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.

To assess the current status of early surgical site infections following prosthetic implantation in plastic surgery across four provincial-level administrative regions in China, and to explore the effectiveness of standardized training for infection prevention and control.

Objective: To identify the latent classes of acceptance and striving and their associated factors among nursing students, and to examine the mediating role of positive acceptance and striving in the association between self transcendence and subjective well being, so as to provide evidence for targeted interventions to improve subjective well being among nursing students. Methods: From July to October 2025, a convenience sample of 861 nursing students was recruited from five schools in Sichuan and Chongqing, China. Participants were surveyed using the Self transcendence Scale, the Positive Acceptance and Striving Scale, and the General Well being Scale. Latent profile analysis was conducted to identify profiles of positive acceptance and striving. Logistic regression analysis was used to examine associated factors, and relative mediation analysis was performed to assess differences in the mediating effect across latent profiles. Results: Three latent classes of acceptance and striving were identified: the low acceptance-low striving profile (46.34%, n =399), the moderate acceptance-moderate striving profile (40.88%, n =352), and the high acceptance-high striving profile (12.78%, n =110). Multivariable Logistic regression analysis showed that, with the low acceptance-low striving profile as the reference, nursing students with higher self transcendence scores ( OR =151.85) and those who studied nursing because of personal preference ( OR =14.72) or parental expectations ( OR =11.16) were more likely to be classified into the high acceptance-high striving profile (all P <0.05). Male students ( OR =0.19), those perceiving nurses social status as average ( OR =0.35), and those receiving moderate teacher support ( OR =0.23) were less likely to be classified into the high acceptance-high striving profile (all P <0.05). Positive acceptance and striving partially mediated the association between self transcendence and subjective well being, with a total effect of β =0.97 and a mediating effect of β =0.48; the mediating effect accounted for 49.34% of the total effect. Relative mediation analysis showed that the mediating effect was statistically significant only in the low acceptance-low striving profile ( β =0.21), whereas the direct effects were stronger in the moderate acceptance-moderate striving and high acceptance-high striving profiles ( β =0.39, 1.06)(all P <0.05). Conclusions Positive acceptance and striving among nursing students exhibit substantial heterogeneity. Its predictive effect on subjective well being and the underlying mediating mechanism vary across latent profiles. Profile specific interventions should therefore be implemented to improve subjective well being among nursing students.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Objective To construct machine learning(ML)model for predicting early neurologi-cal deterioration(END)after intravenous thrombolysis(IVT)in patients with acute ischemic stroke(AIS),and to analyze risk factors of END using Shapley additive explanations(SHAP).Methods A total of 97 AIS patients who received IVT were enrolled.Patients were divided into END group(18 cases)and non-END group(79 cases)based on whether they experienced END within 24 hours post-IVT.All patients were randomly divided into training set(n=68)and validation set(n=29)at ra-tio of 7 to 3.Univariate and least absolute shrinkage and selection operator(LASSO)analyses were performed to screen important feature variables associated with END from clinical data.Six ML algo-rithms,including random forest,light gradient boosting machine,decision tree,support vector ma-chine,k-nearest neighbors and extreme gradient boosting,were employed to construct predictive mod-els.Receiver operating characteristic(ROC)curves,calibration curves and clinical decision curve analysis(DC A)were used to evaluate the performance of each ML model.The SHAP method was introduced to interpret the optimal ML model.Results Among the six ML algorithm models,the random forest model was identified as best predictive model.In the training set,it achieved area un-der the curve(AUC)of 0.909,with specificity,precision,recall and F1 score being 0.873,0.856,0.910 and 0.825,respectively.In the validation set,its AUC was 0.915,with correspond-ing values of 0.824,0.800,0.945 and 0.834.Calibration curves and DC A demonstrated that the random forest model had higher prediction accuracy and clinical net benefit.SHAP variable impor-tance plots revealed that the top six contributing imaging factors to END were large-area cerebral in-farction,pre-thrombolysis National Institutes of Health Stroke Scale(NIHSS)score,door-to-needle time(DNT),history of atrial fibrillation,white blood cell(WBC)levels and history of diabetes.Conclusion ML models can effectively predict the risk of END in IVT patients,with the random forest model demonstrating the best predictive performance.Combining SHAP for model visualization interpretation aids clinicians in understanding the contribution of each feature variable to the predic-tion results,thereby facilitating targeted preventive treatment strategies.

