1.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
2.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.
3.Epidemic factors in foodborne parasitic diseases in ethnic minority areas of Guizhou Province from a One Health perspective
Li-dan LU ; Mu-xin CHEN ; Shan CAI ; Dan-ya SHE ; Guang-chu LIN ; Song-ping LI ; Kai-neng MO ; Cheng ZHOU ; Ling LI
Chinese Journal of Zoonoses 2025;41(5):480-486
This study was aimed at understanding the prevalence and influencing factors of food-borne parasitic diseases in ethnic minority areas of Guizhou Province,to provide a scientific basis for the development of appropriate intervention measures based on the human-animal-environment One Health concept.In 2023,the infection status of the human population,reservoir hosts,intermediate hosts,food-borne parasitic diseases,and related social and environmental factors were investigated in Congjiang County in Qidongnan Miao and Dong Autonomous Prefecture;Luodian County in Qiannan Buyi and Miao Autonomous Prefecture;and Ceheng County in Qianxinan Buyi and Miao Autonomous Prefecture.At least 1 000 individuals were sampled from each county,along with at least 50 insect-protected host samples from each location.Food-borne parasite infections were detected with the modified Kato thick smear method.A questionnaire survey was administered to the population.Detection of food-borne parasitic metacercariae was performed in intermediate host fish through the flaking and digestion method,and in crabs through the pounding and sedimentation method.The chi-square test was used to compare rates,and logistic regression was applied for multivariate analysis.A total of 3 023 questionnaires and fecal samples were collected.Males accounted for 47.50%,females accounted for 52.50%,and members of ethnic minorities accounted for 96.06%.A total of 186 food-borne parasitic infections were identified,and the infection rate was 6.15%.Five insect species were detected,which showed an infection rate of 5.39%.The infection rate of Clonorchis sinensis was 0.33%,that of Taenia was 0.40%,that of Heteroceles was 0.17%,that of Acanthus was 0.17%,and that of Echinostoma was 0.03%.Human infections with Echinostomus colloides and Echinostomia transferoris had not previously been reported in China.Single-factor analysis revealed statistically significant differences in food-borne parasite infections according to various factors,including the consumption of untreated water,raw fish and shrimp,raw pig blood,raw cow gastric juice,and raw pork and beef,as well as raw pig and cow viscera(P<0.05).Multivariate analysis indicated that the risk factors for food-borne parasite infections among residents in minority areas of Guizhou Province included the consumption of raw pig blood(OR=2.841,95%CI:1.809-4.463),raw cow gastric juice(OR=2.122,95%CI:1.297-3.469),and raw fish and shrimp(OR=1.779,95%CI:1.049-3.018).A total of 173 fecal samples of the reservoir host were examined,which showed a rate of food-borne parasite infection of 5.2%.A total of 510 intermediate host fish were examined,which showed a 4.51%positivity rate of encysted metacercaria of Clonorchis sinensis.The crab,pig,and beef samples were not positive.In conclusion,food-borne parasitic infections were prevalent in ethnic minority regions of Guizhou Province,and consumption of raw food were influencing factors.A focus on populations with raw food consumption habits,including raw pig blood,cow gastric juice,fish and shrimp,is essential.Concurrently,monitoring of animal hosts must be strengthened to perform key interventions according to the One Health concept.
