OBJECTIVE To establish a high-risk medication list and preventive and therapeutic measures for drug-induced hypofibrinogenemia， and to provide a reference for the prevention and treatment of this condition. METHODS By integrating domestic and international case reports， retrospective case-control studies， and spontaneous adverse drug reaction reporting databases， 19 domestically marketed high-risk drugs for drug-induced hypofibrinogenemia were identified. Based on the clinical characteristics and mechanisms of these drugs， relevant risk factors were systematically reviewed， and existing treatment options were summarized， leading to the preliminary development of recommended preventive and therapeutic measures. A two-round Delphi consultation was conducted to evaluate， revise， and ultimately reach consensus on the preliminary findings， using a mean importance score of ≥3.5 points for indicators and a coefficient of variation ＜0.3 as screening criteria. RESULTS The coefficient of expert authority for both rounds of expert consultation was 0.904. In the first round， the Kendall coordination coefficients （Kendall’s W ） for the high-risk medication list and the proposed preventive and therapeutic measures were 0.390 and 0.223 （ P ＜0.05）， respectively. In the second round， the Kendall’s W were 0.227 and 0.200 （ P ＜0.05）， respectively. After two rounds of expert consultation and discussion， 11 high-risk drugs for drug-induced hypofibrinogenemia， represented by hemocoagulase and certain anti-infective agents， were ultimately identified， along with 5 preventive and therapeutic measures spanning the entire process of “pre-medication assessment， intra-medication monitoring， and bleeding event management”. CONCLUSIONS This study has established a scientific and reliable high-risk medication list， and corresponding preventive and therapeutic measures for drug-induced hypofibrinogenemia， providing a theoretical basis and practical support for the early identification， stratified management， and precise intervention of this condition.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

To characterize the genomes of different emm-type group A Streptococcus (GAS), their virulence genes and drug resistance profiles in Tianjin City from 2011 to 2024. After PCR, a total of 42 strains with different years and emm types were selected for whole genome sequencing and multi-locus sequence typing (MLST), and the core genomes were used to generate a phylogenetic tree, after which the virulence genes and resistance genes were identified and analyzed, followed by the drug susceptibility test. In this study, the GAS strains were dominated by emm1 (50.0%) and emm12 (40.4%), and the MLST phenotypes were categorized into six types: ST36 (40.4%), ST1274 (26.1%), ST28 (23.8%), ST921 (4.7%), ST46 (2.3%), and ST403 (2.3%). There was a high consistency between their emm-types and ST types. A total of 68 virulence genes were detected in the genomes of 42 GAS strains, involving functional genes encoding exotoxin, bacterial adhesion, extracellular enzymes, etc. The virulence genes they carried were significantly different between emm1-type and emm12-type strains, such as speA. At the same time, the carrying rates of some virulence genes in the same emm-type strains changed with time, such as hyl. The resistance genes were basically the same among different emm-type strains except for the vanSE gene detected in all emm12 strains. The results of drug sensitivity showed that the GAS strains isolated in Tianjin City from 2011 to 2024 were sensitive to penicillin, cefazolin, chloramphenicol, vancomycin, and levofloxacin, while the resistance rates to erythromycin, azithromycin, clarithromycin, and clindamycin ranged from 88.5% to 100.0%, and there was a certain degree of consistency between the resistance phenotypes and the detected resistance genes. Overall, the main emm types and evolutionary features of GAS in Tianjin City from 2011 to 2024 were consistent with the dominant types in China, and the carrying rate of virulence genes and drug resistance genes differed significantly among different emm-type strains, and there were continuous evolution and variation in the prevalence of virulence genes in GAS.

Objective:To analyze the epidemic characteristics of human brucellosis in Tangshan City, Hebei Province from 2016 to 2024, and to establish a prediction model for forecasting incidence of human brucellosis in Tangshan City from 2025 to 2028, so that to provide evidence for prevention and control strategies.Methods:The incidence data of human brucellosis in Tangshan City from 2016 to 2024 were collected. Brucella strains isolated from blood cultures of patients with acute brucellosis were identified.The onset time and demographic distributions of brucellosis were analyzed using descriptive epidemiological methods. Chi-square test was used for statistical analysis. Python software was used to establish a seasonal autoregressive integrated moving average model (SARIMA model) and predict the incidence of brucellosis in Tangshan City from 2025 to 2028. Results:From 2016 to 2024, a total of 2 446 cases of human brucellosis in Tangshan City were reported, with the highest incidence in 2016 (378 cases) and the lowest in 2022 (277 cases).Seasonal variation was observed, with 54.87%(1 342/2 446) occurring in spring and summer (March to July). The incidence rate of male was 5.28/100 000, which was significantly higher than that of female (1.94/100 000) ( χ2=554.96, P<0.001). The cases spanned all age groups, with the highest incidence among those aged 50 to 59 (30.25%(740/2 446)). Farmers engaged in cattle/sheep breeding accounting for 85.73% (2 097/2 446) of cases. A total of 236 blood samples were collected from patients with acute brucellosis, and 12 Brucella strains were isolated and identified as sheep type Ⅲ Brucella. The optimal model constructed was SARIMA (1, 0, 0) (1, 0, 1) 12, which was used to predict the incidence of human brucellosis in Tangshan City from 2025 to 2028. The results showed that the overall incidence was relatively stable, retaining the characteristic single annual peak. Conclusions:Human brucellosis in Tangshan City peaks in spring/summer and predominantly affects cattle/sheep farmers. The SARIMA (1, 0, 0) (1, 0, 1) 12 model effectively fits the epidemiological data of human brucellosis in Tangshan City well and enables reliable future trend predictions, supporting scientific and effective prevention and control work.