Objective To construct a hybrid decision-making model that integrates knowledge-driven and data-driven approaches,and to apply it to the etiological diagnosis of ventricular tachycardia(VT).Methods Clinical practice guidelines,expert consensus documents,and medical literature in the field of ar-rhythmia diseases from 2018 to 2023 were retrieved as knowledge sources.Retrospective electronic medical re-cord data of VT patients from Fuwai Hospital,Chinese Academy of Medical Sciences & Peking Union Medical College,from 2013 to 2023 were collected as the dataset.A knowledge-driven model was constructed using a knowledge-rule-based approach to establish clinical pathways.A three-class machine learning model for VT eti-ology diagnosis was developed based on real-world data,and the best-performing model was selected as the rep-resentative of the data-driven approach.The machine learning model was embedded into the decision nodes of the clinical pathway in the form of custom operators,forming the hybrid model.The precision,recall,and F1 score of the three models were evaluated.Results Three clinical practice guidelines were included as knowl-edge sources for the knowledge-driven model.A total of 1305 patient records were collected as the dataset,and five machine learning models were constructed,with the XGBoost model performing the best.The hybrid model adopted a knowledge-driven decision-making framework,embedding the XGBoost model into the decision nodes of a two-level classification.The precision,recall,and F1 scores of the three models were as follows:the knowledge-driven model achieved 80.4％,79.1％,and 79.7％;the data-driven model achieved 88.4％,88.5％,and 88.4％;and the hybrid model achieved 90.4％,90.2％,and 90.3％.Conclusions The hybrid model integrating knowledge-driven and data-driven approaches demonstrated higher accuracy,and all its deci-sion outcomes were based on evidence-based practices,aligning more closely with the actual diagnostic reason-ing of clinicians.Further rigorous validation is needed to assess the feasibility of widely applying the hybrid model in the medical field.

Objective To compare TyG index between the patients with CHF and ADHF to eluci-date the metabolic difference between these two stages.Methods A total of 1156 HF patients ad-mitted in Taizhou People's Hospital between January 2020 and December 2022 were enrolled,and according to 2021 ESC Guidelines for Diagnosis and Treatment of Acute and Chronic Heart Fail-ure,they were divided into CHF group(365 cases)and ADHF group(791 cases).The clinical da-ta,results of laboratory tests,and cardiovascular history were collected,and TyG index was calcu-lated.All-cause death outcome was observed in ADHF patients during a follow-up of 1 year.Results The TyG index was significantly lower in the ADHF group than the CHF group[8.27(7.99,8.62)vs 8.35(8.04,8.75),P=0.001].In the ADHF group,the TyG index was positively correlated with SBP,DBP,TC,TG,LDL-C,FPG,HbA1c,BMI,and LVEF,and negatively with age(P＜0.01).In the CHF group,the index was positively correlated with DBP,TC,TG,LDL-C,FPG,BMI,and HbA1c,and negatively with age(P＜0.05,P＜0.01).Both univariate and multiva-riate logistic regression analyses indicated that the TyG index was a protective factor for ADHF(OR=0.647,95％CI:0.503～0.832,P=0.001;OR=0.694,95％CI:0.536～0.898,P=0.005).Multivariate logistic regression analysis showed that the index in ADHF patients was a protective factor for one-year all-cause mortality(OR=0.483,95％CI:0.254-0.916;P=0.026).Conclusion TyG index might be regarded as an important marker for assessing the metabolic status in HF patients and predicting the prognosis in ADHF patients.

Objective:To investigate the clinical application effect of Zishen Yutai Pill in patients with repeated implantation failure (RIF) undergoing frozen-thawed embryo transfer (FET) cycles.Methods:A retrospective case-control study was conducted, selecting 744 cycles of patients with RIF at the Department of Female Reproductive Medicine,State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University from October 2017 to April 2023. The patients were divided into experimental group (treated with Zishen Yutai Pill, n=279) and control group (treated without Zishen Yutai Pill, n=465) based on whether Zishen Yutai Pill was added to luteal support. The pregnancy outcomes between the two groups were compared. Based on the different endometrial preparation protocols in the FET cycles, the patients were used down-regulation protocol ( n=271) or non-down-regulation protocol ( n=473). The pregnancy outcomes of the two groups in each protocol were compared. Results:There were no statistically significant differences between the two groups in terms of biochemical pregnancy rate, clinical pregnancy rate, embryo implantation rate, early miscarriage rate, late miscarriage rate, and live birth rate (all P>0.05). However, the biochemical pregnancy rate [69.0% (58/84)], clinical pregnancy rate [59.5% (50/84)], and embryo implantation rate [59.4% (57/96)] in the experimental group of the down-regulated protocol were significantly higher than those in control group [56.1% (105/187), P=0.045; 46.5% (87/187), P=0.048; 44.9% (92/205), P=0.019], with statistically significant differences. In the non-down-regulated protocol, there were no statistically significant differences in pregnancy outcomes between the two groups (all P>0.05). Conclusion:In the FET down-regulated protocol, Zishen Yutai Pill can significantly improve the clinical pregnancy rate and the embryo implantation rate in patients with RIF, thereby improving pregnancy outcomes.

