1.Management of an imported family cluster of dengue fever cases in Shanghai, 2024
Lei SHEN ; Dongsheng REN ; Mingyi CAI ; Zhixiang TENG ; Qi SHEN ; Qingyuan XU ; Xiaofen NI
Shanghai Journal of Preventive Medicine 2026;38(2):170-174
ObjectiveTo investigate and manage an imported dengue fever (DF) outbreak in Shanghai in 2024, to summarize the experience and lessons learned from the on-site management, and to provide a reference basis for future prevention and control of DF. MethodsEpidemiological investigation and case search were carried out for an imported DF outbreak in Shanghai, 2024. Real-time fluorescence polymerase chain reaction (RT-PCR) was used to detect dengue virus nucleic acid in the serum samples from cases. Meanwhile, emergency vector surveillance and mosquito control measures were carried out in the affected areas, and the effectiveness of the management was evaluated. ResultsAccording to the epidemiological investigation, it was confirmed that this epidemic was a family cluster of imported DF, with both cases infected in Thailand and developed symptoms successively after returning to Shanghai. Laboratory testing identified the pathogens as dengue virus serotype-3 (DENV-3). In the core and precautionary area, ultra-low-volume space spraying and residual spraying were combined to kill adult mosquitoes, and at the same time, comprehensive cleaning and elimination of mosquito breeding sites was carried out. After 2 weeks, the Breteau Index (BI) in the core area decreased from 20 to 5, and the mosquito net trap index decreased from 2 mosquitoes (net·hour)-1 to 0.67 mosquitoes (net·hour)-1. Continuous implementation of mosquito control measures kept the BI and net trap index below the safety thresholds [BI<5 and mosquito net trap index <2 mosquitoes (net·hour)-1] both in the core and precautionary area. ConclusionEarly diagnosis and isolation of patients, combined with rapid suppression of the density of vector Aedes mosquitoes, are the key measures to prevent the transmission of imported DF cases.
2.Analysis of clinical factors related to complete response after neoadjuvant chemoradiotherapy for locally advanced rectal cancer
Hui YANG ; Xiaofeng MU ; Linan SONG ; Wenjie NI ; Lei DING
Chinese Journal of Radiological Health 2026;35(1):6-11
Objective To explore the clinical factors influencing complete response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Methods Clinical data of LARC patients treated in the Department of Radiation Oncology at Beijing Shijitan Hospital between January 2013 and December 2024 were retrospectively collected. All patients received nCRT, after which surgery or a watch-and-wait approach was adopted based on treatment response. Univariable and multivariable logistic regression analyses were performed to identify prognostic factors influencing complete response. A clinical prediction model was constructed based on the multivariable analysis results, and its predictive performance was evaluated using the receiver operating characteristic curve. Results A total of 113 eligible patients were included. After nCRT, 19 patients (16.8%) achieved complete response, including 3 with clinical complete response and 16 with pathological complete response. Univariable analysis indicated that pretreatment clinical N stage, extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen were associated with complete response after nCRT (P<0.05). Multivariable logistic regression analysis identified pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen as independent influencing factors for complete response (P<0.05). A prediction model incorporating these independent factors yielded an area under the receiver operating characteristic curve of 0.813 (95% confidence interval: 0.713-0.913), with a sensitivity of 89.5% and a specificity of 60.6%, demonstrating good predictive performance. Conclusion Pretreatment extramural venous invasion, carcinoembryonic antigen level, and neoadjuvant treatment regimen are independent factors influencing complete response after nCRT in LARC patients. The prediction model combining these factors may assist in evaluating treatment efficacy following nCRT in LARC patients.
3.Results of summer mosquito surveillance in schools of Jing an District, Shanghai from 2019 to 2025
NI Xiaofen, DENG Haiping, SHEN Lei
Chinese Journal of School Health 2026;47(6):888-892
Objective:
To understand the mosquito infestation status in schools in Jing an District of Shanghai from 2019 to 2025, so as to provide a basis for mosquito control work in schools.
