1.Epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome in Huai'an City from 2011 to 2024
XIA Wenling ; GAO Qiang ; LI Yang ; CAI Ben ; WAN Chunyu ; CUI Zhizhen ; ZHANG Zheng ; PAN Enchun
Journal of Preventive Medicine 2026;38(1):55-59,65
Objective:
To investigate the epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome (SFTS) in Huai'an City, Jiangsu Province from 2011 to 2024, so as to provide a basis for optimizing local SFTS prevention and control strategies, and identifying high-risk areas and key populations.
Methods:
Data on SFTS incidence and deaths in Huai'an City from 2011 to 2024 were collected from the Infectious Disease Reporting Information System of the Chinese Disease Prevention and Control Information System. The reported incidence, mortality, and fatality rates were calculated. Descriptive analysis was performed on temporal, population, and regional distribution. The average annual percent change (AAPC) was used to analyze the trend in the reported incidence of SFTS. Global and local spatial autocorrelation analyses were employed to examine the spatial distribution patterns and spatial association patterns of SFTS incidence while spatio-temporal scanning analyses was used to assess the spatial-temporal clustering of SFTS.
Results:
A total of 337 SFTS cases were reported in Huai'an City from 2011 to 2024, with the reported incidence rising from 0.17/100 000 to 1.88/100 000. There were 20 deaths, with an average annual mortality of 0.03/100 000, and a fatality rate of 5.93%. The incidence showed obvious seasonality, with a peak in May and June (148 cases, accounting for 43.92%). Spring and summer accounted for 107 cases (31.75%) and 159 cases (47.18%), respectively. The reported SFTS cases were mainly male, farmers, and individuals aged ≥41 years, accounting for 56.38%, 79.23%, and 96.74%, respectively. The population distribution of death cases was basically consistent with that of incident cases. Xuyi County was a high-incidence area, with a total of 332 reported cases, accounting for 98.52%. All death cases were reported in this county. Spatial autocorrelation analyses revealed a positive spatial correlation in SFTS incidence from 2019 to 2024, with Moran's I values ranging from 0.214 to 0.336 (all P<0.05). Heqiao Town, Tianquanhu Town, and Guiwu Town in Xuyi County were identified as high-high clustering areas. Spatio-temporal scanning analyses showed that cluster 1 was consistent with the high-high clustering areas, with an aggregation time from the second quarter of 2019 to the second quarter of 2022.
Conclusions
From 2011 to 2024, the reported incidence of SFTS in Huai'an City showed an upward trend, with a high incidence in spring and summer. Males, farmers, and the middle-aged and elderly population were the key populations for prevention and control. Xuyi County was the key area for prevention and control.
2.Investigating Effect of Xianglian Huazhuo Prescription on Cell Cycle and Proliferation in Rats with Chronic Atrophic Gastritis Through TGF-β1/Smads Signaling Pathway
Yican WANG ; Jie WANG ; Yirui CHENG ; Xiaojing LI ; Yibin MA ; Qiuhua LIU ; Ziwei LIU ; Yuxi GUO ; Pengli DU ; Yanru CAI ; Yao DU ; Zheng ZHI ; Bolin LI ; Qian YANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):128-136
ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription (XLHZ) in treating chronic atrophic gastritis (CAG) by regulating cell cycle and inhibiting proliferation, using bioinformatics technology and animal experiments. MethodsDifferential expressed genes (DEGs) related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis (WGCNA) was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction (PPI) analysis of genes was conducted using the Protein Interaction Platform (STRING) database to search the super hub gene (hub 2.0), and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group, and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine (MNNG) + sodium salicylate". The successfully modeled rats were randomly divided into the model group, XLHZ-H, XLHZ-M, and XLHZ-L groups (36, 18, 9 g·kg-1, respectively), and Morodan group (1.4 g·kg-1). Each group was given corresponding intervention for 60 days. Hematoxylin-eosin (HE) staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β1, Smad2 and Smad3 proteins, S/G2/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue, and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified, including TGF-β1, suggesting the involvement of the TGF-β1 signaling pathway in the CAG pathogenesis. Compared with the normal group, the expressions of TGF-β1, Smad2, geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased (P<0.05), and the expression of Smad3 protein was decreased (P<0.05). Compared with the model group, the expressions of TGF-β1 and geminin in the gastric mucosa were decreased in the drug groups (P<0.05). The XLHZ-M group, XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 (P<0.05). The protein expression of Smad3 was significantly increased in XLHZ-M, XLHZ-H, and Morodan groups (P<0.05). Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators, and positively correlated with other indicators (P<0.01). ConclusionXLHZ may inhibit TGF-β1/Smads signaling pathway, regulate cell cycle, and inhibit proliferation in the treatment of CAG.
