Objective This study investigated the diversity of rodent populations and the infection status of Bartonella at three ports along the China-Mongolia border in 2022. Methods Rodents at three Belt and Road ports along the China-Mongolia border, namely Ganqimaodu, Erenhot, and Zhuengadabuqi, were morphologically identified. The Bartonella citrate synthase(gltA)gene was amplified by nested polymerase chain reaction(PCR), and PCR-positive products were sequenced. The resulting sequences were then analyzed for genetic characteristics. Phylogenetic analysis was performed using MEGA 11.0 software using Neighbor-Joining and Maximum-Likelihood method. Results A total of 94 rodents were captured, representing seven species from five families and six genera: Mus musculus, Meriones unguiculatus, Meriones meridianus, Spermophilus dauricus, Allactaga sibirica, Dipus sagitta, and Phodopus roborovskii. Among them, M. unguiculatus was the most abundant species, with 58 rodents, accounting for 61.70% of the total. Overall,11 positive Bartonella pathogen sequences were obtained from the three ports, with a positive detection rate of 11.70%(11/94). The infected rodent species included M. unguiculatus, M. meridianus, and A. sibirica, and two species of Bartonella were detected. Conclusions Rodents at Ganqimaodu, Erenhot, and Zhuengadabuqi ports along the China-Mongolia border were naturally infected with Bartonella. Rodent monitoring and pathogen prevention and control in this area should be strengthened.

Objective This study aimed to investigate the genetic diversity, differentiation, and population structure of Aedes albopictus across different geographical regions in Shandong Province, and to explore the relationship between genetic diversity and geographical distribution. Methods Between July and August 2024, ten Ae. albopictus populations were sampled from seven cities in Shandong Province. Genomic DNA was extracted from individual mosquitoes, and the mitochondrial cytochrome c oxidase subunit I(COⅠ)gene was amplified using PCR and sequenced. The obtained sequences were verified using BLAST and analyzed with MAFFT, MEGA 11, DnaSP v6.12, Arlequin 3.5, PopART 1.7, STRUCTURE 2.3.4 and the R packages adegenet and vegan to assess genetic diversity and population structure. Results A total of 229 COⅠ sequences(662 bp) was obtained, revealing ten variable sites with no insertions or deletions. The overall base composition showed an AT bias of 67.7%. Haplotype analysis identified 11 haplotypes, with Hap2 being the dominant and most widely distributed haplotype across all populations. Neutrality tests showed significant population expansion only in the Rizhao population. Mantel testing result revealed that geographical distance does not significantly impede gene flow. Overall, genetic differentiation among populations was low, indicating frequent gene flow. When combined with additional samples from Shanghai, Fujian, Guangdong, Yunnan, Hainan and Guangxi, STRUCTURE, UPGMA and DAPC analyses revealed two primary genetic clusters of Ae. albopictus. Conclusions Ae. albopictus populations in Shandong Province exhibit frequent gene flow, low genetic differentiation, and relatively low overall genetic diversity. However, the Rizhao population showed signs of recent expansion, highlighting the need for enhanced surveillance and targeted control measures in this area.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Background Large-for-gestational-age (LGA) births are associated with adverse perinatal outcomes and increased risks of offspring obesity, metabolic syndrome, and cardiovascular diseases later in life. Beyond traditional risk factors, exposure to environmental factors, especially fine particulate matter (PM_2.5), before and during pregnancy may contribute to excessive fetal growth; however, the roles of specific chemical constituents and critical exposure windows remain unclear. Objective To examine the associations between maternal exposures to PM_2.5 and its chemical constituents before and during pregnancy and the risk of delivering LGA infants. Methods Singleton pregnancies from the National Free Preconception Health Examination Project between 2010 and 2014 were included. Individual exposures to PM_2.5 and its constituents were estimated for preconception and pregnancy windows using geocoded residential addresses. The associations of single and mixed exposures with LGA risk were analyzed using generalized linear models (GLMs) and qg-computation. Results Exposures to PM_2.5 and its major chemical constituents were significantly associated with an increased LGA risk, with differences in effect magnitude across components. Secondary inorganic aerosols showed the strongest associations. For full-pregnancy exposure, nitrate (OR=1.330, 95%CI: 1.313, 1.347), ammonium (OR=1.279, 95%CI: 1.263, 1.295), and sulfate (OR=1.242, 95%CI: 1.227, 1.257) had larger effects on LGA risk than black carbon and organic matter. Analysis by exposure window indicated that the month preceding conception and the third trimester of pregnancy were critical exposure windows for susceptibility, while the strongest effect was observed for full-pregnancy exposure, suggesting a cumulative effect over time. Mixed exposure analysis further showed that nitrate and sulfate consistently accounted for the main positive contributions across different time windows. Conclusion Maternal exposures to PM_2.5 and its chemical components before and during pregnancy are associated with an elevated LGA risk. Nitrate and sulfate show consistent and strong associations across pregnancy stages, underscoring the importance of component composition and exposure timing in fetal overgrowth.

