This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Alzheimer's disease (AD) is the commonest neurodegenerative disease that causes memory decline, cognitive dysfunction and behavior disorders in the aged people. Primary pathological hallmarks of AD include amyloid-β (Aβ), neurofibrillary tangles (NFTs), gliosis, and neuronal loss. Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels have important physiological functions, especially in aspects of controlling the resting membrane potential, pacemaker activity, memory formation, sleep and arousal. This article reviews the structure, distribution, regulation of HCN channels and the role of HCN channels in the pathological mechanisms of AD, aiming to provide drug therapeutic targets for the prevention and treatment of AD.
Humans ; Alzheimer Disease/physiopathology* ; Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels/physiology* ; Animals ; Amyloid beta-Peptides/metabolism*

OBJECTIVE: To compare the therapeutic efficacy of portal and tail vein transplantation of bone marrow-derived mesenchymal stem cells (BMSCs) against cholestatic liver fibrosis in mice. METHODS: BMSCs were isolated and co-cultured with starvation-activated hepatic stellate cells (HSCs). HSC activation markers were identified using immunofluorescence and qRT-PCR. BMSCs were injected into the liver tissues of bile duct ligation (BDL) mice via the tail and portal veins. Histomorphology, liver function, inflammatory cytokines, and the expression of key proteins were all determined in the liver tissues. RESULTS: BMSCs inhibited HSC activation by reducing α-SMA and collagen I expression. Compared to tail vein injection, DIL-labeled BMSCs injected through the portal vein maintained a high homing rate in the liver. Moreover, BMSCs transplanted through the portal vein resulted in greater improvement in liver color, hardness, and gallbladder size than did those transplanted through the tail vein. Furthermore, BMSCs injected by portal vein, but not tail vein, markedly ameliorated liver function, reduced the secretion of inflammatory cytokines, including TNF-α, IL-6, and IL-1β, and decreased α-SMA + hepatic stellate cell (HSC) activation and collagen fiber formation. CONCLUSION The therapeutic effect of BMSCs on cholestatic liver fibrosis in mice via portal vein transplantation was superior to that of tail vein transplantation. This comparative study provides reference information for further BMSC studies focused on clinical cholestatic liver diseases.
Animals ; Mice ; Mesenchymal Stem Cell Transplantation ; Liver Cirrhosis/etiology* ; Male ; Cholestasis/therapy* ; Mice, Inbred C57BL ; Hepatic Stellate Cells ; Mesenchymal Stem Cells

Objective To investigate the association between gastroesophageal reflux disease(GERD)and the risk of incident chronic obstructive pulmonary disease(COPD)and explore potential effect modifiers influencing this association.Methods Clinical data from 476 175 participants in the UK Biobank(2006-2010)were collected.A Cox proportional hazards model was used to assess the relationship between GERD and the risk of incident COPD.Subgroup analyses were conducted to examine potential modifiers of the primary findings.Results A total of 11 587(2.43%)new COPD cases were diagnosed.The Cox proportional hazards model revealed that GERD was associated with an increased risk of incident COPD(HR=1.59,95%CI=1.46-1.74,P<0.001).GERD was linked to a higher risk of incident COPD in individuals aged<60 years(P<0.001)and non-smokers(P=0.011).No association was observed between GERD and the risk of incident COPD in current smokers with a daily cigarette consumption<10 cigarettes(P=0.261).Conclusion GERD may increase the risk of incident COPD.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Gastroesophageal Reflux/epidemiology* ; Middle Aged ; Proportional Hazards Models ; Incidence ; Male ; Risk Factors ; Female ; Aged

This paper uses literature and network data to systematically sort out the theoretical and practical foundations of global public health cooperation,combines expert interviews to conduct empirical analyses,and further explores China's strategies for participating in global public health cooperation through quantitative statistics and text mining of interview data,and proposes a plan for China's participation in global public health cooperation under the current international situation.Under the countercurrents to globalization,China should take its own public health capacity building as the foundation,put global security and health equity at the core,with a philosophy of open cooperation and sustainable development,actively promote bilateral and multilateral cooperation,focus on cultivating global health talents,and enhance the effectiveness of disease prevention and control by making use of existing platforms,international mechanisms and digital health technologies,so as to help build a Global Community of Health for All.

Syringa pinnatifolia, belonging to the family Oleaceae, is a species endemic to China. It is predominantly distributed in the Helan Mountains region of Inner Mongolia and Ningxia of China. The peeled roots, stems, and thick branches have been used as a distinctive Mongolian medicinal material known as "Shan-chen-xiang", which has effects such as suppressing "khii", clearing heat, and relieving pain and is employed for the treatment of cardiovascular and pulmonary diseases and joint pain. Over the past five years, significant increase was achieved in research on chemical constituents and pharmacological effects. There were a total of 130 new constituents reported, covering sesquiterpenoids, lignans, and alkaloids. Its effects of anti-myocardial ischemia, anti-cerebral ischemia/reperfusion, sedation, and analgesia were revealed, and the mechanisms of agarwood formation were also investigated. To better understand its medical value and potential of clinical application, this review updates the research progress in recent five years focusing on the chemical constituents and pharmacological effects of S. pinnatifolia, providing reference for subsequent research on active ingredient and support for its innovative application in modern medicine system.
Medicine, Mongolian Traditional ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Syringa/chemistry*