3.Investigating Effect of Xianglian Huazhuo Prescription on Cell Cycle and Proliferation in Rats with Chronic Atrophic Gastritis Through TGF-β1/Smads Signaling Pathway
Yican WANG ; Jie WANG ; Yirui CHENG ; Xiaojing LI ; Yibin MA ; Qiuhua LIU ; Ziwei LIU ; Yuxi GUO ; Pengli DU ; Yanru CAI ; Yao DU ; Zheng ZHI ; Bolin LI ; Qian YANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):128-136
ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription (XLHZ) in treating chronic atrophic gastritis (CAG) by regulating cell cycle and inhibiting proliferation, using bioinformatics technology and animal experiments. MethodsDifferential expressed genes (DEGs) related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis (WGCNA) was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction (PPI) analysis of genes was conducted using the Protein Interaction Platform (STRING) database to search the super hub gene (hub 2.0), and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group, and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine (MNNG) + sodium salicylate". The successfully modeled rats were randomly divided into the model group, XLHZ-H, XLHZ-M, and XLHZ-L groups (36, 18, 9 g·kg-1, respectively), and Morodan group (1.4 g·kg-1). Each group was given corresponding intervention for 60 days. Hematoxylin-eosin (HE) staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β1, Smad2 and Smad3 proteins, S/G2/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue, and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified, including TGF-β1, suggesting the involvement of the TGF-β1 signaling pathway in the CAG pathogenesis. Compared with the normal group, the expressions of TGF-β1, Smad2, geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased (P<0.05), and the expression of Smad3 protein was decreased (P<0.05). Compared with the model group, the expressions of TGF-β1 and geminin in the gastric mucosa were decreased in the drug groups (P<0.05). The XLHZ-M group, XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 (P<0.05). The protein expression of Smad3 was significantly increased in XLHZ-M, XLHZ-H, and Morodan groups (P<0.05). Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators, and positively correlated with other indicators (P<0.01). ConclusionXLHZ may inhibit TGF-β1/Smads signaling pathway, regulate cell cycle, and inhibit proliferation in the treatment of CAG.
4.Analysis of Risk Factors and Establishment of Prediction Model for Turbidity Toxicity Accumulation Syndrome in Patients with Chronic Atrophic Gastritis
Yican WANG ; Chenggong ZHAO ; Pengli DU ; Jie WANG ; Yuxi GUO ; Haiyan BAI ; Yongli HUO ; Xiaomeng LANG ; Zheng ZHI ; Bolin LI ; Jianping LIU ; Yanru CAI ; Jianming JIANG ; Qian YANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(10):288-295
ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis (CAG) with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching, patients were divided into a training set (namely dev) and a validation set (namely vad) in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator (namely Lasso) regression algorithms. Subsequently, a model, named model 1se, was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods, including the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test (H-L), calibration plot, and decision curve analysis (DCA). ResultsAge, body mass index (BMI), family history of cancer, job and life satisfaction, yellow and greasy fur with slippery pulse, and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration, which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.
5.Analysis of Risk Factors and Establishment of Prediction Model for Turbidity Toxicity Accumulation Syndrome in Patients with Chronic Atrophic Gastritis
Yican WANG ; Chenggong ZHAO ; Pengli DU ; Jie WANG ; Yuxi GUO ; Haiyan BAI ; Yongli HUO ; Xiaomeng LANG ; Zheng ZHI ; Bolin LI ; Jianping LIU ; Yanru CAI ; Jianming JIANG ; Qian YANG
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(10):288-295
ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis (CAG) with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching, patients were divided into a training set (namely dev) and a validation set (namely vad) in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator (namely Lasso) regression algorithms. Subsequently, a model, named model 1se, was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods, including the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test (H-L), calibration plot, and decision curve analysis (DCA). ResultsAge, body mass index (BMI), family history of cancer, job and life satisfaction, yellow and greasy fur with slippery pulse, and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration, which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.