Sichuan Province is a hilly schistosomiasis-endemic province in China with the highest endemicity and largest coverage. During the period of more than 70 years of integrated control, there are five distinct phases of schistosomiasis control in Sichuan Province, including baseline investigation, Oncomelania hupensis snail control, chemotherapy for both humans and livestock, management of source of Schistosoma japonicum infections, and sustained control and intensified surveillance and early warning, and a package of key interventions are implemented, including environmental modification, snail control with chemical treatment, large-scale chemotherapy for humans and livestock, management of source of S. japonicum infections, intensified integrated control, establishment of an early warning and surveillance system. As a result, schistosomiasis has been eliminated across all 63 disease-endemic counties (cities, districts) in Sichuan Province by June 2025. Government-led multi-sectoral collaborations, science and technology-supported precision control strategies, and a sustainable control model tailored to the ecological and socio-economic conditions in endemic regions are essential to achieving the target of schistosomiasis elimination in Sichuan Province.

ObjectiveTo investigate the intervention effect of Tengli Kangliu prescription （TKP） on the carcinogenesis of colorectal adenoma （CRA） induced by azoxymethane （AOM）/dextran sulphate sodium salt （DSS） in C57BL/6 mice and decipher the potential mechanism through regulating the signal transducer and activator of transcription 3 （STAT3） pathway to target M2-type macrophages. MethodsA total of 55 male C57BL/6 mice were randomized into a blank group （n=10）， a model group （n=15）， a celecoxib （0.02 g·kg^-1·d^-1） group （n=15）， a TKP （42.43 g·kg^-1·d^-1） group （n=15）. The mice in the model， TKP， and celecoxib groups were modeled for CRA lesions through the AOM/DSS three-cycle protocol. The intervention in each group began one week after free access to DSS and lasted for 12 weeks， and the blank group received 20 mL·kg^-1·d^-1 normal saline through gavage. Throughout the study period， changes in body mass and survival rate were recorded， alongside measurements of colorectal length and spleen mass. Histological changes of the colonic tissue were observed by HE staining. Immunohistochemical （IHC） staining was performed to detect the positive expression of CD68 and CD11c in the colorectal tissue. Western blot was employed to assess the protein levels of STAT3， phosphorylated （p）-STAT3， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） in the intestinal tissue. Real-time quantitative PCR was employed to analyze the mRNA levels of arginase 1 （Arg1）， CD206， and vascular endothelial growth factor （VEGF）. Enzyme-linked Immunosorbent assay（ELISA） was employed to measure the serum concentrations of Th2-type cytokines interleukin （IL）-4， IL-6， and IL-13 in mice. ResultsCompared with the blank group， the model group exhibited symptoms including diarrhea， hematochezia， and body mass loss， accompanied by shortened colon length， mucosal damage， and multiple tumors. In addition， the model group showcased up-regulated protein levels of STAT3， p-STAT3， and Bcl-2， down-regulated protein level of Bax， increased positive expression of CD68 and CD11c， and up-regulated mRNA levels of Arg1， CD206， and VEGF in the colon tissue， together with elevated serum levels of IL-4， IL-13， and IL-6 （P<0.05）. Compared with the model group， the above-mentioned indicators were partially reversed in both TKP group and celecoxib group， with superior effects observed in the TKP group （P<0.05）. ConclusionTKP significantly improves the survival quality of the mouse model of AOM/DSS-induced CRA by reducing intestinal inflammation and decreasing colorectal tumor number and size. It may delay the progression of AOM/DSS-induced colorectal tumor-like lesions by inhibiting activation of the STAT3/p-STAT3 signaling pathway in the intestinal tissue， targeting regulation of M2-type macrophages， and improving the tumor microenvironment， thereby suppressing CRA carcinogenesis.

This paper systematically analyzes schistosomiasis transmission risks during the elimination stage and reviews the evolution of the schistosomiasis surveillance system in China from a One Health perspective, with a special emphasis on schistosomiasis surveillance and response practices during the elimination stage from a One Health perspective. These practices include precise screening of human schistosomiasis under low-endemicity conditions, systematic monitoring of schistosomiasis in domestic and wild animals, ecological management of Oncomelania snails, and information-coordinated responses. Nevertheless, the current surveillance and response system for schistosomiasis suffers from challenges of insufficient cross-sectoral coordination and complex external environments, which constrain precise schistosomiasis surveillance and response in China. Therefore, it is urgently necessary to integrate coordination mechanisms, empower the surveillance system with technological innovation, improve capacity building, and actively promote diverse social participation in the One Health framework, so as to consolidate current schistosomiasis control achievements and achieve the target for schistosomiasis elimination across China, which may provide a replicable technical model for global zoonoses control.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.