Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Objective To analyze the characteristics and causes of an occupational acute carbon monoxide poisoning incident caused by a nitrogen generator malfunction. Methods The workers and the workshop from an electronic component manufacturing company in Guangzhou City, which had an occupational acute carbon monoxide poisoning incident, were selected as the research subjects using the retrospective investigation method. Relevant data of worksite survey of occupational health, clinical records of poisoning patients, and occupational disease diagnosis data were collected for analysis. Results A total of 15 workers who experienced discomfort in this incident, were from the final inspection workshop using high-purity nitrogen (purity of 99.999%). The short-term exposure concentration of carbon monoxide in the workplace air at three oven operating posts using high-purity nitrogen was 64.1, 581.0, and 142.0 mg/m³, respectively, while the concentration in the workplace air at the oven operating posts using regular nitrogen and the nitrogen-generating room was <0.1 mg/m³. Carboxyhemoglobin saturation levels in the 15 patients ranged from 2.000%-17.300%. Occupational acute mild carbon monoxide poisoning was diagnosed in nine patients, occupational acute carbon monoxide exposure reactions was diagnosed in six patients. This poisoning incident was caused by machine malfunction and improper operation, leading to occupational acute carbon monoxide poisoning. Conclusion Companies using nitrogen production machine should enhance their ability to identify carbon monoxide risks, strengthen training and management of workers, establish emergency response plans for nitrogen production and use, ensure proper maintenance of production equipment, and optimize operational procedures to prevent acute poisoning incidents.

AIM: To identify the primary active components and underlying mechanisms of Yijing Decoction(YJD)in treating early diabetic retinopathy(DR)based on liquid chromatography-mass spectrometry and network pharmacology.METHODS: Active components of YJD were characterized through LC-MS. Components with optimal ADME(absorption, distribution, metabolism, excretion)properties were selected as key bioactive candidates. Network pharmacology approaches were employed to predict YJD-DR therapeutic targets. Protein-protein interaction(PPI)networks, gene ontology(GO)enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were subsequently conducted to predict core targets and networks. Critical targets and pathways were experimentally validated through Western blot.RESULTS: Ten core therapeutic targets were identified, including TNF, Alb, EGFR, STAT3, PTGS2, ESR1, PPAR, MMP9, TLR4, and MAPK. YJD was related to cancer-related signaling, fluid shear stress and atherosclerosis, and neurodegenerative diseases, encompassing key biological processes such as inflammatory response regulation, programmed cell death activation, and enhanced cell migration. Furthermore, Western blot analysis confirmed that YJD significantly inhibited high glucose-induced phosphorylation of STAT3(P-STAT3/STAT3)and ERK(P-ERK/ERK)in rat retinal microvascular endothelial cells.CONCLUSION: This study revealed YJD's pharmacodynamical basis and its multi-component, multi-target, and multi-paths pharmacology. YJD exerts therapeutic effects on DR by coordinately regulating critical signaling pathways and alleviating intraocular inflammation, thus preserving retinal vascular endothelial cells, maintaining blood-retinal barrier integrity, and facilitating retinal neurovascular repair.

ObjectiveTo analyze the changes in the degree of coordination of China's major epidemic prevention and control efforts before and after the outbreak of the Corona Virus Disease 2019 (COVID-19), so as to explore the impact of epidemic prevention and control measures on coordination dynamics. MethodsA total of 3 864 policy documents related to epidemic prevention and control from January 2000 to December 2020 across 31 provinces (autonomous regions, and municipalities) in China were systematically collected. Contents specific to collaborative and cooperative efforts were extracted, and the extent of interdepartmental coordination were quantified to assess the effectiveness of epidemic prevention and control efforts. Wilcoxon signed-rank test was adopted to statistically analyze the differences between the indicators before and after the epidemic. ResultsThe average overall coordination level for major epidemic prevention and control in 31 provinces (autonomous regions, and municipalities) increased from 43.06% to 97.62%, and the average coordination levels in the eastern, central, and western China soared from 42.29%, 37.50%, and 47.46%, to 98.81%, 96.20%, and 97.46%, respectively, with statistically significant differences (all P<0.05). In terms of department categorization, coordination levels in the professional departments and the key support departments peaked at 100.00%, while other support departments rose to 95.43%, with an increase of 77.15%, 181.85%, and 139.89%, respectively, exhibiting noteworthy statistically significant differences (all P<0.001). ConclusionThe scope of coordination departments of China’s major epidemic prevention and control exists a remarkable surge following the COVID-19 outbreak, notable heightened coordination is particularly observed among the key support departments. Future endeavors should prioritize the roles played by diverse departments in epidemic prevention and control, enhancing both the clarity of departmental responsibilities and the effectiveness of interdepartmental coordination.

