Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, making accurate and objective diagnosis challenging when relying solely on clinical assessments. Therefore, there is an urgent need to develop reliable and objective auxiliary diagnostic models to provide effective diagnosis for PTSD patients. Currently, the application of graph neural networks for representing PTSD is limited by the expressiveness of existing models, which does not yield optimal classification results. To address this, we proposed a multi-graph multi-kernel graph convolutional network (MK-GCN) model for classifying PTSD data. First, we constructed functional connectivity matrices at different scales for the same subjects using different atlases, followed by employing the k-nearest neighbors algorithm to build the graphs. Second, we introduced the MK-GCN methodology to enhance the feature extraction capability of brain structures at different scales for the same subjects. Finally, we classified the extracted features from multiple scales and utilized graph class activation mapping to identify the top 10 brain regions contributing to classification. Experimental results on seismic-induced PTSD data demonstrated that our model achieved an accuracy of 84.75%, a specificity of 84.02%, and an AUC of 85% in the classification task distinguishing between PTSD patients and non-affected subjects. The findings provide robust evidence for the auxiliary diagnosis of PTSD following earthquakes and hold promise for reliably identifying specific brain regions in other PTSD diagnostic contexts, offering valuable references for clinicians.
Humans ; Stress Disorders, Post-Traumatic/diagnostic imaging* ; Neural Networks, Computer ; Algorithms ; Brain/diagnostic imaging* ; Magnetic Resonance Imaging

OBJECTIVES: This study evaluated the association between obesity and glaucoma in middle-aged and older people. A population-based retrospective cohort study was conducted using data from the China Health and Retirement Longitudinal Study. METHODS: Glaucoma was assessed via self-reports. Multivariate logistic regression analysis and a Cox proportional hazards model were used to assess the relationship between obesity and glaucoma risk. RESULTS: Older males living in urban areas who were single, smokers, and non-drinkers were found to have a significantly higher incidence of glaucoma (all p<0.05). Diabetes, hypertension, and kidney disease were also associated with higher glaucoma risk, while dyslipidemia was associated with lower risk (all p<0.05). After the model was adjusted for demographic, socioeconomic, and health-related variables, obesity was significantly associated with a 10.2% decrease in glaucoma risk according to the Cox proportional hazards model (hazard ratio, 0.90; 95% confidence interval [CI], 0.83 to 0.97) and an 11.8% risk reduction in the multivariate logistic regression analysis (odds ratio, 0.88; 95% CI, 0.80 to 0.97). A further subgroup analysis showed that obesity was associated with a reduced risk of glaucoma in people living in rural areas, in smokers, and in those with kidney disease (all p<0.05). Obesity also reduced glaucoma risk in people with diabetes, hypertension, or dyslipidemia more than in healthy controls (all p<0.05). CONCLUSIONS This cohort study suggests that obesity was associated with a reduced risk of glaucoma, especially in rural residents, smokers, and people with kidney disease. Obesity exerted a stronger protective effect in people with diabetes, hypertension, or dyslipidemia than in healthy people.

Transoral incisionless fundoplication (TIF)has been used for the treatment of gastroesophageal reflux disease (GERD)via repairing the gastroesophageal junction valve. Both the clinical report and control study confirmed that,with the prerequisite of rational selection of patients,TIF as an emerging technology can effectively cure or improve the clinical symptoms of GERD,esophagitis,and level of esophageal acid exposure. Compared with the traditional treatment,TIF is more effective,safe and having lasting effect for the rationally selected GERD patients. This article reviewed advances in study on TIF for the treatment of GERD.

Objective To analyze the clinical, imaging characteristics and NOTCH3 mutations of cerebral autosomal dominant arteriopathy with the subcortical infarcts and leukoencephalopathy (CADASIL) in Henan, China.Methods CADASIL patients diagnosed by gene or biopsy in People′s Hospital of Zhengzhou University between 2012-2016 were recruited.Clinical and imaging features of these patients were analyzed retrospectively.The distribution of NOTCH3 gene mutations hotspots was described in Henan region at the same time.Results There were 37 patients from 19 families who were diagnosed as CADASIL by genetic testing or biopsy, 27 of whom had symptoms of CADASIL.Two families were confirmed by pathological examination and 17 by genetic testing.Of these 17 families, 13 mutations were found.Mutations in exon 11 were found in eight families, in exon 4 were detected in four families, and in exon 13 were found in two families.Mutation in exons 3, 8 and 20 was detected in one family respectively.Most patients presented with stroke and several presented with cognitive decline.Twelve patients had been attacked by risk factors.Magnetic resonance imaging (MRI) was performed on 22 patients.White-matter lesions were distributed in brain stem, basal ganglia, subcortical, temporal pole, external capsule.There were 19 patients with white-matter lesions in temporal pole and seven in capsula externa, showed as a high signal in T2WI.Conclusions CADASIL patients can be associated with risk factors.T2WI hyperintensities in the anterior temporal lobe were more common than that in the capsular external.Exon 11 and exon 4 were the hotspots for the NOTCH3 mutation in Henan patients.