ObjectiveTo investigate the gene expression sequence and molecular mechanisms in the local microenvironment during the subacute to chronic phases (1-28 days) in mouse models of spinal cord compression injury and hemisection spinal cord injury, thereby revealing the molecular characteristics of spinal cord repair and providing a theoretical basis for selecting therapeutic targets for spinal cord injury. MethodsThirty-six 8-9-week-old SPF-grade ICR mice were randomly divided into three groups (n=12 per group): sham-operated control (CTR) group, hemisection spinal cord injury (HSCI) group, and spinal cord compression injury (SCC) group. Mice in the CTR group underwent the same surgical preparation and anesthesia, followed by a dorsal midline incision at the T₉-T₁₀ segment. After layer-by-layer dissection and removal of the corresponding lamina, the spinal cord dura mater was fully exposed and kept intact. The cord was exposed to air for 10 minutes (matching the duration of the compression injury group), during which any instrument contact with the cord was avoided. The incision was then irrigated and sutured. The HSCI group underwent a 70% transection of the T₉ spinal cord segment using micro-instruments to establish a hemisection spinal cord injury model. The SCC group underwent sustained compression of the T₁₀ spinal cord segment for 10 minutes using a self-made compressor (a 30 g solid small iron bar) to establish a spinal cord compression injury model. Motor function recovery was assessed using the modified Basso-Beattie-Bresnahan (BBB) score on postoperative days 1, 3, 7, 14, 21, and 28. On days 7 and 14 post-operation, mice were anesthetized, and the injured spinal cord segments were harvested. The evolution of specific molecular networks in the spinal cord injury mouse models was analyzed via RNA sequencing (RNA-Seq) and enrichment analysis, and the expression of key genes was verified using real time fluorogenic quantitative PCR. ResultsBBB scores indicated that motor function recovery in the SCC group was significantly better than that in the HSCI group, with BBB scores showing a continuously increasing trend and remaining higher than those in the HSCI group over the 4-week period (P <0.001). Gene ontology （GO)and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses based on RNA-Seq differentially expressed genes revealed that, compared to the CTR group, genes related to the extracellular matrix were significantly up-regulated (P<0.05), while genes related to axon guidance were significantly down-regulated (P <0.05) in the SCC group on day 7 post-operation. On day 21, genes involved in immune regulation and the retinol signaling pathway were significantly activated in the SCC group (P<0.05). In contrast, in the HSCI group, genes associated with inflammation and immune response were significantly up-regulated (P<0.001), while genes related to neuronal differentiation and synapse formation were significantly down-regulated (P <0.001) on day 7. On day 21, genes related to cell-matrix junctions and N-methyl-D-aspartate receptors were significantly up-regulated (P<0.001) in the HSCI group. Furthermore, compared to the SCC group, the HSCI group exhibited different pathway enrichment characteristics in GO and KEGG analyses on days 7 and 21 post-injury. On day 7, genes involved in the NOD-like receptor signaling pathway and the complement and coagulation cascades were significantly up-regulated in the HSCI group (P<0.001). On day 21, genes related to the extracellular matrix-receptor interaction and the neuroactive ligand-receptor interaction pathways were significantly activated (P<0.001). Finally, real time fluorogenic quantitative PCR validation results were highly consistent with the RNA-Seq results, further confirming the differential expression trends of key genes between the SCC and HSCI groups. ConclusionThe SCC and HSCI injury models may drive distinct repair pathways: the preservation of some axons in the SCC model predisposes it toward tissue repair, whereas the HSCI model requires the coordination of more complex molecular networks to achieve a new equilibrium. This finding further deepens the understanding of the heterogeneous regulatory mechanisms underlying spinal cord injury.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Parkinson's disease （PD） is a neurological degenerative disease with a high clinical incidence， unclear etiology， and incurability. The main pathological features of PD are the loss of dopaminergic neurons in the midbrain substantia nigra and the formation of Lewy bodies. At present， the anti-parkinsonism drugs used in clinical practice have problems， such as decreasing efficacy and severe toxic side effects in the late stage of the disease. Mitochondrial autophagy is a self-regulation mode in which cells automatically remove damaged and aging mitochondria to maintain mitochondrial homeostasis. It is generally believed that the degree of mitochondrial autophagy is weakened in PD state， and this process mainly progresses through the ubiquitin-dependent pathway， non-ubiquitin-dependent pathway， and α-Synuclein-mediated mitochondrial autophagy pathway. Abnormal accumulation of damaged mitochondria will cause further damage to nerve cells and accelerate PD process. Therefore， restoring the mitochondrial autophagy balance， reducing the excessive accumulation of abnormal mitochondria， and reducing the damage of dopaminergic neurons in the substantia nigra are particularly important for the treatment of PD. Traditional Chinese medicine （TCM） has definite effect in the clinical prevention and treatment of PD， and studies have been carried out targeting the intervention of mitochondrial autophagy. A large number of studies have confirmed that single herbs and compound prescriptions of TCM can relieve nerve function defects and delay degenerative changes of nerve cells by restoring the balance of mitochondrial autophagy， thus playing a role in the treatment of PD. This paper systematically summarized the regulatory mechanisms of mitochondrial autophagy in the pathogenesis of PD and the influences of active ingredients from single herbs and compound prescriptions of TCM on mitochondrial autophagy. Furthermore， this paper explored the pathogenesis of PD and the basis of the therapeutic role of TCM through the intervention of mitochondrial autophagy， providing references for promoting the application of TCM in the prevention and treatment of PD.

