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1.
Front Neurosci ; 17: 1113578, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37144093

RESUMO

Background: Myopia is one of the major public health problems worldwide. However, the exact pathogenesis of myopia remains unclear. This study proposes using voxel-based morphometry (VBM) to investigate potential morphological alterations in gray matter volume (GMV) in form-deprivation myopia (FDM) rats. Methods: A total of 14 rats with FDM (FDM group) and 15 normal controls (NC group) underwent high-resolution magnetic resonance imaging (MRI). Original T2 brain images were analyzed using VBM method to identify group differences in GMV. Following MRI examination, all rats were perfused with formalin, and immunohistochemical analysis of NeuN and c-fos levels was performed on the visual cortex. Results: In the FDM group, compared to the NC group, significantly decreased GMVs were found in the left primary visual cortex, left secondary visual cortex, right subiculum, right cornu ammonis, right entorhinal cortex and bilateral molecular layer of the cerebellum. Additionally, significantly increased GMVs were found in the right dentate gyrus, parasubiculum, and olfactory bulb. Conclusions: Our study revealed a positive correlation between mGMV and the expression of c-fos and NeuN in the visual cortex, suggesting a molecular relationship between cortical activity and macroscopic measurement of visual cortex structural plasticity. These findings may help elucidate the potential neural pathogenesis of FDM and its relationship to changes in specific brain regions.

2.
Front Cell Infect Microbiol ; 13: 1103471, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-36798084

RESUMO

Background: Fungal keratitis is a common blinding eye disease, and Fusarium is one of the main species that cause fungal keratitis. As is well known, oxidative stress plays an important role in Fusarium keratitis and it is also a significant initiating factor of ferroptosis. But the relationship between Fusarium keratitis and ferroptosis is currently unclear. This study aimed to speculate and validate potential ferroptosis-related genes in Fusarium keratitis using bioinformatics analysis, which provided ideas for further research on its specific mechanism and new targets for its treatment. Methods: The microarray expression profiling dataset (GSE58291) came from Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were obtained by the limma package of the R software. The DEGs were performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Then, the DEGs were intersected with the genes in the ferroptosis database. The top 5 hub genes were obtained by the protein-protein interaction (PPI) network analysis and the cytoHubba plug-in of Cytoscape software. The hub genes were subjected to GSEA analysis. Then we analyzed the immune infiltration of the samples by CIBERSORT and ssGSEA algorithm. Finally, we validated the mRNA of hub genes by qPCR. Results: A total of 1,368 DEGs were identified and 26 ferroptosis-related DEGs were obtained. At the same time, ferroptosis-related pathways were enriched by GO and KEGG using DEGs. HMOX1, CYBB, GPX2, ALOX5 and SRC were obtained by the PPI network analysis and the cytoHubba plug-in of Cytoscape software. The iron metabolism and immune response related pathways were enriched using GSEA. They included hematopoietic cell lineage, lysosome and FC gamma R mediated phagocytosis. T cells follicular helper, monocytes, macrophages and mast cells might play an important role in Fusarium keratitis using analysis of immune infiltration. Finally, qPCR confirmed that the expression of HMOX1, CYBB, ALOX5 mRNA in the DON group was significantly elevated, while the expression of GPX2 were significantly decreased. Conclusions: Ferroptosis may play an important role in Fusarium keratitis. HMOX1, CYBB, ALOX5 and GPX2 may be key ferroptosis-related genes in the pathogenesis of Fusarium keratitis.


Assuntos
Úlcera da Córnea , Infecções Oculares Fúngicas , Ferroptose , Fusarium , Ceratite , Fusarium/genética , Biologia Computacional , Perfilação da Expressão Gênica
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