6.A Comparative Study of Artificial Intelligence-based Classification Versus Manual Classification of Medical Adverse Events: Taking the DeepSeek Large Language Model As an Example
Rui WANG ; Xutong TAN ; Congpu ZHAO ; Shuchang WANG ; Zheng CHEN ; Xiaojun MA ; Zhiling CAI
Medical Journal of Peking Union Medical College Hospital 2026;17(3):828-833
To analyze the application value of artificial intelligence (AI)-based classification in the categorization of medical adverse events. Medical adverse events reported to the Adverse Event Reporting System of Peking Union Medical College Hospital from September 1, 2023, to August 31, 2024, were retrospectively collected as the study subjects. After de-identification of adverse events meeting the inclusion criteria, conventional manual classification and AI-based classification using a large language model (DeepSeek-R1 Full-Context Internet Edition) were performed. The time required for classification using both methods was recorded, and the consistency and discrepancies between the two methods were compared. Using manual classification as the gold standard, the accuracy of AI-based classification was comprehensively evaluated. A total of 273 medical adverse events were analyzed. Manual classification took 38 838 seconds in total, with an average of 14.22 seconds per event. AI-based classification took 600 seconds in total, with an average of 2.19 seconds per event. The two methods showed consistent classification in 202 events and inconsistent classification in 71 events, yielding an overall agreement rate of 73.99% and a Kappa coefficient of 0.646 (95% CI: 0.575-0.717), with a standard error of 0.0362. Using manual classification as the gold standard, AI-based classification achieved accuracy ranging from 80% to 100%, precision from 30% to 100%, recall from 40% to 100%, F1 scores from 0.46 to 0.79, and specificity from 46% to 98%. Notably, AI-based classification demonstrated balanced and overall excellent performance in the categorization of device-related and drug-related adverse events. The DeepSeek large language model can assist in improving the efficiency of medical adverse event classification, showing promising application potential, particularly in the categorization of device-related and drug-related adverse events.
7.Association of blood selenium exposure with sex hormones among men aged 18-79 years in China
Zheng LI ; Yingli QU ; Yawei LI ; Saisai JI ; Haocan SONG ; Qi SUN ; Miao ZHANG ; Wenli ZHANG ; Jiayi CAI ; Liang DING ; Ying ZHU ; Feng ZHAO ; Zhaojin CAO ; Yuebin LYU ; Lu WANG ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(10):1632-1639
Objective:To investigate the association between blood selenium levels and sex hormones in Chinese men aged 18-79 years.Methods:Data were derived from the China National Human Biomonitoring survey conducted in 2017-2018, with a final sample size of 5 414 men. General demographic characteristics, behavioral habits, and dietary frequency were collected through questionnaires and physical examinations. Fasting blood samples were collected to measure blood lead, serum testosterone, and estradiol levels. Complex sampling linear regression models were used to analyze the associations between blood selenium levels and testosterone, estradiol, and the testosterone/estradiol ratio, adjusting for confounding factors including age, education level, marital status, smoking status, alcohol consumption, seafood intake, soy product intake, protein supplement intake, BMI, and diabetes status.Results:The mean age of the 5 414 participants was (46.85±27.91) years; 4 774 (91.65%) were of Han ethnicity and 4 505 (86.68%) were married. The median ( Q1, Q3) blood selenium concentration in men was 97.80 (80.64, 116.99) μg/L. After adjusting for confounding factors, the complex sampling linear regression model revealed negative associations between blood selenium levels and both testosterone levels and the testosterone/estradiol ratio, with a significant linear trend ( Ptrend<0.05). Compared with the Q1 group, the β (95% CI) values for testosterone in the Q2, Q3, and Q4 groups were -0.02 (-0.06 to 0.02), -0.03 (-0.08 to 0.01), and -0.06 (-0.09 to -0.02), respectively. Similarly, the β (95% CI) values for the testosterone/estradiol ratio in the Q2, Q3, and Q4 groups were -0.01 (-0.03 to 0.02), -0.01 (-0.04 to 0.04), and -0.03 (-0.06 to -0.01), respectively. Subgroup analysis indicated stronger associations between blood selenium levels and testosterone/estradiol levels in non-smoking and obese men (BMI≥28 kg/m2). Conclusion:Blood selenium levels are negatively associated with testosterone levels and the testosterone/estradiol ratio in Chinese adult males.
