AIG, intervals of endoscopic surveillance should be shortened to prevent the genesis and development of neoplasms such as g-NET.
8.Expert consensus on combined screening for common cancers(2025 edition)
Kexin CHEN ; Wanqing CHEN ; Yubei HUANG ; Zhangyan LYU ; Fangfang SONG ; Changfa XIA ; Yongjie XU ; Lei YANG ; Chao SHENG ; Yacong ZHANG ; Peng WANG ; Yunmeng ZHANG ; Yuting JI ; Jingjing LI ; Wenxuan LI ; Jie WU ; Qianyun JIN ; Fengju SONG
Chinese Journal of Oncology 2025;47(7):533-557
Malignant tumors (commonly referred to as cancer) represent a major global public health challenge and contribute significantly to the worldwide disease burden. Early screening plays a critical role in improving detection rates, enabling timely intervention, and enhancing patient survival rates. However, current cancer screening guidelines primarily focus on site-specific screening, which may not fully address the need for comprehensive early detection. A scientifically rational, multi-cancer screening approach offers several advantages: it optimizes the use of biological samples, reduces time costs for participants, enhances the efficiency and comprehensiveness of screening, and minimizes overall expenses. Such an approach also facilitates the rational allocation of healthcare resources, ultimately helping to reduce the societal burden of cancer. To address this need, the Cancer Epidemiology Committee of the Chinese Anti-Cancer Association has developed the Expert Consensus on Combined Screening for Common Cancers in China. This consensus integrates multidisciplinary expertise and synthesizes the latest domestic and international researches on cancer screening, early detection, and treatment for prevalent malignancies. Drawing upon China's unique demographic and healthcare context, as well as practical screening experiences, the consensus provides evidence-based recommendations on target populations, screening technologies, and procedural workflows for multi-cancer screening. These guidelines align with the principles and methodologies established by the World Health Organization (WHO), aiming to enhance the effectiveness of combined cancer screening in China, improve early detection rates, and provide a scientific foundation for national cancer prevention and control strategies.
9.Stearic acid affects the expression of IL-17 in CD4+T cells from ketosis cows through CD36
Ziwei JI ; Siyao LI ; Haixin ZHANG ; Ziwei LI ; Shangmingzhu ZHANG ; Wei YANG ; Chuang XU ; Bingbing ZHANG
Chinese Journal of Veterinary Science 2025;45(3):602-610
The peripheral blood of healthy or ketosis dairy cows was collected,and CD4+T cells were isolated.The expressions of lipid synthesis related proteins fatty acid synthase(FASN),acetyl coenzyme A carboxylase 1(ACC1),cluster of differentiation 36(CD36)and store-operated calcium entry(SOCE)related proteins ORAIl,ORAI2,ORAI3,STIM1,STIM2 were detected by Western blot.IL-17 cells were detected by flow cytometry.CD4+T cells were isolated from the spleen of 1-day-old calves and cultured in vitro.Cells were treated and divided into control(Ctrl)group,si-lenced CD36(siCD36)group,stearic acid(SA)group,and SA+siCD36 group.Cells in the Ctrl and SA groups were transfected with 75 pmol/L negative control siRNA for 48 h,and then stimulated with 200 μmol/L SA for 24 h;Cells in the siCD36 group and SA+siCD36 group were transfected with 75 pmol/L CD36 siRNA for 48 h,and then stimulated with 200 μmol/L SA for 24 h in the SA+siCD36 group.The protein expression of FASN,CD36,ACC1,ORAI1,ORAI2,ORAI3,STIM1 and STIM2 was detected by Western blot,and IL-17 cells were detected by flow cytometry.The results showed that the expression of IL-17 in peripheral blood CD4+T cells of ketosis dairy cows was significantly increased compared to that of healthy cows(P<0.01).Additionally,the protein level of FASN,CD36,STIM1(P<0.05),and ACC1,ORAI2,ORAI3,STIM2(P<0.01)were up-regulated.Compared with the Ctrl group,the protein expression levels of CD36,ACC1 and ORAI3(P<0.05)were up-regulated in the SA group,as well as the protein expression of FASN and STIM1(P<0.01).Additionally,the expression of IL-17 was significantly increased(P<0.05).Compared with the SA group,there was a decrease in the protein expression of STIM1,ORAI1(P<0.05)and CD36,ACC1,FASN,ORAI2(P<0.01)in the siCD36+SA group,as well as IL-17(P<0.05).These results suggest that SA can promote the expression of IL-17 in CD4+T cells in ketosis cows by regulating fatty acid synthesis and activating SOCE channels through CD36.
10.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

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