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Several disease-modulatory FDA-approved drugs are being used in patients with neurodegenerative diseases. However, information on their toxicity-related profiles is very limited. Therefore, measurement of drug toxicity is essential to increase the knowledge of their side effects. This study aimed to identify compounds that can modulate M-cell regeneration by causing neuro-protection and -toxicity. Here, we developed a simple and efficient in vivo assay using Tg (hsp: Gal4FF62A; UAS: nfsB-mCherry) transgenic zebrafish larvae. Interestingly, via the phenotype-based drug screening approach, we rapidly investigated 1,260 compounds from the United States drug collection and validated these in large numbers, including 14 compounds, that were obstructing this regeneration process. Next, 4 FDA-approved drugs out of 14 compounds were selected as the lead hits for in silico analysis to clarify their binding patterns with PTEN and SOCS3 signaling due to their significant potential in the inhibition of axon regeneration. Molecular docking studies indicated good binding affinity of all 4 drugs with the respective signaling molecules. This may point to PTEN and SOCS3 as the signaling molecules responsible for reducing axon regeneration. Moreover, the acute effect of compounds in reducing M-cell regeneration delineated their toxic effect. In conclusion, our in vivo along with in silico screening strategy will promote the rapid translation of new therapeutics to improve knowledge of the toxicity profile of approved/non-approved drugs efficiently.

Pathogenic aging is regarded as asymptomatic AD when there is no cognitive deficit except for neuropathology consistent with Alzheimer's disease. These individuals are highly susceptible to developing AD. Braak and Braak's theory specific to tau pathology illustrates that the brain's temporal cortex region is an initiation site for early AD progression. So, the hub gene analysis of this region may reveal early altered biological cascades that may be helpful to alleviate AD in an early stage. Meanwhile, cognitive processing also drags its attention because cognitive impairment is the ultimate result of AD. Therefore, this study aimed to explore changes in gene expression of aged control, asymptomatic AD (AsymAD), and symptomatic AD (symAD) in the temporal cortex region. We used microarray data sets to identify differentially expressed genes (DEGs) with the help of the R programming interface. Further, we constructed the protein-protein interaction (PPI) network by performing the STRING plugin in Cytoscape and determined the hub genes via the CytoHubba plugin. Furthermore, we conducted Gene Ontology (GO) enrichment analysis via Bioconductor's cluster profile package. Resultant, the AsymAD transcriptome revealed the early-stage changes of glutamatergic hyperexcitability. Whereas the connectivity of major hub genes in this network indicates a shift from initially reduced rRNA biosynthesis in the AsymAD group to impaired protein synthesis in the symAD group. Both share the phenomenon of breaking tight junctions and others. In conclusion, this study offers new understandings of the early biological vicissitudes that occur in the brain before the manifestation of symAD and gives new promising therapeutic targets for early AD intervention.

Pathogenic aging is regarded as asymptomatic AD when there is no cognitive deficit except for neuropathology consistent with Alzheimer's disease. These individuals are highly susceptible to developing AD. Braak and Braak's theory specific to tau pathology illustrates that the brain's temporal cortex region is an initiation site for early AD progression. So, the hub gene analysis of this region may reveal early altered biological cascades that may be helpful to alleviate AD in an early stage. Meanwhile, cognitive processing also drags its attention because cognitive impairment is the ultimate result of AD. Therefore, this study aimed to explore changes in gene expression of aged control, asymptomatic AD (AsymAD), and symptomatic AD (symAD) in the temporal cortex region. We used microarray data sets to identify differentially expressed genes (DEGs) with the help of the R programming interface. Further, we constructed the protein-protein interaction (PPI) network by performing the STRING plugin in Cytoscape and determined the hub genes via the CytoHubba plugin. Furthermore, we conducted Gene Ontology (GO) enrichment analysis via Bioconductor's cluster profile package. Resultant, the AsymAD transcriptome revealed the early-stage changes of glutamatergic hyperexcitability. Whereas the connectivity of major hub genes in this network indicates a shift from initially reduced rRNA biosynthesis in the AsymAD group to impaired protein synthesis in the symAD group. Both share the phenomenon of breaking tight junctions and others. In conclusion, this study offers new understandings of the early biological vicissitudes that occur in the brain before the manifestation of symAD and gives new promising therapeutic targets for early AD intervention. [ABSTRACT FROM AUTHOR]