1.Epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome in Zhejiang Province
LÜ ; Jing ; XU Xinying ; QIAO Yingyi ; SHI Xinglong ; YUE Fang ; LIU Ying ; CHENG Chuanlong ; ZHANG Yuqi ; SUN Jimin ; LI Xiujun
Journal of Preventive Medicine 2026;38(1):10-14
Objective:
To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control.
Methods:
Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence.
Results:
A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk.
Conclusions
SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.
2.Urban-rural difference in adverse outcomes of pulmonary tuberculosis in patients with pulmonary tuberculosis-diabetes mellitus comorbidity
FANG Zijian ; LI Qingchun ; XIE Li ; SONG Xu ; DAI Ruoqi ; WU Yifei ; JIA Qingjun ; CHENG Qinglin
Journal of Preventive Medicine 2025;37(1):7-11
Objective:
To investigate the urban and rural differences in adverse outcomes of pulmonary tuberculosis (PTB) in patients with pulmonary tuberculosis-diabetes mellitus comorbidity (PTB-DM), so as to provide insights into improving the prevention and treatment measures for PTB-DM.
Methods:
Patients with PTB-DM who were admitted and discharged from 14 designated tuberculosis hospitals in Hangzhou City from 2018 to 2022 were selected. Basic information, and history of diagnosis and treatment were collected through hospital information systems. The adverse outcomes of PTB were defined as endpoints, and the proportions of adverse outcomes of PTB in urban and rural patients with PTB-DM were analyzed. Factors affecting the adverse outcomes of PTB were identified using a multivariable Cox proportional hazards regression model.
Results:
A total of 823 patients with PTB-DM were enrolled, including 354 (43.01%) urban and 469 (56.99%) rural patients. There were 112 (13.61%) patients with adverse outcomes of PTB. The proportions of adverse outcomes of PTB in urban and rural patients were 14.41% and 13.01%, respectively, with no statistically significant difference (P>0.05). Multivariable Cox proportional hazards regression analysis identified first diagnosed in county-level hospitals or above (HR=2.107, 95%CI: 1.181-3.758) and drug resistance (HR=3.303, 95%CI: 1.653-6.600) as the risk factors for adverse outcomes of PTB in urban patients with PTB-DM, while the treatment/observed management throughout the process (HR=0.470, 95%CI: 0.274-0.803) and fixed-dose combinations throughout the process (HR=0.331, 95%CI: 0.151-0.729) as the protective factors for adverse outcomes in rural patients with PTB-DM.
Conclusions
There are differences in influencing factors for adverse outcomes of PTB in urban and rural patients with PTB-DM. The adverse outcomes of PTB are associated with first diagnosed hospitals and drug resistance in urban patients, and are associated with the treatment/observed management and fixed-dose combinations throughout the process in rural patients.
3.Identification of novel pathogenic variants in genes related to pancreatic β cell function: A multi-center study in Chinese with young-onset diabetes.
Fan YU ; Yinfang TU ; Yanfang ZHANG ; Tianwei GU ; Haoyong YU ; Xiangyu MENG ; Si CHEN ; Fengjing LIU ; Ke HUANG ; Tianhao BA ; Siqian GONG ; Danfeng PENG ; Dandan YAN ; Xiangnan FANG ; Tongyu WANG ; Yang HUA ; Xianghui CHEN ; Hongli CHEN ; Jie XU ; Rong ZHANG ; Linong JI ; Yan BI ; Xueyao HAN ; Hong ZHANG ; Cheng HU
Chinese Medical Journal 2025;138(9):1129-1131
4.Correlation between pathological features at the positive margin and biochemical recurrence after radical prostatectomy in patients with organ-confined prostate cancer.
Xin-Huan FAN ; Yan ZHANG ; Lin-Lin ZHU ; Cheng-Yi LIU ; De-Gang CHEN ; Shi-Fang SANG ; Peng-Cheng XU
National Journal of Andrology 2025;31(3):202-207
Objective: To investigate the correlation between pathological features at the positive margins and biochemical recurrence after radical prostatectomy for prostate cancer. Methods: From June 2014 to December 2019, a total of 200 patients with organ-confined prostate cancer who underwent radical prostatectomy were included in this study by the method of case matching (1∶1). One hundred patients with positive surgical margin and 100 with negative surgical margin were enrolled in this study. All patients did not receive any adjuvant treatment after surgery with a clinical stage of T2/N0. BCR-free survival was estimated using the Kaplan-Meier method. An optimal cutoff for the PSM length which differentiated risk for BCR was identified by Classification and Regression Tree analysis (CART). Cox proportional hazards regression model was used to assess the association between variables and BCR-free survival. Results: A total of 200 patients were included in this study, and 177 patients with pT2 stage were pathological after operation. The median follow-up time of this group of patients was 32.8 months ranged from 5.6 to 80.5 months. A total of 28 cases of biochemical recurrence were found through PSA follow-up after surgery, including 6 cases (6.0%) in the negative margin group and 22 cases (22.0%) in the positive margin group. The result of Kaplan Meier survival curve analysis showed that the non biochemical recurrence survival time of the negative margin group was longer than that of the positive margin group (log rank χ2=9.336, P=0.003). It was found that the length of positive margin ≥1 mm in the positive margin group was positively correlated with postoperative biochemical recurrence. Multivariate Cox proportional hazards regression was used to identify that the highest Gleason score ≥8 and the length of positive ≥1 mm were independent factors of postoperative biochemical recurrence in both the overall patients and the patients with positive margin. Conclusion: The patients with highest Gleason score ≥8 and the length of positive ≥1mm are at elevated risk for BCR.
