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.

Colorectal cancer(CRC) is a common malignant tumor worldwide. Due to the treatment intolerance and side effects, CRC rank the top among various cancers regarding the incidence and mortality rates. Therefore, exploring new therapies is of great significance for the treatment of CRC. Aerobic glycolysis(AEG) plays an important role in the microenvironment formation, proliferation, metastasis, and recurrence of CRC and other tumor cells. It has been confirmed that intervening in the AEG pathway can effectively curb CRC. The active ingredients and compound prescriptions of traditional Chinese medicine(TCM) can effectively inhibit the proliferation, metastasis, and drug resistance and regulate the apoptosis of tumor cells by modulating AEG-associated transport proteins [eg, glucose transporters(GLUT)], key enzymes [hexokinase(HK) and phosphofructokinase(PFK)], key genes [hypoxia-inducible factor 1(HIF-1) and oncogene(c-Myc)], and signaling pathways(MET/PI3K/Akt/mTOR). Accordingly, they can treat CRC, reduce the recurrence, and improve the prognosis of CRC. Although AEG plays a key role in the development and progression of CRC, the specific mechanisms are not yet fully understood. Therefore, this article delves into the intrinsic connection of the targets and mechanisms of the AEG pathway with CRC from the perspective of tumor cell glycolysis and explores how active ingredients(oxymatrine, kaempferol, and dioscin) and compound prescriptions(Quxie Capsules, Jiedu Sangen Decoction, and Xianlian Jiedu Prescription) of TCM treat CRC by intervening in the AEG pathway. Additionally, this article explores the shortcomings in the current research, aiming to provide reliable targets and a theoretical basis for treating CRC with TCM.
Humans ; Colorectal Neoplasms/genetics* ; Drugs, Chinese Herbal/therapeutic use* ; Glycolysis/drug effects* ; Animals ; Medicine, Chinese Traditional ; Signal Transduction/drug effects*

Prostate cancer(PCa) is a common malignant tumor among elderly men, with high incidence and mortality rates worldwide, posing a serious threat to human health. Traditional treatments face limitations, highlighting the urgent need for novel therapeutic strategies. Recent studies on the regulatory mechanisms of micro ribonucleic acid(microRNA, miRNA) in tumor development has identified miRNA as new targets for PCa diagnosis and treatment. Traditional Chinese medicine(TCM), with its multi-mechanism, multi-target, and multi-pathway regulatory properties, shows promising potential in miRNA-based PCa therapy. This review summarized recent findings on miRNA' roles in PCa and research progress of TCM intervention and found that a variety of miRNA played important regulatory roles in cell differentiation, proliferation, apoptosis, invasion, metastasis, immune microenvironment, and drug resistance, and their potential as biomarkers for PCa diagnosis, prognosis, and therapy, indicating the potential to be a biomarker for the diagnosis, prognosis evaluation, and treatment of PCa. The review concluded that the active components of TCM(terpenoids, flavonoids, alkaloids, and others) and compounds(Yishen Tonglong Decoction, Shenhu Decoction, Zhoushi Qiling Decoction, Fuzheng Yiliu Decoction, and Qilan Formula) could regulate the expression of their downstream target genes by acting on specific miRNA and affect the above biological behaviors of PCa cells, thus playing a role in the treatment of PCa. This review aims to provide a theoretical basis for miRNA as potential biomarkers and therapeutic targets for PCa and suggest new avenues for further development of targeted therapy strategies against miRNA.
Humans ; MicroRNAs/metabolism* ; Prostatic Neoplasms/metabolism* ; Male ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Animals ; Gene Expression Regulation, Neoplastic/drug effects*

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype

Objective: To investigate the environmental contamination of norovirus in nurseries and primary/secondary schools, so as to provide a scientific basis for effective prevention and control measures. Methods: A total of 483 external environmental samples were collected from 34 cluster outbreaks of norovirus gastroenteritis in kindergartens and primary/secondary schools in Linhai City from 2021 to 2024. Pathogen detection was conducted using a rapid nucleic acid extraction kit and realtime fluorescence RT-PCR, and the results were analyzed using the χ2 test or Fishers exact test. Results: Among the collected external environmental samples, the total positive rate of surface contamination was 13.66%. The positive rates in kindergartens and primary/secondary schools were 12.20% and 15.82%, respectively. In kindergartens, the five surfaces with the highest detection rates were desks/chairs (23.33%), toilet stool troughs (20.69%), urinal troughs (12.00%), washbasins/sinks (11.11%), and toilet mops (9.38%). In primary/secondary schools, the top five were toilet stool troughs (38.30%), urinal troughs (23.53%), toilet door handles (13.04%), toilet mops (12.50%), and drinking cups (11.11%). The difference in positive detection rates among different external environments in primary/secondary schools was statistically significant (Fishers exact probability test, P<0.01). The positive detection rate in sanitary toilets was higher than that in classroom environments (χ2=17.38), while the positive detection rate in classroom environments of kindergartens was higher than that in primary/secondary schools (χ2=5.42)(P<0.05). Conclusions Norovirus exhibits a high contamination rate in nurseries and schools, particularly in restroom areas. Strengthening sanitation and disinfection in highrisk environments, and improving hygiene awareness among children and staff, are essential for the effective prevent and control of norovirus.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

This study was analyzed the spatial-temporal distribution and aggregation characteristics of Yersinia pestispositive host animals and vector pathogens in marmot natural foci in the Qilian-Altun mountains,Gansu Province,to provide a scientific basis for precise plague prevention and control.Y.pestissurveillance data for marmot natural foci in Qilian-Altun Mountains of Gansu Province from 2014 to 2023 were obtained from the Disease Control and Prevention Center of Gansu Province.Origin 2024 software was used for data visualization and presentation.Global and local spatial autocorrelation analyses and trend analyses were conducted in ArcGIS 10.8 software,with townships as the spatial scale.Cumulatively,440 strains of Y.pestis were isolated from the natural marmot foci in the Qilian-Altun mountainsof Gansu Province from 2014 to 2023.Most strains was isolated from marmots(345 strains,78.41%),and the remainder were isolated from vectors.Temporal distribution analysis indicated that the highest number of detected bacteria was reported in July and August(both 121 strains,27.50%).Regional distribution analysis revealed that Aksai County reported the highest number of detected bacteria(255 strains,57.95%).Global spatial autocorrelation analysis showed a spatially clustered distribution of the number of bacteria detected annually in the townships containing natural foci,except in2014,2016,and 2021-2023.The strongest spatial clustering was observed in 2020(Moran's I=0.521 2,Z=14.397 0,P<0.001).Local spatial autocorrelation analysis indicated a"high-high"aggregation area in the natural foci every year from 2014 to 2023,primarily in Hongliuwan Town of Aksai County and Dangchengwan Town of Subei County.The distribution of the"low-low"aggregation area was essentially consistent with the low activity area of the Yersinia pestisepidemic.The trend in annual total bacterial count gradually increased from east to west,and peaked in the western part of the epidemic focus.Clear spatial aggregation characteristics of the number of Y.pestis were detected in the marmot natural foci in the Qilian-Altun mountains at the townshiplevel as a whole in Gansu Province from 2014 to 2023.The aggregation area was mainly in the western section of Qilian Mountain to the Altun mountain section of the epidemic source area.Monitoring and prevention and control efforts should be focused in this key area,with prevention and control measures tailored to the local conditions,and classified guidance to decrease the risk of plague occurrence and spread.