Objective: To investigate the impact of extracurricular physical activity on heart rate variability (HRV) among primary and secondary school students in Chengdu City, so ao to provide references for scientific exercise prescription. Methods: Using a convenient sampling method, 1 323 primary and secondary students were enrolled from central Chengdu who underwent physical fitness assessments at Sichuan Provincial Institute of Sports Science from September 2020 to January 2022. According to the standards of the National Physical Fitness Monitoring Center, boys and girls were divided into groups with and without extracurricular physical exercise habits. HRV was monitored using the SA-3000P device. Key HRV parameters were evaluated separately by gender, including standard deviation of normal to normal intervals (SDNN), root mean square of successive differences (rMSSD), total power (TP), low frequency power (LF) and high frequency power (HF). Statistical analyses were employed by t-test, Mann-Whitney U-test and Chi square test. Results: lgSDNN, lgrMSSD, TP, LF and HF in the group without extracurricular physical exercise habit [boys:(1.67±0.13)ms, (1.59±0.20)ms, (7.34±0.73)ms 2, (6.11±0.74)ms 2, (6.05±0.87)ms 2; girls:(1.67± 0.13)ms , (1.59±0.19)ms, (7.35±0.60)ms 2, (6.06±0.69)ms 2, (6.12±0.87)ms 2] were lower than those in the group with extracurricular physical exercise habit [boys:(1.75±0.13)ms, (1.72±0.18)ms, (7.69±0.62)ms 2, (6.41±0.76)ms 2, (6.44±0.79)ms 2；girls:(1.73±0.13)ms, (1.68±0.20)ms, (7.60±0.65)ms 2, (6.26±0.86)ms 2, (6.36±0.90)ms 2] ( t =-8.24, -8.75, -6.54, -5.35 , -6.33；-5.10，-4.90，-4.47，-2.71，-2.93, all P ＜0.01). Only the group of boys without extracurricular physical exercise habits showed a decrease in lgLF/HF [0.04(-0.19,0.27)] compared to the group with extracurricular physical exercise habits [ -0.03 (-0.25,0.20)] ( Z=-2.01, P <0.05). When the score classes of autonomic nerve activity, stress index and fatigue index were compared between boys and girls groups without and with extracurricular physical exercise habits, the proportion of boys normal and above scores increased from 79.3%, 84.1%, 71.8% to 91.4%, 95.7%, 87.3%, respectively, and the differences were statistically significant ( χ 2=47.42, 63.66, 38.28); the proportion of girls normal score and above increased from 79.8%, 85.7%, 75.0% to 85.4%, 92.1%, 79.4%, and the differences were statistically significant ( χ 2=48.31, 22.18, 22.22) (all P <0.01). Conclusion The primary and secondary school students who have the habit of extracurricular physical exercise have enhanced compliance in indicators related to HRV, showing more complex heart rate variability.