Humans
;
Male
;
Prostatectomy
;
Prostatic Neoplasms/pathology*
;
Neoplasm Recurrence, Local
;
Margins of Excision
;
Prostate-Specific Antigen/blood*
;
Proportional Hazards Models
;
Middle Aged
;
Aged
;
Neoplasm Staging
;
Kaplan-Meier Estimate
5.Influencing factors of positive surgical margins after radical resection of prostate cancer.
Chang-Jie SHI ; Zhi-Jian REN ; Ying ZHANG ; Ding WU ; Bo FANG ; Xiu-Quan SHI ; Wen CHENG ; Dian FU ; Xiao-Feng XU
National Journal of Andrology 2025;31(4):328-332
OBJECTIVE:
To investigate the influencing factors of pathological positive surgical margins (PSM) after radical resection of prostate cancer.
METHODS:
The clinical data of 407 patients who underwent radical resection of prostate cancer in our hospital from 2011 to 2020 were retrospectively analyzed. And the patients were divided into two groups according to postoperative pathological results. Single factor analysis was used to evaluate the differences in postoperative Gleason score, preoperative total prostate-specific antigen (tPSA), preoperative serum free prostate-specific antigen to preoperative tPSA ratio (fPSA/ tPSA), clinical stage, postoperative pathological stage, operation method, age, body mass index (BMI), diameter and volume of prostate tumor. Multivariate logistic regression was used to determine the independent risk factor of PSM.
RESULTS:
Among 407 patients with prostate cancer, 179 cases (43.98%) were positive. Univariate analysis showed that there were significant differences in postoperative Gleason score, preoperative tPSA, clinical stage and postoperative pathological stage between the two groups (P<0.05). And Gleason score, preoperative tPSA and pathologic stage were independent risk factors for PSM.
CONCLUSION
There are relationships between PSM and postoperative Gleason score, tPSA, clinical T stage, postoperative pathologic pT stage. Among them, postoperative Gleason score (Gleason=7 points, Gleason≥8 points), preoperative total prostate-specific antigen (tPSA > 20 μg/L), and postoperative pathologic pT stage (pT3a, pT3b) were independent risk factors for positive pathological margins of prostate cancer.
Margins of Excision
;
Prostatic Neoplasms/surgery*
;
Prostatectomy/statistics & numerical data*
;
Prostate/surgery*
;
Retrospective Studies
;
Neoplasm Grading/statistics & numerical data*
;
Prostate-Specific Antigen/blood*
;
Neoplasm Staging/statistics & numerical data*
;
Postoperative Period
;
Risk Factors
;
Humans
;
Male
6.Advancements in molecular imaging probes for precision diagnosis and treatment of prostate cancer.
Jiajie FANG ; Ahmad ALHASKAWI ; Yanzhao DONG ; Cheng CHENG ; Zhijie XU ; Junjie TIAN ; Sahar Ahmed ABDALBARY ; Hui LU
Journal of Zhejiang University. Science. B 2025;26(2):124-144
Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans
;
Male
;
Prostatic Neoplasms/diagnosis*
;
Molecular Probes
;
Molecular Imaging/methods*
;
Magnetic Resonance Imaging
;
Positron-Emission Tomography
;
Tomography, Emission-Computed, Single-Photon
;
Ultrasonography
;
Optical Imaging
;
Biomarkers, Tumor
;
Precision Medicine/methods*
7.IsoVISoR: Towards 3D Mesoscale Brain Mapping of Large Mammals at Isotropic Sub-micron Resolution.
Chao-Yu YANG ; Yan SHEN ; Xiaoyang QI ; Lufeng DING ; Yanyang XIAO ; Qingyuan ZHU ; Hao WANG ; Cheng XU ; Pak-Ming LAU ; Pengcheng ZHOU ; Fang XU ; Guo-Qiang BI
Neuroscience Bulletin 2025;41(2):344-348
8.Expert consensus on peri-implant keratinized mucosa augmentation at second-stage surgery.