Objective To study the correlation between Periostin, interleukin-33 (IL-33), and chronic cough after thoracoscopic lobectomy in patients with coronary artery bypass grafting (CABG) combined with lung cancer. Methods A total of 102 lung cancer and coronary heart disease patients at Tianjin Chest Hospital from January 2022 to January 2024 were prospectively enrolled, and they were divided into a chronic cough group (n=42) and a non-chronic cough group (n=60) based on whether chronic cough occurred after surgery. Serum levels of Periostin and IL-33 were measured on the 1st, 7th, and 14th days post-lobectomy. The Pearson method was employed to analyze the correlation between Periostin and IL-33 levels and the severity of cough. Univariate and multivariate logistic regression analyses were conducted to identify factors influencing the occurrence of chronic cough. Additionally, receiver operating characteristic (ROC) curve analysis was utilized to assess the potential value of serum Periostin and IL-33 levels in predicting postoperative chronic cough. Results In patients with chronic cough, the peripheral blood Periostin and IL-33 levels measured on days 7 and 14 were significantly higher than those in patients with non-chronic cough, and the interactions between the two groups and at different time points were significant (P<0.001). The degree of cough was positively correlated with the levels of Periostin and IL-33 on days 7 and 14 (P<0.05), but had no significant correlation with the levels on day 1 (P>0.05). In patients with lung cancer, after thoracoscopic lobectomy, Periostin [OR=1.619, 95%CI (1.295, 2.025)] and IL-33 [OR=1.831, 95%CI (1.216, 2.758)] on day 7 and Periostin [OR=1.952, 95%CI (1.306, 2.918)] and IL-33 [OR=1.742, 95%CI (1.166, 2.603)] on day 14 were identified as risk factors for chronic cough. ROC curve analysis showed that the sensitivity of Periostin on day 7 was 69.05%, the specificity was 71.67%, and the area under the curve (AUC) was 0.756 [95%CI (0.616, 0.893)]. The sensitivity of Periostin on day 14 increased to 71.43% and the specificity was 76.67%, AUC was 0.762 [95%CI (0.633, 0.898)]. At the same time, the critical value of IL-33 on day 7 was 45.03 pg/mL, the sensitivity and specificity were both 83.33%, the AUC was 0.884 [95%CI (0.789, 0.980)], and the critical value of IL-33 on day 14 was 56.01 pg/mL, the sensitivity was 85.71%, the specificity was 80.00%, and the AUC was 0.899 [95%CI (0.799, 0.999)]. Joint logistic regression analysis of Periostin and IL-33 levels on days 7 and 14 showed showed that the sensitivity was 95.24%, the specificity was 95.00%, and the AUC reached 0.993 [95%CI (0.979, 1.000)]. Conclusion Periostin and IL-33 levels, measured at various time points, are abnormally elevated following thoracoscopic lobectomy in patients with combined CABG and lung cancer. These levels significantly correlate with cough severity. Given their predictive potential for chronic cough, these markers are deemed valuable biomarkers.

To report two cases of psychiatric symptoms associated with zonisamide, an antiepileptic drug, and raise clinical awareness of this potential adverse effect. Two male patients with epilepsy treated with zonisamide were retrospectively analyzed. Case 1 (25 years old) developed acute emotional and behavioral abnormalities (e.g., insomnia, aggression, incoherent speech) after switching from sodium valproate to zonisamide (200 mg/day). Case 2 (48 years old) had long-term zonisamide use (≥5 years) with persistent treatment-resistant psychotic symptoms (e.g., delusions, command hallucinations). Clinical courses, medication adjustments, and symptom responses were documented. In Case 1, psychiatric symptoms resolved after discontinuing zonisamide and switching to sodium valproate, with improved mood stability and reduced impulsivity. In Case 2, despite escalating antipsychotic medications (risperidone, clozapine), psychotic symptoms persisted, likely due to ongoing zonisamide use. Both cases highlighted zonisamide’s potential to exacerbate or induce psychiatric manifestations, possibly via mechanisms involving sodium/calcium channel inhibition and neurotransmitter dysregulation (e.g., dopamine, serotonin). Zonisamide can cause or worsen psychiatric symptoms, particularly in vulnerable individuals. Clinicians should monitor for mental health changes during zonisamide treatment and consider drug discontinuation or substitution with alternative antiepileptics (e.g., sodium valproate) if psychiatric adverse effects emerge. Awareness of this association is crucial to avoid misdiagnosis and optimize epilepsy management.

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.