4.Synthesis of A New Naphthalenesulfonamide-based"Turn-on"Fluorescent Probe for Rapid Detection of Glyphosate
Rong-Rong ZHAO ; Hong-Lin LIU ; Ying-Ping HUANG ; Cui-Wen DENG ; Song-Yan LI ; Shui-Lian YU ; Mao-Sheng TAO ; Yi-Qun TIAN ; Xi YUAN
Chinese Journal of Analytical Chemistry 2025;53(6):903-913
Widespread utilization of glyphosate has led to environmental residues,posing potential threats to ecological systems and human health.Traditional methods for detection of glyphosate are limited by specialized equipment and operational techniques,resulting in inefficient responses.Therefore,it is urgent to develop a convenient,sensitive and accurate detection method for detection of glyphosate.Herein,a new naphthalenesulfonamide-based"Turn-on"fluorescent probe was synthesized using 2-chloroaniline and dansyl chloride as raw materials through a one-step process,which showed a good linear relationship between the glyphosate concentration in concentration range of 0.003-70 μmol/L and the fluorescence intensity(R2=0.995),with a detection limit of 2.73 nmol/L(S/N=3).Analytical techniques such as nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS)were used to investigate the interaction mechanism between the fluorescent probe and glyphosate.The results indicated that a nucleophilic substitution reaction occurred between the probe and the secondary amine(—NH—)of glyphosate,inducing a photoinduced electron transfer(PET)effect which enhanced the fluorescence intensity by 11.2 times.The probe showed good anti-interference ability towards coexisting metal ions,anions and pesticides in water.When applied to determination of glyphosate in the samples such as tap water,river water(Xiangxi River Reservoir),soil,soybeans,and corn,the spiking recoveries ranged from 94.7%to 109.9%,demonstrating the high accuracy and broad applicability of this detection method.A portable test strip based on this fluorescent probe was developed for rapid semi-quantitative analysis of glyphosate.The developed method was rapid,sensitive,and portable,providing theoretical and technical support for on-site measurement of environmental contaminants.
5.Retropharyngeal lymph node metastases from head and neck cancer removed by transoral robotic surgery
Ming SONG ; Ping HAN ; Shuwei CHEN ; Faya LIANG ; Ankui YANG ; Quan ZHANG ; Peiliang LIN ; Xiaoming HUANG
Chinese Journal of Otorhinolaryngology Head and Neck Surgery 2025;60(3):292-299
Objective:To evaluate the safety, and feasibility of transoral robot-assisted retropharyngeal lymph node (RPLN) dissection.Methods:Clinical data of head and neck cancer patients who underwent transoral robot-assisted RPLN dissection at the Department of Otorhinolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, and Sun Yat-sen University Cancer Centre from December 2017 to March 2024 were retrospectively analyzed. A total of 35 patients(22 males, 13 females, aged 47.4±13.4 years old) with RPLN metastases from head and neck cancer, including 20 cases of nasopharyngeal cancer, 9 cases of thyroid cancer, 2 cases of salivary adenocarcinoma, 2 cases of tonsil cancer, and 2 cases of hypopharyngeal cancer. Operation time, intraoperative bleeding and complications, postoperative nasogastric tube retention time, hospital stay and complications were evaluated. Statistical analysis was performed using SPSS 22.0 software.Results:All patients successfully received transoral robot-assisted RPLN dissection without intermediate open surgery, with removals of 2 (1, 3) RPLNs. The total operation time was 130 (102, 210) minutes. The intraoperative bleeding was 50 (20, 100) ml, and there was no major bleeding or organ damage during the operation. Prophylactic tracheotomy was performed in 8 cases, and postoperatively nasogastric tubes were left in 22 patients, with retention time of 10.5 (7.5, 14.0) days. Postoperative hospital stay was 5 (4, 9) days. Postoperative complications included incision dehiscence in 4 cases and dysphagia in 4 cases. The median postoperative follow-up was 23.4 months, with progression or recurrence in 5 patients, including regional recurrence in 3 patients, lung metastasis in 1 patient, and bone metastasis in 1 patient. The 2-year regional failure-free survival and disease-free survival rates were 91.43% and 85.71%, respectively.Conclusion:Transoral robot-assisted RPLN dissection is a safe and feasible surgical method with less trauma, fewer complications, and higher safety. Patients need to be carefully selected at the initial stage of application.
6.Graph Neural Networks and Multimodal DTI Features for Schizophrenia Classification: Insights from Brain Network Analysis and Gene Expression.
