The neurophysiological mechanisms by which exercise improves cognitive function have not been fully elucidated. A comprehensive and systematic review of current domestic and international neurophysiological evidence on exercise improving cognitive function was conducted from multiple perspectives. At the molecular level, exercise promotes nerve cell regeneration and synaptogenesis and maintains cellular development and homeostasis through the modulation of a variety of neurotrophic factors, receptor activity, neuropeptides, and monoamine neurotransmitters, and by decreasing the levels of inflammatory factors and other modulators of neuroplasticity. At the cellular level, exercise enhances neural activation and control and improves brain structure through nerve regeneration, synaptogenesis, improved glial cell function and angiogenesis. At the structural level of the brain, exercise promotes cognitive function by affecting white and gray matter volumes, neural activation and brain region connectivity, as well as increasing cerebral blood flow. This review elucidates how exercise improves the internal environment at the molecular level, promotes cell regeneration and functional differentiation, and enhances the brain structure and neural efficiency. It provides a comprehensive, multi-dimensional explanation of the neurophysiological mechanisms through which exercise promotes cognitive function.
Animals ; Humans ; Brain/physiology* ; Cognition/physiology* ; Exercise/physiology* ; Nerve Regeneration/physiology* ; Neuronal Plasticity/physiology*

Objective:To explore the longitudinal effect of learning stress on learning burnout in vocational college students, and the mediating role of academic procrastination.Methods:A total of 1 212 vocational college students were selected, and two follow-up surveys were conducted at 12-week intervals in September (T1) and November (T2) of 2024 using the basic situation questionnaire, the burnout inventory-student survey, the learning pressure questionnaire and the brief academic procrastination scale. SPSS 26.0 software was used to compare the demographic characteristics of students' depersonalization using t test and single factor analysis of variance. Bootstrap was used to analyze the relationship among learning stress, academic procrastination and learning burnout. Results:The scores of learning stress at T1 and T2 for vocational college students were 14.47±3.52 and 14.52 ±3.50, the scores of academic procrastination at T1 and T2 were 27.14±9.07 and 27.21±9.04, and the scores of learning burnout T1 and T2 were 39.38±8.76 and 39.69±8.79.The t-test showed that the score of learning burnout at T1 of students aged 18 and below (36.70±8.72) was lower than students aged 18 above (40.15±8.63, t=-5.81, P<0.01). The score of learning burnout for liberal arts students at T1(40.82±8.54) was higher than that of science students (37.68±8.72, t=6.31, P<0.01). Single factor analysis of variance showed that the score of learning burnout for grade 1 students at T1(35.19±8.45) was lower than that of grade 2 students (41.33±7.98) and grade 3 students (38.92±9.88), and learning burnout score of grade 2 students at T1 was higher than that of grades 3 students ( F=61.59, P<0.01). The score of learning burnout for high-achieving students at T1(36.23±8.34) was lower than that of middle-achieving students (39.82±8.52) and low-achieving students (45.42±9.14), and the score of learning burnout for middle-achieving students at T1 were lower than that of low-achieving students ( F=36.53, P<0.01). Bootstrap test showed that academic procrastination T2 played a partial mediating role in the relationship between learning stress T1 and learning burnout T2 (effect size=0.04, 95% CI=0.03-0.07). Academic procrastination T1 played a partial mediating role in the relationship between learning stress T1 and learning burnout T2 (effect size=0.05, 95% CI=0.04-0.07). Conclusion:Learning stress can directly affect learning burnout in vocational college students, and also can indirectly affect learning burnout through the mediating effect of academic procrastination.

In order to explore the effects of lipopolysaccharide(LPS)on the repair of bovine endo-metrial stromal cells(BESCs)during inflammatory response,BESCs were treated by LPS in this study.Cell apoptosis rate was detected using flow cytometry,cell viability was measured using the CCK-8 assay,cell migration ability was observed using a scratch assay,and the expression of con-nective tissue growth factor(CTGF),transforming growth factor-beta 3(TGF-β3)and vascular endothelial growth factor(VEGF)mRNA was measured using qRT-PCR.Additionally,the expression of key proteins in the PI3K/AKT and Wnt/β-catenin signaling pathways was assessed using Western blot analysis.The results showed that cell viability of BESCs significantly decreased(P＜0.01),cell migration ability decreased(P＜0.05),apoptosis rate of BESCs increased(P＜0.01),CTGF and TGF-β3 mRNA expression levels decreased(P＜0.01),while VEGF mRNA ex-pression increased after treatment with LPS(P＜0.01).The phosphorylation levels of PI3K,AKT and GSK-3β proteins decreased(P＜0.05),as well as the expression levels of c-Myc and Cyclin-D1 proteins also decreased(P＜0.01).These results indicated that LPS can inhibit the proliferation of BESCs and promote cell apoptosis possibly through the inhibition of the PI3K/AKT and Wnt/β-catenin signaling pathways.