8.Association of cadmium internal exposure levels with blood lipid in adults aged 18 to 79 years in China
Haocan SONG ; Saisai JI ; Zheng LI ; Yawei LI ; Feng ZHAO ; Yingli QU ; Yifu LU ; Yingying HAN ; Junxin LIU ; Jiayi CAI ; Tian QIU ; Wenli ZHANG ; Xiao LIN ; Junfang CAI ; Yuebin LYU ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(8):1254-1263
Objective:To explore the association of blood and urinary cadmium levels with lipid profile levels and dyslipidemia in Chinese adults aged 18 to 79 years.Methods:Based on the China National Human Biomonitoring (CNHBM) program, a cross-sectional survey was conducted from 2017 to 2018 using a multi-stage stratified random sampling method, including a total of 10 713 adults aged 18 to 79 years. Data was obtained through questionnaires, physical examinations, biological sample collection, and laboratory testing. Multiple linear mixed effect model (MLMM) and generalized linear mixed effect model (GLMM) were used to analyze the association of blood and creatinine-corrected urinary cadmium levels with lipid profile levels as well as dyslipidemia among adults.Results:The age of 10 713 participants was (47.23±0.24) years, with 5 372 males accounting for 61.3% of the national population. The weighted mean±standard error (SE) of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was (5.21±0.03), (1.86±0.03), (2.96±0.03), and (1.43±0.01) mmol/L, respectively. The prevalence rate of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, low HDL-C, and high LDL-C was 16.0%, 21.6%, 6.6%, 13.5%, and 10.0%, respectively. MLMM showed that, after adjusting for relevant confounders, log-transformed blood cadmium levels were positively associated with increased levels of TC, TG and LDL-C ( P<0.05). When blood cadmium levels were categorized into quartiles, compared to the lowest exposure group ( Q1), participants in the highest blood cadmium exposure group ( Q4) had increases of 0.19 (95% CI: 0.06, 0.32) mmol/L in TC and 0.25 (95% CI: 0.08, 0.43) mmol/L in TG. GLMM indicated that, after adjusting for confounders, higher blood cadmium exposure levels were associated with increased risks of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, and high LDL-C ( P<0.05). Further analysis by quartiles showed that, compared to the blood cadmium Q1 exposure group, the OR value (95% CI) for the Q4 group was 1.53 (1.12, 2.08) for hypercholesterolemia, 1.54 (1.09, 2.17) for hypertriglyceridemia, 2.24 (1.47, 3.40) for mixed hyperlipidemia, and 1.49 (1.07, 2.09) for high LDL-C. Conclusion:The cadmium internal exposure levels are associated with blood lipid profile levels as well as the incidence of dyslipidemia in Chinese adults aged 18 to 79.
9.Establishment of near-infrared spectroscopy quantitative models for moisture and index components in Alismatis Rhizoma decoction pieces
Xun LU ; Zhe ZHANG ; Geng-zhi ZHAN ; Lu-yao CAI ; Cun-yu LI ; Yun-feng ZHENG ; Tuan-jie WANG ; Yu JIN ; Guo-ping PENG
Chinese Traditional Patent Medicine 2025;47(10):3184-3190
AIM To establish the near-infrared spectroscopy quantitative models for moisture,23-acetylalismol B and 23-acetylalismol C in Alismatis Rhizoma decoction pieces.METHODS The near-infrared spectroscopy(NIRS)data were collected in 95 batches of decoction pieces,after which drying method was adopted in the content determination of moisture,HPLC was applied to determining the contents of 23-acetylalismol B and 23-acetylalismol C,the quantitative models were established by partial least squares method combined with feature extraction algorithms.RESULTS The model training determination coefficients were 0.952 6,0.958 1 and 0.920 8,along with the prediction determination coefficients of 0.930 0,0.905 2 and 0.906 4,the residual prediction deviations(PRD)of 4.00,3.58 and 3.46,and the root mean square error ratios of prediction values to calibration values(RMSEP/RMSEC)of 1.15,1.11 and 1.06,respectively.CONCLUSION The quantitative models based on NIRS exhibit good prediction effects,which can be used for the rapid quality detection of Alismatis Rhizoma decoction pieces.
10.Analysis of Dabie bandavirus infection and genetic characteristics in a city of Hebei Province
Luling LI ; Yamei WEI ; Minghao GENG ; Yan ZHENG ; Yanan CAI ; Xu HAN ; Zhenkun WANG ; Zhengguang WANG ; Qi LI
Chinese Journal of Zoonoses 2025;41(8):801-808
This study was aimed at investigating the prevalence of Dabie bandavirus(DBV)infection in suspected cases of se-vere fever with thrombocytopenia syndrome(SFTS)and tick specimens in Cangzhou City from 2023 to 2024,and providing scientific basis for the prevention,control and pathogen surveillance of SFTS in this area.Pathogen detection and virus isolation were performed on suspected SFTS cases and tick specimens collected in Cangzhou City from 2023 to 2024.The next-generation sequencing technol-ogy was used to conduct whole-genome sequencing of DBV.A phylogenetic tree was constructed using software such as MEGA,DNA Star,and homology comparison and amino acid variation site analysis were carried out.Among the 70 suspected SFTS cases,the DBV positive detection rate was 60%(42/70).The positive cases were mainly farmers aged 50-79,concentrated in Yanshan County and Haixing County.402 ticks were pooled into 31 sample tubes,among which 2 tubes tested positive for DBV nucleic acid,with a mini-mum infection rate of 0.50%.A total of 9 human-derived and 2 tick-derived DBV strains were isolated.The whole-genome sequencing results showed that all strains clustered within the F branch,with sequences homology exceeding 99%.There were a total of 10 amino acid variation sites in the RdRP,GP and NSs sequences.Therefore,the distribution of SFTS cases in Cangzhou City exhibited regional clustering.The overall level of DBV infection in ticks in this region was relatively low.It is recommended to further improve the disease early warning mechanism and continue to conduct pathogen surveillance.


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