Methods:
Four schools of each school type (colleges and secondary specialized schools, primary and secondary schools, nurseries and kindergartens) were respectively selected from Jing an District as the survey sites by combination of stratified sampling and convenience sampling. Mosquito breeding sites surveys (including small stagnant water and medium and large static water) and adult mosquito monitoring were carried out in schools every August, from 2019 to 2025. The breeding sites surveys were investigated by visual inspection and spoon trapping methods, and the adult mosquito monitoring was investigated by the human baited trapping. Chi square test was used for inter group comparison.
Results:
A total of 970 small stagnant water were surveyed from 2019 to 2025, with the positive rate of 17.01% for mosquito breeding. The highest positive rate was in colleges and secondary specialized schools (25.07%). The top three positive breeding sites for mosquito were unused containers(27.46%), waste tires (16.67%), and bonsai and aquatic plants (16.52%). There were statistically significant differences in the positive rates for mosquito breeding among different years, school types and waterlogging types ( χ 2=122.70, 28.48 , 24.80, all P <0.01). A total of 640 medium and large static water were surveyed, and the positive rate for mosquito breeding was 7.34%. There was a statistically significant difference for the positive rate among different years ( χ 2= 50.23 , P <0.01). The highest positive rate for mosquito breeding was in colleges and secondary specialized schools (9.63%), and there was no statistically significant difference for the positive rate among different school types ( χ 2=4.41, P =0.11). From 2019 to 2025, a total of 390 mosquitoes were captured in the time period from 16:30 to 17:00, all of which were Aedes albopictus; the adult mosquito density in colleges and secondary specialized schools was the highest, being 2.38 mosquitoes/(0.5 h ·person). A total of 210 mosquitoes were captured in the time period from 19:00 to 19:30 during 2019-2025, among which Aedes albopictus accounted for 74.76% and Culex pipiens pallens accounted for 25.24%. The adult mosquito density in colleges and secondary specialized schools was the highest, being 1.15 mosquitoes/(0.5 h ·person). In colleges and secondary specialized schools, the area with the largest number of captured mosquitoes was around the teaching buildings and libraries(44.78%). In primary and secondary schools, as well as nurseries and kindergartens, the area with the largest number of captured mosquitoes was around the school gates and playgrounds( 49.44% , 53.60%), the difference in mosquito distribution in different regions among different types of schools was statistically significant ( χ 2=111.39, P <0.01).
Conclusions
The mosquito density in Jing an District schools is generally higher during summer. It is recommended that the school strengthen the management of mosquito breeding sites and the control of adult mosquitoes before the start of autumn semester, so as to prevent insect infestation of mosquitoes.
4.Prediction model of tacrolimus blood concentration based on population pharmacokinetics information and machine learning
Zhaolin CHEN ; Pengli ZHU ; Weijian NI ; Lei ZHANG ; Liqin TANG
China Pharmacy 2026;37(14):1898-1904
OBJECTIVE To construct a prediction model for tacrolimus trough concentration based on population pharmacokinetics (PPK) information and machine learning, evaluate its predictive performance in clinical therapeutic drug monitoring (TDM) data, and provide evidence-based support for individualized dose adjustment of tacrolimus after renal transplantation. METHODS A retrospective cohort study design was adopted, and consecutive TDM records of kidney transplant recipients treated in the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from January to June 2025 were included to construct the final analysis set. Based on 29 input variables including previous TDM concentration, previous concentration/dose ( C / D ) ratio, and individual predicted exposure (IPRE), 13 commonly used regression algorithm models and 1 weighted ensemble model were systematically compared. The dataset was split into training set and test set in an 80∶20 ratio by patient. Five-fold cross-validation based on patient grouping was performed on the training set, and the model performance was evaluated on the obtained evaluation points using the coefficient of determination ( R 2 ), mean absolute error (MAE), root mean square error (RMSE), Pearson correlation coefficient (Corr) and ±20%/±30% accuracy. The SHapley Additive exPlanations (SHAP) method was used for model interpretability analysis