Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Endothelial dysfunction is a key factor linking obstructive sleep apnea hypopnea syndrome (OSAHS) with cardiovascular diseases. In this study, we used advanced proteomics and metabolomics approaches to investigate the impact of extracellular vesicles (EVs) derived from the serum of OSAHS patients on endothelial function. Our multi-omics analysis identified dysregulated pathways related to fatty acid metabolism, apoptosis regulation, and inflammatory responses, highlighting fatty acid synthase (FASN) as a crucial player in OSAHS-induced endothelial dysfunction. Both in vitro and in vivo experiments demonstrated that FASN-enriched EVs impair endothelial cell viability and disrupt metabolic homeostasis, offering new insights for the development of targeted therapies for cardiovascular complications associated with OSAHS.

Objective To explore the probability and associated factors of pulmonary fibrosis in 350 cases of elderly pneumonia. Methods Elderly patients who received diagnosis and treatment at Changzhi Medical College Affiliated Peace Hospital from January 2018 to December 2022 were selected, and 350 patients who met the criteria were included in the study. Analyze its clinical data, incidence of pulmonary fibrosis, and analyze the relationship between the two. Results The average age of 350 patients was (63.51 ± 5.74) years old; 219 cases were common type , 72 cases were severe type, and 59 cases were critically ill. At admission, the CT signs were: ground glass in 66 cases (18.86%) , paving stone in 37 cases (10.57%), consolidation in 73 cases (20.86%), nodules in 93 cases (26.57%) , fried egg sign in 20 cases (5.71%) , and mosaic sign in 61 cases (17.43%). At discharge, the lesion signs were as follows: 61 cases (17.43%) had no lesions, 207 cases (59.14%) maintained the original lesion signs, and 82 cases (23.43%) evolved into other signs. 76 cases of pulmonary fibrosis were discharged, with an incidence rate of 21.71%. There were significant differences in the incidence of pulmonary fibrosis among patients with different ages, lesion evolution during treatment, lesion signs at discharge, and clinical stages (all P<0.001). Pulmonary fibrosis is positively correlated with age (P=0.047), lesion signs at discharge (P=0.032), and clinical classification (P=0.010). The incidence of lesions presenting as paving stones (P=0.014) and fibrosis in critically ill patients (P=0.013) at discharge is higher. Age increase (P=0.047) , wide range of lesions at admission (P=0.042), evolution of lesions into other signs at discharge (P=0.016), and clinical classification as severe (P=0.008) or critically ill (P=0.021) are independent risk factors for the development of pulmonary fibrosis in elderly pneumonia patients. Conclusion The incidence of pulmonary fibrosis in elderly patients exceeds 20%. Increasing age, wide range of lesions upon admission, evolution of lesions into other signs upon discharge, and clinical classification as severe or critically ill are independent risk factors for the occurrence of pulmonary fibrosis in elderly pneumonia patients.

Objective:To explore the risk factors for malnutrition after a tracheotomy and to construct a predictive model useful for its prevention through early intervention.Methods:Clinical data describing 440 tracheotomy patients were subjected to a retrospective analysis. The variables examined were age, sex, etiology, Glasgow Coma Score (GCS), activities of daily living (ADL) score, age-corrected Charlson comorbidity index (aCCI), food intake, swallowing function, incidence of infections, as well as any history of diabetes mellitus, hypertension, smoking or alcohol consumption. Patients identified as being at risk of malnutrition (NRS-2002≥3) were screened using the Nutritional Risk Screening tool (NRS-2002) and the European Society of Clinical Nutrition and Metabolism′s ESPEN2015 criteria. The subjects were thus categorized into a malnutrition group of 343 and a control group of 97. Unifactorial and multifactorial logistic regression analyses were performed, and stepwise regression was applied to include the factors found significant in the unifactorial analysis into the multifactorial logistic regression analysis, and to construct a column-line graph prediction model. The clinical utility of the model was assessed by applying the receiver operator characteristics (ROC) curves, calibration plots and decision curve analysis (DCA).Results:Of the 440 persons studied, 343 (78%) were malnourished. The multivariate logistic regression analysis showed that pulmonary infection, dysphagia, low GCS score and high aCCI score were significant risk factors for malnutrition after a tracheotomy. A prediction nomograph was constructed. After fitting and correcting, the area under the curve (AUC) of the prediction model′s ROC curve was 0.911, the specificity was 80.4%, and the sensitivity was 91.3%. That was significantly higher than the AUCs for pulmonary infection (0.809), dysphagia (0.697), aCCI (0.721) and GCS (0.802). Bootstrap self-sampling was used to verify the model internally. After 1000 samples the average absolute error between the predicted risk and the actual risk was 0.013, indicating good prediction ability. The DCA results demonstrated that the model has substantial clinical applicability across a range of nutritional interventions, particularly for threshold probability values ranging from 0 to 0.96.Conclusion:Pulmonary infection, dysphagia, low GCS score, and high aCCI score are risk factors for malnutrition among tracheotomy patients. The nomogram model constructed in this study has good predictive value for the occurrence of malnutrition among such patients.

Objective:To establish ultra performance liquid chromatography (UPLC) characteristic chromatogram of Pulsatilla chinensis; To provide reference for the origin identification and quality control of Pulsatilla chinensis. Methods:UPLC Method was adopted. The determination was performed on a column of Agilent SB C18 (2.1 mm×100 mm, 1.8 μm) . The mobile phase was acetonitrile-methanol (2:1) -0.1% phosphoric acid solution by fradient elution at a flow rate of 0.30ml/min. The column temperature was 30 ℃. The detection wavelength was 215 nm. The injection volume was 2 μl. The common counterfeit products and medicinal herbs of Pulsatilla chinensis from different areas were evaluated by comparison of characteristic chromatogram, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Results:There were 9 characteristic peaks in the characteristic chromatogram of Pulsatilla chinensis, and 8 common peaks were identified by high resolution mass spectrometry and comparison of reference materials. Through PCA analysis, it was possible to clearly distinguish the medicinal herbs of Pulsatilla chinensis from different areas. Combined with OPLS-DA analysis, it was found that peak 2, peak 3, peak 6 were the main markers of Pulsatilla chinensis from different producing areas. Conclusion:The established method has good specificity, repeatability and durability, and it can effectively distinguish the common counterfeits of Pulsatilla chinensis, and provide the basis of quality control and selection of origin for Pulsatilla chinensis.

Anti-seizure medications (ASMs) are the main therapy for epilepsy.There are many kinds of ASMs with complex mechanism of action, so it is difficult for pharmacists to examine prescriptions.This paper put forward some suggestions on the indications, dosage forms/routes of administration, appropriateness of usage and dosage, combined medication and drug interaction, long-term prescription review, individual differences in pathophysiology of children, and drug selection when complicated with common epilepsy, for the reference of doctors and pharmacists.

The review focused upon the molecular mechanisms underlying ischemia reperfusion injury leading to interstitial fibrosis in transplanted kidneys, the roles of vascular dysfunction, epithelial cells, and pericytes in this process, the construction of different animal experimental models and their effects and recent novel approaches for the prevention and treatment of this process.

Lymphedema is a common complication associated with breast cancer treatment, which has a serious impact on patients' limb function and quality of life. A clear and standardized diagnosis of breast cancer-related lymphedema is important for early identification of lymphedema and timely clinical diagnosis and treatment. Standardized, effective and timely management can reduce the incidence of lymphedema. This article reviews the current common diagnostic tools and methods and management methods, and evaluates their advantages and disadvantages in terms of both diagnosis and early management.