BACKGROUND:More and more animal experiments and clinical studies have confirmed that electrical stimulation can promote the repair of peripheral nerve injury,but the specific mechanism is not yet fully understood. OBJECTIVE:To investigate the effect of electrical stimulation-induced miR-741-3p regulating Radil on Schwann cell migration. METHODS:(1)Twelve male SD rats were randomly divided into electrical stimulation group and control group.The electrical stimulation group received continuous electrical stimulation for 7 days after sciatic nerve compression injury,while the control group was not treated after sciatic nerve compression.The injured nerves were taken on day 7 after operation.The expression difference of miR-741-3p between the two groups was verified by fluorescence in situ hybridization.(2)The target genes of miR-741-3p were predicted by miRDB,TargetScan,and miRWalk databases.(3)Schwann cells were transfected with miR-741-3p mimetic and its control,miR-741-3p inhibitor and its control,Radil siRNA and its control,miR-741-3p inhibitor+Radil siRNA and miR-741-3p inhibitor+siRNA control.The transfection efficiency was detected by RT-PCR.The migration ability of Schwann cells was detected by Transwell chamber. RESULTS AND CONCLUSION:(1)The fluorescence intensity of miR-741-3p in the electrical stimulation group was lower than that in the control group.(2)The results of database prediction showed that 69 genes might be the target genes of miR-741-3p.Radil was one of the predicted target genes,which was mainly involved in cell adhesion and migration.(3)Compared with the miR-741-3p inhibitor control group,the number of Schwann cell migration increased in the miR-741-3p inhibitor group(P<0.05).Compared with the miR-741-3p mimic control group,the number of Schwann cell migration in the miR-741-3p mimic group decreased(P<0.05).Compared with the siRNA control group,the number of Schwann cell migration was decreased in the Radil siRNA group(P<0.05).(4)Compared with miR-741-3p inhibitor control group,the expression level of Radil was increased in miR-741-3p inhibitor group.Compared with miR-741-3p mimic control group,the expression level of Radil was decreased in miR-741-3p mimic group.(5)Compared with miR-741-3p inhibitor+siRNA control group,the number of Schwann cell migration was reduced in miR-741-3p inhibitor+Radil siRNA group(P<0.05).The results showed that electrical stimulation promoted the migration of Schwann cells by down-regulating miR-741-3p and targeting Radil gene.

Objective To analyze the PLCβ4 gene mRNA expression and its clinical significance in hepatocellular carcinoma (HCC) based on TCGA database. Methods Based on the data on 424 clinical samples (including 374 cases of HCC tissues and 50 cases of nontumor liver tissues) in the TCGA database, Kaplan–Meier method, Cox regression analysis, and immune infiltration analysis were performed to evaluate the relationship between PLCβ4 gene and the clinical characteristics and survival prognosis of HCC patients. Correlation analysis between PLCβ4 gene and 24 types of immune cells was applied to investigate the relationship between PLCβ4 gene and immune cell infiltration and mRNA expression level of TP53 gene, a high-frequency mutation gene in HCC. In addition, paraffin sections of highly, moderately, and poorly differentiated tumor tissues and normal liver tissues from HCC patients were collected. The histopathological observation was carried out via HE staining method, and the expression levels of PLCβ4 and Ki-67 proteins in each clinical sample were verified through the immunohistochemical method. Results The expression level of PLCβ4 gene in HCC was significantly higher than that in normal tissues (P<0.01), and all patients in the PLCβ4 high-expression group had a significantly longer overall survival than those in the low-expression group (P<0.05), which suggested that PLCβ4 substantially affected the prognosis of HCC patients. Correlation analysis showed that the expression level of PLCβ4 gene was highly correlated with immune cell infiltration and the expression level of TP53 gene. As verified by clinical sample experiments, HE staining experiments and immunohistochemical results revealed that PLCβ4 gene expression in HCC tissue samples was significantly higher than that in normal tissues (P<0.001), and it was negatively correlated with the degree of differentiation. Conclusion PLCβ4 may serve as an independent prognostic factor in HCC and is expected to be a novel molecular target for HCC treatment.

ObjectiveTo establish an adjusted Serfling regression model to estimate the excess cases and the excess epidemic period of hand-foot-mouth disease (HFMD) in Beijing from 2011 to 2019, so as to provide data support and decision-making basis for HFMD prevention and control. MethodsThe weekly number of HFMD cases in Beijing from 2011 to 2019 was utilized for adjusted the Serfling regression model. Then the adjusted model was used to fit the baseline and epidemic threshold of HFMD in Beijing from 2011 to 2019, calculating the excess cases and determining the excess epidemic period. ResultsA total of 279 306 cases of HFMD were reported in Beijing from 2011 to 2019, with the climax of the disease occurring in summer and autumn. After adjusting the fitting R² of the Serfling regression model to 0.773, a total of 10 excess epidemic periods totaling 92 weeks were estimated, mainly occurring in summer. The highest number of excess cases during an excess epidemic period was found in 2014 (1 272 cases, 95%CI: 990‒1 554), accounting for 65.04% of the actual cases (95%CI: 50.62%‒79.46%). ConclusionThe adjusted Serfling regression model fits well and can be utilized for early warning of HFMD and estimating the disease burden caused by HFMD.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.