Objective To investigate the effect of tissue-resident memory T cells(TRM)on imiquimod-induced psoriatic-like skin lesions in mice,and to elucidate the underlying mechanisms of TRM involvement in this process.Methods Forty female BALB/c mice were procured and randomly allocated into four groups:ten in the blank control group,and thirty for the establishment of a psoriasis mouse model.Following successful modeling,the thirty mice were further randomized into three groups:the model control group,the methotrexate-treated group,and the imiquimod-treated group,with ten mice in each group.Mice in the blank control group and model control group were uniformly treated with Vaseline for intervention.The methotrexate group and the imiquimod group were treated with 62.5mg of 5％imiquimod cream.The methotrexate group was administered by gavage at a dose of 1 mg/kg,and the gavage volume of each group was 10 mL/kg.The model control group,blank group and imiquimod group were gavaged with the same volume of normal saline.Treatment was conducted over six consecutive days.Subsequently,comparisons were made across groups regarding the psoriasis area and severity index(PASI),histopathological findings,inflammatory cytokine levels,and TRM cell levels.Results(1)The imiquimod group exhibited signifi-cantly lower scores for erythema(2.54±0.32),skin thickening(2.59±0.25),and scaling(2.52±0.29)compared to the methotrexate group,model control group,and blank control group(P<0.05).Additionally,the methotrexate group demonstrated reduced scores for erythema,skin thickening,and scaling compared to the model control group(P<0.05).(2)Hematoxylin-eosin(HE)staining revealed that the epidermis in the methotrexate group became thin-ner,with fewer parakeratotic cells and increased hair follicles.Conversely,the imiquimod group displayed abnor-mal cell morphology and relatively thicker white skin after modeling.(3)The imiquimod group showed significantly lower levels of TNF-α(51.63±4.39 pg/mL),IL-1β(35.53±4.15 pg/mL),IFN-γ(23.43±3.41 pg/mL),and IL-23(15.24±2.95 pg/mL)compared to the methotrexate and model control groups(P<0.05).Similarly,the methotrexate group exhibited reduced levels of TNF-α,IL-1β,IFN-γ,and IL-23 compared to the model control group(P<0.05).(4)The imiquimod group had significantly lower levels of CD8+CD103+cells(15.39±2.31)than the methotrexate and model control groups(P<0.05).Furthermore,the methotrexate group demonstrated lower levels of CD8+CD103+cells compared to the model control group(P<0.05).Conclusion Miquimod induces heavier skin lesions,faster response,and more epidermal thickening in psoriasis like mice.CD8+CD103+TRM cells and inflammatory factors may be involved in the recurrence of psoriasis.

Objective:To investigate the inhibitory effect and mechanism of puerarin(Pue)on hydrogen peroxide(H2 O2)induced ferroptosis in the rat Schwann cell derived cell line RSC96.Methods:The RSC96 cells were incuba-ted with H2 O2 to establish a cellular injury model,while a subset of cells were co-incubated with H2 O2 and Pue.The vi-ability of cells was examined using the CCK-8 assay.The intracellular levels of glutathione(GSH),total superoxide dismutase(T-SOD),reactive oxygen species(ROS),malondialdehyde(MDA),and ferrous ions(Fe2+)levels were quantified using commercial kits.Western blot was employed to detect the protein expression level of glutathione peroxi-dase 4(GPX4),cyclooxygenase-2(COX-2),solute carrier family 7 member 11(SLC7A11),nuclear factor erythroid 2-related factor 2(Nrf2),and heme oxygenase-1(HO-1).Immunofluorescence assay was performed to examine the expression and nuclear distribution of Nrf2.Results:Pue pretreatment significantly increased the survival rate of H2 O2-treated RSC96 cells,increased the intracellular content of GSH and T-SOD,and inhibited the concentration of ROS and MDA.It also activated the nuclear translocation of Nrf2 and upregulated GPX4,SLC7A11,HO-1,and Nrf2 proteins in RSC96 cells;This effect was abolished by the Nrf2 inhibitor ML385.Conclusion:Pue treatment alleviated the H2 O2-induced ferroptosis of RSC96 cells via the Nrf2/SLC7A11/GPX4 signaling pathway.