Objective To evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Aim To explore the mechanism of baicalin combined with heat stimulation in treating acute lym-phoblastic leukemia(ALL)based on network pharma-cology and in vitro experiments.Methods The CCK-8 assay was used to screen the suitable conditions for heat stimulation to interfere ALL cell lines Jurkat,CCRF-CEM,Hut-78 and a normal lymphocyte HMy2.CIR,and the effects of baicalin combined with heat stimulation on the proliferation of three ALL cell lines and a normal lymphocyte were tested.The key targets of baicalin combined with fever stimulation for the treatment of ALL were obtained based on network phar-macological analysis,and the potential mechanisms were predicted by gene ontology(GO)annotation and kyoto encyclopedia of genes and genomes(KEGG)en-richment.The expression levels of TNF-α,AKT1,TYMS and CASP3 mRNA in ALL cell lines Jurkat and CCRF-CEM were examined by RT-qPCR with baicalin alone and baicalin combined with heat stimulation.Results The optimal conditions for heat stimulation to intervene ALL cells were 41 ℃ for 24 h,and heat stimulation combined with baicalin synergistically inhibited the growth of ALL cell lines and effectively reduced the cy-totoxicity of baicalin.Based on the network pharmaco-logical analysis,55 intersecting targets of baicalin with ALL diseases and 77 intersecting targets of baicalin with fever were obtained.The results of GO annotation and KEGG enrichment suggested that baicalin com-bined with fever stimulation to intervene ALL might be associated with influencing intracellular reactive oxygen species metabolism,DNA transcription and apoptotic processes involved in cysteine enzymes.Apoptosis,TNF and IL-17 signaling pathways were the key pathways for baicalin combined with heat stimulation in treating ALL.Under heat stimulation at 41 ℃ using SDHA gene as housekeeping gene,in vitro experiments showed that baicalin significantly up-regulated the expression of TNF-α and CASP3,and down-regulated the expression of TYMS in ALL cells.Conclusions Based on net-work pharmacologic analyses and in vitro experiments,baicalin combined with heat stimulation can regulate TNF-α and CASP3 gene levels in ALL cells and de-stroy cellular structure to promote cell apoptosis,thus synergistically treating ALL.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Depression is a heterogeneous mental disorder in which the interaction between genetic susceptibility and environ-mental factors plays a key role in its pathogenesis.Although the specific mechanisms of the disease still need to be thoroughly studied and elucidated,there is now a broad consensus that epi-genetic markers have a central influence on its mechanism of ac-tion.DNA methylation of brain-derived neurotrophic factor(BD-NF)is not only regarded as a promising epigenetic biomarker of pathology,but may also help predict the efficacy of antidepres-sants.In this paper we reviewed the gene structure of BDNF and its DNA methylation regulation mechanism,and also analyzed the changes of DNA methylation of this factor in depression pa-tients and animal models,aiming to provide new ideas and theo-retical support for clinical research.

OBJECTIVE: To determine the prevalence of lumbar spondylolysis (LS) and the proportion of spondylolytic spondylolisthesis (SS) in China, and to evaluate the musculoskeletal status of patients with LS and SS. METHODS: Spine Computed Tomography (CT) images were collected from community populations aged 40 and above in a nationwide multi-center project. LS was diagnosed, and SS was graded by an experienced radiologist. Bone mineral density (BMD) and paraspinal muscle parameters were quantified based on CT images. RESULTS: One hundred and seventeen patients of a total of 3,317 individuals were diagnosed with LS, corresponding to a prevalence rate of 3.53%. 63 of the 1,214 males (5.18%) and 54 of the 2,103 females (2.57%) were diagnosed with LS. SS occurred in 64/121 vertebrae (52.89%). BMD was not associated with LS ( P = 0.341). The L5 extensor paraspinal muscle density was higher in the LS group than in the non-LS group. In the LS group, patients with SS had a smaller L5 paraspinal extensor muscle cross-sectional area than those without SS ( P = 0.003). CONCLUSION The prevalence of LS in Chinese adults was 3.53%, with prevalence rates of 5.18% in males and 2.57% in females. Patients with LS have higher muscle density, whereas those with SS have smaller muscle cross-sectional areas at the L5 level.
Humans ; Male ; Female ; Middle Aged ; China/epidemiology* ; Prevalence ; Adult ; Lumbar Vertebrae/diagnostic imaging* ; Spondylolysis/diagnostic imaging* ; Aged ; Bone Density ; Tomography, X-Ray Computed ; Aged, 80 and over ; Spondylolisthesis/epidemiology* ; East Asian People

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index