to identify core predictive features. RESULTS A total of 809 consecutive TDM records from 83 kidney transplant recipients were included, with 66 cases in the training set and 17 cases in the test set. The SVR model showed the best performance, with R 2 of 0.649 8, MAE of 1.126 0 ng/mL, RMSE of 1.478 6 ng/mL, Corr of 0.819 1, ±20% accuracy of 59.68%, and ±30% accuracy of 79.03%. The Weighted Ensemble model and Extra Trees model ranked second and third, respectively. SHAP interpretability analysis showed that the top 6 features contributing to the prediction were IPRE, previous TDM concentration, previous C/D ratio, dose-normalized concentration, hematocrit (HCT), and concentration-dose coefficient ( θ cd ), among which IPRE was the core predictive feature (SHAP mean value 0.915 4). CONCLUSIONS The machine learning model incorporating PPK information demonstrates good predictive ability for tacrolimus concentration in the current TDM cohort. SVR is the optimal model, IPRE is the core predictive feature of the model, and a few core PK-derived features (IPRE, dose-normalized concentration, θ cd ) together with clinical features (previous TDM concentration, HCT, etc.) constitute the main information sources for model prediction.
5.Clinical value of quantitative parameters of contrast-enhanced ultrasound in the diagnosis of benign and malignant ovarian tumors
Chinese Journal of Radiological Health 2026;35(3):445-449
Objective To analyze the value of contrast-enhanced ultrasound (CEUS) quantitative parameters in identifying benign and malignant ovarian tumors so as to provide reference for ultrasound diagnosis of ovarian cancer. Methods A total of 116 patients with ovarian tumors admitted to the hospital between February 2021 and February 2024 were enrolled. All patients underwent CEUS examination. Pathological fingdings served as the gold standard to evaluate the diagnostic performance of CEUS quantitative parameters. Results Pathological examination identified 74 benign and 42 malignant ovarian tumors. No significant differences were observed between the two groups in terms of initial enhancement time, enhancement intensity or regression rate (P>0.05). The time to peak was significantly longer in patients with benign tumors than in those with malignant tumors (P<0.05). Whereas peak intensity and enhancement rate were significantly lower in the benign goup (P<0.05). ROC curves analysis showed that when using a single parameter for diagnosis, enhancement rate yielded the largest area under the curve (AUC) of 0.977. Its sensitivity and specificity were 95.24% and 98.65%. The combination of parameters achieved an even larger AUC of 0.998, with a sensitivity of 97.62% and a specificity of 98.65%. Conclusion The combination of CEUS quantitative (time to peak, peak intensity and enhancement rate) demonstrates good diagnostic value for benign and malignant ovarian tumors and improves diagnostic sensitivity.
6.Effects of combined occupational exposure to benzene series, dust and noise on high-frequency hearing loss
Shujun LI ; Feng WANG ; Siqi CHEN ; Ying LUO ; Zhen PAN ; Lei NI ; Yong YAO
Journal of Public Health and Preventive Medicine 2026;37(5):56-59
Objective To investigate the effects of combined exposure to benzene series, dust and noise on occupational high-frequency hearing loss (HFHL) in the electronics manufacturing industry. Methods A total of 740 employees from an electronic manufacturing enterprise were selected as the study subjects. According to the detection of occupational hazard factors, they were divided into noise group, noise benzene group, and noise dust group, with 325, 167, and 248 people, respectively. Occupational health examinations were conducted on the study participants to analyze their HFHL detection status and influencing factors. Results Among all participants (n=740), 456 (61.62%) were male, 284 (38.38%) were female, and 123 (15.62%) were detected with HFHL. The detection rate of HFHL increased with age and length of service (P<0.01). According to the exposure factor grouping, the detection rates of HFHL in the noise group, noise benzene group, and noise dust group were 12.00%, 19.16%, and 20.97%, respectively (P<0.05). Multivariate logistic regression analysis showed that workers aged ≥ 40 years, with 10-20 years of work experience, ≥ 20 years of work experience, exposure to noise and benzene series, and exposure to noise and dust had an increased risk of developing HFHL to 1.734, 1.923, 3.071, 1.706, and 1.527, respectively (P<0.05). Conclusion Combined exposure to noise and benzene series, combined exposure to noise and dust, as well as age and extended length of service may increase the risk of HFHL among workers.