Recent years have witnessed significant advancements in myopia control research through the application of diffuse optical technology(DOT)spectacle lenses. Myopia has emerged as a global public health challenge, affecting nearly half of the world's population, with childhood and adolescent myopia rates continuing to rise. DOT lenses represent an innovative myopia control intervention based on retinal contrast signal theory. These lenses incorporate micro-light scattering dots distributed across the lens surface to reduce retinal imaging contrast and modulate the influence of visual input on axial elongation, thereby slowing myopia progression. The core mechanism operates through refractive index differences between the lens substrate(1.53)and scattering dots(1.50), which generate optical scattering effects. This design maintains clear vision through a central 5 mm optical zone while effectively reducing contrast signal intensity in the peripheral retina. Large-scale randomized controlled trials, including the CYPRESS study, have demonstrated significant myopia control efficacy in children aged 6-10 years: 12-month follow-up data revealed a 74% reduction in myopia progression and a 50% reduction in axial elongation, with sustained safety and visual quality maintained over 4-year long-term follow-up. However, several aspects of DOT technology remain contentious and require further clinical validation, including its applicability across different age groups, optimal scattering dot density configurations, combined application effects with other myopia control methods, and long-term visual adaptation during extended use. This review systematically examines the theoretical foundations, design characteristics, clinical application progress, and future development directions of DOT technology, providing scientific evidence for clinical myopia prevention and control strategy formulation.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Background Exposure to benzo[a]pyrene (BaP) may impair lung function through various mechanisms; however, it remains uncertain whether BaP induces ferroptosis in lung tissue cells, resulting in lung function impairment. Objective To investigate the ferroptosis of lung tissue cells triggered by subchronic BaP exposure in mice and its correlation with lung injury, and to explore the function of ferroptosis in BaP-induced lung tissue damage. Method Seventy-two healthy 3-weeks-old male C57BL/6J mice were acclimatized for 1 week and then randomly divided into six groups: control group (corn oil 10 mL·kg⁻¹), low-dose BaP group (2.5 mg·kg⁻¹), medium-dose BaP group (5 mg·kg⁻¹), high-dose BaP group (10 mg·kg⁻¹), BaP+ferrostatin-1 (Fer-1) group (10 mg·kg⁻¹+1 mg·kg⁻¹), and Fer-1 group (1 mg·kg⁻¹), with 12 mice each group. Corn oil and BaP were administered via gavage every other day, followed by an intraperitoneal injection of Fer-1 the subsequent day, throughout a period of 90 d. Whole-body plethysmography was applied to detect lung function; hematoxylin-eosin staining (HE) and Masson staining were used to observe lung tissue injury and fibrosis; microscopy of alveolar epithelial cells was conducted to reveal mitochondrial morphology; biochemical assays were used to measure the content of tissue iron, malondialdehyde (MDA), and glutathione (GSH), as well as the activity of glutathione peroxidase (GSH-Px); Western blotting and real-time quantitative PCR (RT-qPCR) analyses were performed to reveal the protein and mRNA expression of ferroptosis markers. Results Compared to the control group, the high-dose BaP group showed a significant increase in expiration time (Te) (P<0.01), and a significant decrease in ratio rate of achieving peak expiratory flow (Rpef), tidal volume (TVb), peak inspiratory flow (PIF), minute volume (MVb), and peak expiratory flow (PEF) (P<0.05 or 0.01). Based on the results of HE and Masson staining, partial destruction of alveolar structures, thickening of alveolar walls, infiltration of inflammatory cells, significant thickening of tracheal walls and a large deposition of collagen fibers in lung tissue were observed in the medium- and high-dose BaP groups. By microscopy, the alveolar epithelial cells exposed to low-dose BaP showed condensed chromatin, and the mitochondria exposed to medium and high-dose BaP showed wrinkles, increased mitochondrial membrane density, and diminished mitochondrial cristae. Compared to the control group, in the medium- and high-dose BaP groups, the lung tissue iron content and the expression levels of ACSL4 protein and mRNA significantly elevated (P<0.01 or 0.05), while the mRNA expression level of SLC7A11 significantly decreased (P<0.05); in the high-dose BaP group, the MDA content, COX2 protein, and PTGS2 mRNA expression levels significantly increased (P<0.05 or 0.01), GSH content and GSH-Px activity, GPX4 protein and mRNA expression levels, and the expression level of SLC7A11 protein significantly decreased (P<0.01 or 0.05). The ferroptosis inhibitor Fer-1 markedly reversed respiratory function, morphology, mitochondrial alterations, and the aforementioned ferroptosis-related biochemical indicators. Conclusion Subchronic exposure to BaP can induce ferroptosis in mice lung tissue cells, resulting in compromised lung function.

Objective To investigate the efficacy of leaflet augmentation technique to repair the recurrent mitral valve (MV) regurgitation after mitral repair in children. Methods A retrospective analysis was conducted on the clinical data of children who underwent redo MV repair for recurrent regurgitation after initial MV repair, using a leaflet augmentation technique combined with a standardized repair strategy at Fuwai Hospital, Chinese Academy of Medical Sciences, from 2018 to 2022. The pathological features of the MV, key intraoperative procedures, and short- to mid-term follow-up outcomes were analyzed. Results A total of 24 patients (12 male, 12 female) were included, with a median age of 37.6 (range, 16.5–120.0) months. The mean interval from the initial surgery was (24.9±17.0) months. All children had severe mitral regurgitation preoperatively. The cardiopulmonary bypass time was (150.1±49.5) min, and the aortic cross-clamp time was (94.0±24.2) min. There were no early postoperative deaths. During a mean follow-up of (20.3±9.1) months, 3 (12.5%) patients developed moderate or severe mitral regurgitation (2 severe, 1 moderate). One (4.2%) patient died during follow-up, and one (4.2%) patient underwent a second MV reoperation. The left ventricular end-diastolic diameter was significantly reduced postoperatively compared to preoperatively [ (43.5±8.6) mm vs. (35.8±7.8)mm, P<0.001]. Conclusion The leaflet augmentation technique combined with a standardized repair strategy can achieve satisfactory short- to mid-term outcomes for the redo mitral repair after previous MV repair. It can be considered a safe and feasible technical option for cases with complex valvular lesions and severe pathological changes.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.