Objective Domestic research institutions and researchers have established a wide variety of animal disease models and accumulated a wealth of specialized, distinctive, and targeted atlas data during the model development process. These atlas data are of great value for development and application. Therefore, it is necessary to develop a professional and complete digital atlas database platform for animal models, which can achieve the open sharing of animal model atlas data and the integration and optimization of atlas resources related to disease animal models held by relevant domestic institutions. Methods Based on the B/S architecture, the authors' institution built a digital atlas database of animal models, using Java as the main development language and Oracle database system along with related auxiliary tools. The database platform ran in a Linux environment and could be accessed by users through a web browser. At present, the data on this platform mainly came from the atlas resources submitted by animal model resource units within Guangdong Province. Results In August 2024, a digital atlas database platform for animal models was constructed based on the classification structure of three dimensions: systemic diseases, animal species, and resource units. This platform provided functions such as collection, management, retrieval, and viewing of atlas data. As of January 2025, four resource units had submitted 61 atlas data entries of animal models to the platform, totalling 610 data items. Conclusion The animal model digital atlas database platform has been constructed and put into preliminary use. Although the amount of data on the platform is still limited, it is capable of integrating and openly sharing animal model atlas data. It is believed that with the continuous enrichment of atlas data in the future, this platform is expected to provide important data support for the development of laboratory animal science and comparative medicine research, thereby promoting the efficient utilization of scientific research resources.

Objective Domestic research institutions and researchers have established a wide variety of animal disease models and accumulated a wealth of specialized, distinctive, and targeted atlas data during the model development process. These atlas data are of great value for development and application. Therefore, it is necessary to develop a professional and complete digital atlas database platform for animal models, which can achieve the open sharing of animal model atlas data and the integration and optimization of atlas resources related to disease animal models held by relevant domestic institutions. Methods Based on the B/S architecture, the authors' institution built a digital atlas database of animal models, using Java as the main development language and Oracle database system along with related auxiliary tools. The database platform ran in a Linux environment and could be accessed by users through a web browser. At present, the data on this platform mainly came from the atlas resources submitted by animal model resource units within Guangdong Province. Results In August 2024, a digital atlas database platform for animal models was constructed based on the classification structure of three dimensions: systemic diseases, animal species, and resource units. This platform provided functions such as collection, management, retrieval, and viewing of atlas data. As of January 2025, four resource units had submitted 61 atlas data entries of animal models to the platform, totalling 610 data items. Conclusion The animal model digital atlas database platform has been constructed and put into preliminary use. Although the amount of data on the platform is still limited, it is capable of integrating and openly sharing animal model atlas data. It is believed that with the continuous enrichment of atlas data in the future, this platform is expected to provide important data support for the development of laboratory animal science and comparative medicine research, thereby promoting the efficient utilization of scientific research resources.