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.

BackgroundAs a high prevalence disorder， schizophrenia has caused significant burden to family and society due to the impairment of occupational and social function. Currently， the dominant vocational training model in China follows a paternalistic， clinician-led decision-making approach. Although it improves patients' social function to some extent， it undermines their autonomy and treatment adherence. Therefore， it is urgently necessary to explore a new intervention method to enhance treatment compliance and social function in patients. ObjectiveTo explore the impact of shared decision-making oriented vocational training on social function in hospitalized schizophrenia patients， so as to provide references for rehabilitation interventions. MethodsA total of 68 patients diagnosed with schizophrenia according to the International Classification of Diseases， tenth edition （ICD-10） criteria were consecutively enrolled from January to June 2024 at The Third People's Hospital of Wenjiang Distric， Chengdu. Participants were randomly allocated into the research group （n=34） and the control group （n=34） using a random number table method. Both groups received routine rehabilitation training， while the research group received shared decision-making oriented vocational training for 12 weeks， 2 times a week for 2 hours each time. Before and at the 4^th and 12^th week of intervention， two groups were evaluated by General Self-Efficacy Scale （GSES）， Stigma Scale for Mental Illness （SSMI）， Scale of Social function of Psychosis Inpatients （SSFPI） and Inpatient Psychiatric Rehabilitation Outcome Scale （IPROS）. ResultsA total of 63 participants completed the study， with 30 cases in the research group and 33 cases in the control group. Repeated measures ANOVA revealed statistically significant time effects and interaction effects in both groups for GSES， SSMI， SSFPI and IPROS scores （F=20.451， 16.022； 26.193， 12.944； 23.957， 5.023； 11.776， 3.985， P<0.05 or 0.01）， while no significant group effects were observed （F=0.188， 0.742， 1.878， 0.474， P>0.05）. At the 12^th week of intervention， there were statistically significant differences in GSES， SSMI， SSFPI and IPROS scores between the two groups. ConclusionShared decision-making oriented vocational training may help to improve social function in patients with schizophrenia. ［Funded by 2023 Chengdu Medical Research Project （number， 2023468）］

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

Objective To investigate dynamic changes in myocardial protein phosphorylation during the acute phase of myocardial infarction (MI) in mice. Methods Six 8-week-old C57BL/6J mice were randomly assigned to MI model (n＝3) or sham-operated control (n＝3) groups. Cardiac tissues were harvested 72 hours post-intervention for proteomic analysis. Phosphorylation modifications were systematically characterized using liquid chromatography-mass spectrometry (LC-MS). Bioinformatics analyses included differential phosphorylation screening, functional enrichment, hierarchical clustering, and protein-protein interaction network. Results LC-MS identified 1 921 differentially phosphorylated sites (20 tyrosine and 1 901 serine/threonine sites) across 851 proteins. Compared with controls, MI hearts exhibited significant phosphorylation upregulation at 1 545 sites and downregulation at 376 sites (P＜0.05). Conclusions This study delineates MI-associated phosphorylation dynamics, providing mechanistic insights and potential therapeutic targets for acute MI intervention.

Objective To explore predictive factors of severe community-acquired pneumonia (CAP) complicated with respiratory failure (RF) and to develop and internally validate a clinical prediction model. Methods A retrospective study was conducted on 350 patients with severe CAP admitted to Tianyou Hospital Affiliated to Wuhan University of Science and Technology from September 2022 to December 2024. Patients were randomly divided into a training set (n＝245) and a validation set (n＝105) in a 7∶3 ratio, and further categorized into RF and non-RF groups. LASSO regression was applied to optimize variable selection. Multivariate logistic analysis was used to construct the prediction model, followed by internal validation. Results Univariate regression analysis identified male, hypertension, diabetes, coronary heart disease, age, CURB-65 score, white blood cell count, neutrophil count, C-reactive protein (CRP), serum amyloid A, procalcitonin, and hospital stay as risk factors for RF in severe CAP, while albumin level was a protective factor. LASSO regression selected CURB-65 score, albumin level, and CRP for inclusion in the final model. The area under the receiver operating characteristic curve was 0.903 in the training set and 0.919 in the validation set. Calibration curve analysis demonstrated excellent agreement between predicted and observed probabilities in both sets, and Hosmer-Lemeshow goodness-of-fit tests indicated no significant deviations. Threshold probabilities ranged from 0.01 to 0.99 in both training and validation sets. Conclusions CURB-65 score, albumin level, and CRP are independent predictors of RF in severe CAP. The clinical prediction model based on these factors exhibits strong discrimination, calibration, goodness-of-fit, and clinical utility.