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

The rich club, as a community of highly interconnected nodes, serves as the topological center of the network. However, the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown. In this study, we first detected and validated the rich club in the structural networks of mouse, monkey, and human brains using neuronal tracing or diffusion magnetic resonance imaging data. Further, we assessed the role of rich clubs in functional integration, segregation, and balance using quantitative metrics. Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species, with the functional networks of higher species exhibiting greater integration. These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.
Animals ; Humans ; Brain/diagnostic imaging* ; Mice ; Male ; Nerve Net/diagnostic imaging* ; Macaca ; Female ; Neural Pathways/diagnostic imaging* ; Magnetic Resonance Imaging ; Biological Evolution ; Adult ; Diffusion Magnetic Resonance Imaging ; Brain Mapping ; Species Specificity ; Mice, Inbred C57BL

Objective To analyze the hot spots,rules and distribution on safety research of inhalation preparations at home and abroad in the past 20 years,and to summarize the current status of safety and risk control research on inhalation preparations.Methods This reaserch is based on the literature related to the safety and risk control of inhalation preparations in the core collection database of the Web of Science.With the help of Excel 2021 and CiteSpace6.1.R3,visualized processing and analysis were carried out on the annual number of publications,countries,institutions,authors,co-occurrence of keywords,clustering and prominence.Results A total of 365 articles were included,the annual publication number in the field of the safety and risk control of inhalation preparations was less than 30 per year from 2002 to 2018.But since 2019,the number of articles published this year has exceeded 30.Through the analysis of the cooperation network of countries and institutions,the top four countries in terms of publication volume are the United States,the United Kingdom,Germany,and China,and the top three institutions are AstraZeneca,GlaxoSmithKline and Pfizer.Through the analysis of the author cooperation network,the cooperation network between European and American authors was formed earlier,and a certain research group has appeared in 2002.In contrast,a more concentrated cooperation network has been formed in China in 2020.Conclusions In the past 20 years,the research on inhalation preparations has mainly focused on their safety and efficacy,while there are few studies on their risk control.There is a disconnect between safety assessment and risk assessment,and the future focus maybe focused on the adverse reaction assessment and risk management research of inhalation preparations.

Biomarkers ; Brain/diagnostic imaging* ; Brain Diseases/diagnostic imaging* ; Humans ; Machine Learning ; Magnetic Resonance Imaging ; Neuroimaging