Jingjing GAO ; Heping TANG ; Zhengning WANG ; Yanling LI ; Na LUO ; Ming SONG ; Sangma XIE ; Weiyang SHI ; Hao YAN ; Lin LU ; Jun YAN ; Peng LI ; Yuqing SONG ; Jun CHEN ; Yunchun CHEN ; Huaning WANG ; Wenming LIU ; Zhigang LI ; Hua GUO ; Ping WAN ; Luxian LV ; Yongfeng YANG ; Huiling WANG ; Hongxing ZHANG ; Huawang WU ; Yuping NING ; Dai ZHANG ; Tianzi JIANG
Neuroscience Bulletin 2025;41(6):933-950
Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans
;
Schizophrenia/pathology*
;
Diffusion Tensor Imaging/methods*
;
Male
;
Female
;
Adult
;
Brain/metabolism*
;
Young Adult
;
Middle Aged
;
White Matter/pathology*
;
Gene Expression
;
Nerve Net/diagnostic imaging*
;
Graph Neural Networks
7.Effects of Hot Night Exposure on Human Semen Quality: A Multicenter Population-Based Study.
Ting Ting DAI ; Ting XU ; Qi Ling WANG ; Hao Bo NI ; Chun Ying SONG ; Yu Shan LI ; Fu Ping LI ; Tian Qing MENG ; Hui Qiang SHENG ; Ling Xi WANG ; Xiao Yan CAI ; Li Na XIAO ; Xiao Lin YU ; Qing Hui ZENG ; Pi GUO ; Xin Zong ZHANG
Biomedical and Environmental Sciences 2025;38(2):178-193
OBJECTIVE:
To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality.
METHODS:
A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters.
RESULTS:
The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights.
CONCLUSION
Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans
;
Male
;
Semen Analysis
;
Adult
;
Sperm Motility
;
Hot Temperature/adverse effects*
;
China
;
Middle Aged
;
Spermatozoa/physiology*
;
Young Adult
8.Development and validation of a prediction score for subtype diagnosis of primary aldosteronism.
Ping LIU ; Wei ZHANG ; Jiao WANG ; Hongfei JI ; Haibin WANG ; Lin ZHAO ; Jinbo HU ; Hang SHEN ; Yi LI ; Chunhua SONG ; Feng GUO ; Xiaojun MA ; Qingzhu WANG ; Zhankui JIA ; Xuepei ZHANG ; Mingwei SHAO ; Yi SONG ; Xunjie FAN ; Yuanyuan LUO ; Fangyi WEI ; Xiaotong WANG ; Yanyan ZHAO ; Guijun QIN
Chinese Medical Journal 2025;138(23):3206-3208
9.Hydroxysafflor yellow A inhibits lipopolysaccharide-induced vascular smooth muscle cell-derived foam cell formation through the NLPR3/IL-1β/PCSK9 signaling pathway via activation of autophagy.
Lin LIU ; Yingyun LI ; Boyu LIU ; Guoting LI ; Changchao YANG ; Junna SONG ; Qingzhuo CUI ; Jingshan ZHAO
Chinese Medical Journal 2025;138(23):3195-3197
10.Explainable machine learning model for predicting septic shock in critically sepsis patients based on coagulation indexes: A multicenter cohort study.
Qing-Bo ZENG ; En-Lan PENG ; Ye ZHOU ; Qing-Wei LIN ; Lin-Cui ZHONG ; Long-Ping HE ; Nian-Qing ZHANG ; Jing-Chun SONG
Chinese Journal of Traumatology 2025;28(6):404-411
PURPOSE:
Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis.
METHODS:
It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm.
RESULTS:
Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis.
CONCLUSION
The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans
;
Shock, Septic/blood*
;
Machine Learning
;
Male
;
Female
;
Retrospective Studies
;
Middle Aged
;
Aged
;
Sepsis/complications*
;
ROC Curve
;
Cohort Studies
;
Adult
;
Intensive Care Units
;
Algorithms
;
Blood Coagulation
;
Critical Illness

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