Objective: To investigate the influencing factors of overactive bladder (OAB) in college freshmen and the impacts of OAB on their mental health, quality of life and social interaction. Methods: An epidemiological questionnaire survey was conducted in an anonymous manner on the prevalence of OAB among 5300 freshmen aged 17 to 22 years enrolled in the 2023—2024 academic year in Xinxiang Medical University and Sanquan College of Xinxiang Medical University.The questionnaire included questions on basic information, history of urinary tract infection, constipation, smoking, history of alcohol consumption, history of coffee/strong tea drinking, history of carbonated beverage drinking, redundant prepuce, phimosis, holding urine, chronic insomnia, self-rating anxiety scale (SAS), quality of life score (QoL), and social avoidance and distress scale (SADS).The influencing factors of OAB were analyzed with multivariate logistic regression analysis.The subjects were grouped according to whether they had OAB, and the differences in SAS, QoL and SADS between the OAB group and non-OAB group were compared.The impacts of OAB on the anxiety level, quality of life, and social interaction were analyzed with multiple linear regression analysis. Results: The overall prevalence rate of OAB was 4.9% (244/5018).Multivariate logistic regression analysis showed that the history of urinary tract infection (OR=0.177), constipation (OR=0.636), smoking (OR=0.582), alcohol consumption (OR=0.685), coffee/strong tea drinking (OR=0.387), carbonated beverage drinking (OR=0.631), redundant prepuce (OR=0.673), phimosis (OR=0.311), urine holding (OR=0.593), and chronic insomnia (OR=0.256) were influencing factors for the occurrence of OAB (P＜0.05).The OAB group had higher SAS score [(41.18±6.54) vs. (38.61±6.36)], QoL score [(3.65±1.20) vs. (2.79±0.95)], social avoidance score [(6.25±1.86) vs. (5.86±1.51)], social distress score [(6.27±1.59) vs. (5.97±1.32)], and total SADS score [(12.51±2.35) vs. (11.84±2.01)] than the non-OAB group (P＜0.05).The results of multiple linear regression analysis showed that OAB could independently affect the scores of QoL, SAS, and SADS.The OAB group had higher scores of QoL, SAS, and SADS compared with the non-OAB group (P＜0.001). Conclusion: History of urinary tract infection, constipation, smoking, alcohol consumption, coffee/strong tea drinking, carbonated beverage drinking, redundant prepuce, phimosis, urine holding, and chronic insomnia are influencing factors for the occurrence of OAB in male college students.Moreover, OAB has negative impacts on their mental health, quality of life, and social interaction.

Modified electro-convulsive therapy (MECT) is one of the most potent treatments for major depressive disorder (MDD). However, it remains a second-line option due to significant side effects, such as transient memory loss. The relationship between therapeutic efficacy and cognitive impairment warrants further investigation to develop improved treatment regimens. In this review, we examine recent evidence from magnetic resonance imaging (MRI) studies aiming to identify structural and functional brain changes specifically associated with both the antidepressant effects and the amnesic outcomes of MECT. MECT induces widespread alterations across multiple brain systems. Increases in gray matter volume (GMV) have been observed in the prefrontal, temporal, and parietal cortices, as well as in subcortical regions such as the hippocampus (HP), amygdala, and striatum. Strengthening of myelination has also been reported along the dorsolateral prefrontal-limbic pathways. Functional changes include increased spontaneous neural activity in prefrontal areas, reorganization of intrinsic connectivity within the default mode network (DMN), and altered functional connectivity (FC) among the DMN, salience network (SN), and central executive network (CEN). Correlational studies have identified structural and functional alterations linked to antidepressant efficacy, including right hippocampal volume enlargement, prefrontal cortical thickening, reduced iron deposition in the striatum, decreased FC within certain DMN nodes, and enhanced effective connectivity from the dorsolateral prefrontal cortex (DLPFC) to the right angular gyrus. In contrast, the amnesic effects have been associated with increased volumes in the left hippocampus and bilateral dentate gyrus; enhanced FC in the left angular gyrus and left posterior cingulate cortex (PCC); increased FC between the right ventral anterior insula and DLPFC; and reduced FC in the left thalamus and bilateral precuneus. Changes in the hippocampus appear to correlate with both antidepressant efficacy and memory impairment. Clinical studies have found no significant correlation between the severity of memory impairment and the reduction in depressive symptoms, suggesting that the therapeutic and adverse effects may arise from distinct regional or subregional mechanisms. Supporting this hypothesis, recent findings show that increased right hippocampal volume is significantly associated with reduced depression scores, whereas increased volume in the left dentate gyrus correlates with declines in delayed recall performance. Additionally, enhanced connectivity between the anterior hippocampus and middle occipital gyrus (MOG) has been linked to mood improvement, while decreased FC between the mid-hippocampus and angular gyrus has been associated with impairments in memory integration. In conclusion, current evidence suggests that the antidepressant and memory-impairing effects of MECT may localize to distinct hippocampal subregions. These effects likely result from differential modulation of local neural activity and functional connectivity, leading to divergent behavioral outcomes. Given that both effects may originate in deep and spatially constrained structures such as the hippocampus, small-sample studies and conventional methodologies may fail to differentiate them effectively. Future research should employ large-scale, longitudinal designs utilizing high-field MRI and multimodal neuroimaging to characterize MECT-induced structure-function coupling in the hippocampus and its integration at the network level. Additionally, multiscale analyses spanning molecular, circuit, and network dimensions would be beneficial.