ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Ferroptosis, a programmed cell death modality discovered and defined in the last decade, is primarily induced by iron-dependent lipid peroxidation. At present, it has been found that ferroptosis is involved in various physiological functions such as immune regulation, growth and development, aging, and tumor suppression. Especially its role in tumor biology has attracted extensive attention and research. Breast cancer is one of the most common female tumors, characterized by high heterogeneity and complex genetic background. Triple negative breast cancer (TNBC) is a special type of breast cancer, which lacks conventional breast cancer treatment targets and is prone to drug resistance to existing chemotherapy drugs and has a low cure rate after progression and metastasis. There is an urgent need to find new targets or develop new drugs. With the increase of studies on promoting ferroptosis in breast cancer, it has gradually attracted attention as a treatment strategy for breast cancer. Some studies have found that certain compounds and natural products can act on TNBC, promote their ferroptosis, inhibit cancer cells proliferation, enhance sensitivity to radiotherapy, and improve resistance to chemotherapy drugs. To promote the study of ferroptosis in TNBC, this article summarized and reviewed the compounds and natural products that induce ferroptosis in TNBC and their mechanisms of action. We started with the exploration of the pathways of ferroptosis, with particular attention to the System X_c^--cystine-GPX4 pathway and iron metabolism. Then, a series of compounds, including sulfasalazine (SAS), metformin, and statins, were described in terms of how they interact with cells to deplete glutathione (GSH), thereby inhibiting the activity of glutathione peroxidase 4 (GPX4) and preventing the production of lipid peroxidases. The disruption of the cellular defense against oxidative stress ultimately results in the death of TNBC cells. We have also our focus to the realm of natural products, exploring the therapeutic potential of traditional Chinese medicine extracts for TNBC. These herbal extracts exhibit multi-target effects and good safety, and have shown promising capabilities in inducing ferroptosis in TNBC cells. We believe that further exploration and characterization of these natural compounds could lead to the development of a new generation of cancer therapeutics. In addition to traditional chemotherapy, we discussed the role of drug delivery systems in enhancing the efficacy and reducing the toxicity of ferroptosis inducers. Nanoparticles such as exosomes and metal-organic frameworks (MOFs) can improve the solubility and bioavailability of these compounds, thereby expanding their therapeutic potential while minimizing systemic side effects. Although preclinical data on ferroptosis inducers are relatively robust, their translation into clinical practice remains in its early stages. We also emphasize the urgent need for more in-depth and comprehensive research to understand the complex mechanisms of ferroptosis in TNBC. This is crucial for the rational design and development of clinical trials, as well as for leveraging ferroptosis to improve patient outcomes. Hoping the above summarize and review could provide references for the research and development of lead compounds for the treatment for TNBC.

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.

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.

For patients with moderate-to-severe functional mitral regurgitation (FMR) who continue to experience heart failure symptoms despite optimized medical and device therapy, transcatheter mitral valve edge-to-edge repair (TEER) is increasingly becoming a reliable treatment option. With the continuous research and development and improvement of TEER-related devices, there are currently dozens of domestically developed TEER devices undergoing clinical trials in China. In this study, we report the first case of a patient with severe FMR treated with the X-Clip® TEER system. The patient, a 60-year-old male, suffered FMR attributed to dilated cardiomyopathy. Preoperative transthoracic echocardiography showed severe mitral regurgitation (4+). He underwent percutaneous repair using the X-Clip® system, and immediate postoperative ultrasound showed mild mitral regurgitation. At the 1-month follow-up, the patient’s symptoms and New York Heart Association (NYHA) functional class improved, and a follow-up transthoracic echocardiogram showed mild mitral regurgitation (1+).

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.

ObjectiveTo investigate the relationship between the non-fasting triglyceride and glucose （TyG） index and hyperglycemia in pregnancy during the third trimester in high altitudes. MethodsThis study selected clinical and laboratory data of 774 Tibetan singleton pregnant women who delivered at Chaya People's Hospital of Qamdo city in Xizang autonomous region， from January 2023 to April 2025. The non-fasting TyG index was calculated from non-fasting triglyceride （TG） and random plasma glucose （PG）. Based on the tertiles of the non-fasting TyG index values， the individuals were split into three groups （corresponding to non-fasting TyG index of 8.89 and 9.21， respectively）. The baseline clinical characteristics， lipid levels and the occurrence of developing hyperglycemia in pregnancy were compared among the three groups. Statistical analyses were performed using ANOVA， Kruskal-Wallis H test， Chi-square test， or Fisher exact test and the relationship between the non-fasting TyG index and hyperglycemia in pregnancy were examined using multivariate logistic regression models and curve fitting. ResultsA total of 774 Tibetan singleton pregnant women were included， with a average age of 27.3 ± 6.1 years， a pre-delivery body mass index （Pre-BMI） of （25.2±2.3）kg/m² ， a proportion of 26.7% （207/774） primigravid women， the mean non-fasting TyG index was 9.1 ± 0.4。Thirty pregnant women were diagnosed with hyperglycemia in pregnancy， with a detection rate of 3.9% （30/774）. Statistically significant differences in serum total cholesterol （TC）， TG， low-density lipoprotein cholesterol （LDL-C） and high-density lipoprotein cholesterol （HDL-C） levels were identified when comparing different non-fasting TyG groups （all P values <0.05）. Subsequent trend test analysis indicated that the levels of TC， TG， LDL-C， and PG gradually increased with elevated the non-fasting TyG index （ F_{trend TC}=95.61， P<0.001； F_{trend TG}=1 051.91， P<0.001； F_{trend LDL-C} = 97.20， P < 0.001； F_{trend TG}=195.20； P<0.001）. After adjustment for maternal age， pre-delivery BMI， altitude， TC， LDL-C， and HDL-C， multivariate Logistic regression models revealed independent positive associations between non-fasting TyG index and hyperglycemia in pregnancy （Model 1： OR=2.72， 95% CI： 1.13-6.53， P=0.026； Model 2： OR=2.56， 95% CI： 1.01-6.50， P=0.048； Model 3： OR=2.72， 95% CI： 1.06-6.97， P=0.037； Model 4： OR=4.02， 95% CI： 1.42-11.40， P=0.009） and the incident of hyperglycemia in pregnancy showed an increasing tendency as increasing with the non-fasting TyG index， however， this association did not statistical significance （P _trend >0.05）. Curve fitting by restricted cubic splines （RCS） were used to assess linearity between non-fasting TyG and hyperglycemia in pregnancy， and there was a linear dose-response relationship between non-fasting TyG and hyperglycemia in pregnancy （P _{for non-linear} = 0.515）. ConclusionNon-fasting TyG index in the third trimester is a risk factor for hyperglycemia in pregnancy among the Tibetan singleton pregnant women at high altitudes and there was a possible linear dose-response relationship between the non-fasting TyG index and hyperglycemia in pregnancy.