A Cocktail of Polyherbal Bioactive Compounds and Regular Mobility Training as Senolytic Approaches in Age-dependent Alzheimer's: the In Silico Analysis, Lifestyle Intervention in Old Age

Alzheimer's is a principal concern globally. Machine learning is a valuable tool to determine protective and diagnostic approaches for the elderly. We analyzed microarray datasets of Alzheimer's cases based on artificial intelligence by R statistical software. This study provided a screened pool of ncRNAs and coding RNAs related to Alzheimer's development. We designed hub genes as cut points in networks and predicted potential microRNAs and LncRNA to regulate protein networks in aging and Alzheimer's through in silico algorithms. Notably, we collected effective traditional herbal medicines. A list of bioactive compounds prepared including capsaicin, piperine, crocetin, safranal, saffron oil, coumarin, thujone, rosmarinic acid, sabinene, thymoquinone, ascorbic acid, vitamin E, cyanidin, rhaponticin, isovitexin, coumarin, nobiletin, evodiamine, gingerol, curcumin, quercetin, fisetin, and allicin as an effective fusion that potentially modulates hub proteins and molecular signaling pathways based on pharmacophore model screening and chemoinformatics survey. We identified profiles of 21 mRNAs, 272 microRNAs, and eight LncRNA in Alzheimer's based on prediction algorithms. We suggested a fusion of senolytic herbal ligands as an alternative therapy and preventive formulation in dementia. Also, we provided ncRNAs expression status as novel monitoring strategies in Alzheimer's and new cut-point proteins as novel therapeutic approaches. Synchronizing fusion drugs and lifestyle could reverse Alzheimer's hallmarks to amelioration via an offset of the signaling pathways, leading to increased life quality in the elderly.

Automated summary

Alzheimer's disease is a global concern, and this study used machine learning and artificial intelligence to analyze microarray datasets to identify ncRNAs and coding RNAs linked to its development. By designing hub genes and predicting microRNAs and LncRNA, potential protein networks and signaling pathways in aging and Alzheimer's were identified. Traditional herbal medicines and bioactive compounds were also investigated for their effects on hub proteins. The study suggests a fusion of senolytic herbal ligands as an alternative therapy for dementia and provides new insights into monitoring strategies and therapeutic approaches for Alzheimer's.