Shiwen ZHANG ; Rui SHENG ; Zhen FAN ; Fang WANG ; Ping DI ; Junyu SHI ; Duohong ZOU ; Dehua LI ; Yufeng ZHANG ; Zhuofan CHEN ; Guoli YANG ; Wei GENG ; Lin WANG ; Jian ZHANG ; Yuanding HUANG ; Baohong ZHAO ; Chunbo TANG ; Dong WU ; Shulan XU ; Cheng YANG ; Yongbin MOU ; Jiacai HE ; Xingmei YANG ; Zhen TAN ; Xiaoxiao CAI ; Jiang CHEN ; Hongchang LAI ; Zuolin WANG ; Quan YUAN
International Journal of Oral Science 2025;17(1):51-51
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
9.Association of Body Mass Index with All-Cause Mortality and Cause-Specific Mortality in Rural China: 10-Year Follow-up of a Population-Based Multicenter Prospective Study.
Juan Juan HUANG ; Yuan Zhi DI ; Ling Yu SHEN ; Jian Guo LIANG ; Jiang DU ; Xue Fang CAO ; Wei Tao DUAN ; Ai Wei HE ; Jun LIANG ; Li Mei ZHU ; Zi Sen LIU ; Fang LIU ; Shu Min YANG ; Zu Hui XU ; Cheng CHEN ; Bin ZHANG ; Jiao Xia YAN ; Yan Chun LIANG ; Rong LIU ; Tao ZHU ; Hong Zhi LI ; Fei SHEN ; Bo Xuan FENG ; Yi Jun HE ; Zi Han LI ; Ya Qi ZHAO ; Tong Lei GUO ; Li Qiong BAI ; Wei LU ; Qi JIN ; Lei GAO ; He Nan XIN
Biomedical and Environmental Sciences 2025;38(10):1179-1193
OBJECTIVE:
This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study.
METHODS:
A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants.
RESULTS:
Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m 2) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m 2) and obesity (≥ 28.0 kg/m 2) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m 2 ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses.
CONCLUSION
This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans
;
Body Mass Index
;
China/epidemiology*
;
Male
;
Female
;
Middle Aged
;
Prospective Studies
;
Rural Population/statistics & numerical data*
;
Aged
;
Follow-Up Studies
;
Adult
;
Mortality
;
Cause of Death
;
Obesity/mortality*
;
Overweight/mortality*
10.REDH: A database of RNA editome in hematopoietic differentiation and malignancy
Jiayue XU ; Jiahuan HE ; Jiabin YANG ; Fengjiao WANG ; Yue HUO ; Yuehong GUO ; Yanmin SI ; Yufeng GAO ; Fang WANG ; Hui CHENG ; Tao CHENG ; Jia YU ; Xiaoshuang WANG ; Yanni MA
Chinese Medical Journal 2024;137(3):283-293
Background::The conversion of adenosine (A) to inosine (I) through deamination is the prevailing form of RNA editing, impacting numerous nuclear and cytoplasmic transcripts across various eukaryotic species. Millions of high-confidence RNA editing sites have been identified and integrated into various RNA databases, providing a convenient platform for the rapid identification of key drivers of cancer and potential therapeutic targets. However, the available database for integration of RNA editing in hematopoietic cells and hematopoietic malignancies is still lacking.Methods::We downloaded RNA sequencing (RNA-seq) data of 29 leukemia patients and 19 healthy donors from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database, and RNA-seq data of 12 mouse hematopoietic cell populations obtained from our previous research were also used. We performed sequence alignment, identified RNA editing sites, and obtained characteristic editing sites related to normal hematopoietic development and abnormal editing sites associated with hematologic diseases.Results::We established a new database, "REDH", represents RNA editome in hematopoietic differentiation and malignancy. REDH is a curated database of associations between RNA editome and hematopoiesis. REDH integrates 30,796 editing sites from 12 murine adult hematopoietic cell populations and systematically characterizes more than 400,000 edited events in malignant hematopoietic samples from 48 cohorts (human). Through the Differentiation, Disease, Enrichment, and knowledge modules, each A-to-I editing site is systematically integrated, including its distribution throughout the genome, its clinical information (human sample), and functional editing sites under physiological and pathological conditions. Furthermore, REDH compares the similarities and differences of editing sites between different hematologic malignancies and healthy control.Conclusions::REDH is accessible at http://www.redhdatabase.com/. This user-friendly database would aid in understanding the mechanisms of RNA editing in hematopoietic differentiation and malignancies. It provides a set of data related to the maintenance of hematopoietic homeostasis and identifying potential therapeutic targets in malignancies.


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