7.Analysis on current status and influencing factors of ethical sensitivity among clinical nursing interns in the context of artificial intelligence
Yue LIN ; Jing WANG ; Kun LI ; Wen WANG ; Lei YANG ; Yang LI ; Mei HUANG ; Chunping NI
Chinese Medical Ethics 2026;39(8):1121-1128
ObjectiveTo investigate the current status of ethical sensitivity among clinical nursing interns in the context of artificial intelligence (AI) and analyze its influencing factors. MethodsAdopting mixed research methods and convenience sampling, a total of 237 nursing interns from a tertiary A hospital in Xi’an were selected as research subjects. Data were collected using a general information questionnaire and the Nursing Students’ Ethical Sensitivity Scale, and semi-structured interviews were conducted with 8 nursing interns. ResultsThe total score of ethical sensitivity among nursing interns was (33.98±6.32), which was at a moderate level. Multiple linear regression analysis revealed that academic degree (undergraduate: β=0.147, P<0.05; postgraduate: β=0.139, P<0.05), affinity for the nursing profession (β=0.118, P<0.05), whether they had taken nursing ethics courses (β=-0.124, P<0.05), and familiarity with artificial intelligence (β=-0.159,P<0.05) were influencing factors of ethical sensitivity among nursing interns. Four themes were extracted from semi-structured interviews, namely, the incomplete mastery of nursing ethics-related knowledge among nursing interns, weakened ethical sensitivity in the AI teaching scenario of nursing interns, insufficient professional identity affecting the development of nursing interns’ ethical sensitivity, and technological dependence leading to the lack of humanistic care among nursing interns. ConclusionEthical sensitivity of nursing interns represents a moderate level, primarily influenced by educational background, degree of fondness for the nursing profession, learning experience of nursing ethics courses, and familiarity with AI. Nursing educators and clinical administrators urgently need to establish a sustainable school-hospital collaborative model of nursing ethics education, attach importance to the cultivation of ethical awareness and value guidance for nursing interns, and strengthen the intensity and depth of nursing ethics education among nursing interns, thereby improving their level of ethical sensitivity in the context of AI.
8.Graphene-based Heterostructure Modified Glassy Carbon Electrode for Sensitive Detection of Catechol
Peng LEI ; Peng-Jia WEI ; Ni WU ; Ming-Lu LI ; Shao-Min SHUANG
Chinese Journal of Analytical Chemistry 2025;53(1):65-73
Catechol(CC)is a highly toxic phenolic pollutant,and its sensitive detection holds significant importance for environmental monitoring.Herein,graphene was used as a template to prepare graphdiyne/graphene(GDY/GR)heterogeneous materials,serving as high-performance electrochemical sensing materials for CC determination.GR played the role of an epitaxial template during the growth of GDY.The electrochemical experiment results demonstrated that the glassy carbon electrode(GCE)modified with GDY/GR showed excellent electrochemical response to CC,with a wide linear detection range(1-900 μmol/L)and a low detection limit(0.11 μmol/L).Meanwhile,GDY/GR/GCE also exhibited good anti-interference ability,stability and reproducibility.More importantly,the practicality of GDY/GR/GCE was evaluated and satisfactory results were obtained in actual water samples,which showed significant potential for practical applications in environmental monitoring.
9.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
10.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.


Result Analysis
Print
Save
E-mail