No abstract

No abstract

Background: Naturally-occurring products derived from living organisms have been shown to modulate various pharmacological and biological activities. Natural products protect against various diseases, which could be used for therapeutic assistance. Autophagy, a lysosome-mediated self-digestion pathway, has been implicated in a range of pathophysiological conditions and has recently gained attention for its role in several neurodegenerative diseases. Methods: In this current review, we emphasized the recent progress made in our understanding of the molecular mechanism of autophagy in different cellular and mouse models using naturally-occurring autophagy modulators for the management of several neurodegenerative diseases. Results: Accumulating evidence has revealed that a wide variety of natural compounds such as alkaloids, polyphenols, terpenoids, xanthonoids, flavonoids, lignans, disaccharides, glycolipoproteins, and saponins are involved in the modulation of the autophagy signaling pathway. These natural products have been used to treat various neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Amyotrophic lateral sclerosis, spinocerebellar ataxia, neuroblastoma, and glioblastoma. Although a number of synthetic autophagy regulators have been recognized as encouraging neurodegenerative therapeutic candidates, natural autophagy- regulating compounds have been of further interest as potential disease therapeutics, as they cause insignificant side effects. Conclusion: Existing in vitro and in vivo data are promising and highlight that naturally-occurring autophagyregulating compounds play an important role in the prevention and treatment of neurodegenerative disorders.

Background and objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disease that results in severe dementia. Having ischemic strokes (IS) is one of the risk factors of the AD, but the molecular mechanisms that underlie IS and AD are not well understood. We thus aimed to identify common molecular biomarkers and pathways in IS and AD that can help predict the progression of these diseases and provide clues to important pathological mechanisms. Materials and Methods: We have analyzed the microarray gene expression datasets of IS and AD. To obtain robust results, combinatorial statistical methods were used to analyze the datasets and 26 transcripts (22 unique genes) were identified that were abnormally expressed in both IS and AD. Results: Gene Ontology (GO) and KEGG pathway analyses indicated that these 26 common dysregulated genes identified several altered molecular pathways: Alcoholism, MAPK signaling, glycine metabolism, serine metabolism, and threonine metabolism. Further protein–protein interactions (PPI) analysis revealed pathway hub proteins PDE9A, GNAO1, DUSP16, NTRK2, PGAM2, MAG, and TXLNA. Transcriptional and post-transcriptional components were then identified, and significant transcription factors (SPIB, SMAD3, and SOX2) found. Conclusions: Protein–drug interaction analysis revealed PDE9A has interaction with drugs caffeine, γ-glutamyl glycine, and 3-isobutyl-1-methyl-7H-xanthine. Thus, we identified novel putative links between pathological processes in IS and AD at transcripts levels, and identified possible mechanistic and gene expression links between IS and AD.

M.A.M.). # These two authors have made an equal contribution and hold joint first authorship for this work. (M.A.M.).Abstract: Background and objectives: Alzheimer's disease (AD) is the progressive neurodegenerative disease characterized by dementia, but no peripheral biomarkers available yet that can detect the AD. This study aimed to identify systems biomarker signatures in the AD through integrative analyses. Materials and Methods: We used two microarray transcriptomics datasets of blood from AD patients to identify differentially expressed genes (DEGs).Geneset and protein overrepresentation analysis, protein-protein interaction (PPI), DEGs-Transcription Factor interactions, DEGs-MicroRNAs interactions, protein-drug interactions, and protein subcellular localizations analyses were done on common DEGs. Results: Total 25 DEGs were detected between the two datasets. Integration of DEGs with biomolecular networks revealed hub proteins (TUBB, ATF3, NOL6, UQCRC1, SND1, CASP2, BTF3, INPP5K, VCAM1, and CSTF1), TFs (FOXC1, ZNF3, GEMIN7, and SMG9), miRNAs (mir-20a-5p, mir-93-5p, mir-16-5p, let-7b-5p, mir-708-5p, mir-24-3p, mir-26b-5p, mir-17-5p, mir-4270, and mir-4441). The analyses revealed candidate blood based biomarkers in the AD. We evaluated the histone modifications of the identified biomolecules. The hub genes and transcription factors (TFs) revealed that they possess several histone modification sites associated with Alzheimer's disease. The protein-drug interactions revealed 10 candidate drugs consisting of antineoplastic (Vinorelbine, Vincristine, Vinblastine, Epothilone D, Epothilone B, CYT997, and ZEN-012), dermatologicals (Podofilox), and immunosuppressive agents (Colchicine) that may target the candidate systems biomarkers. The subcellular localization analysis revealed the interactions of the DEGs range from nucleus to plasma membrane through cytosol. Conclusions: This study presents blood based systems molecular biomarker signatures at RNA and protein levels which might be useful as peripheral biomarkers in the AD. The candidate drugs, histone modification sites, and subcellular localizations will be useful in future drug design in the AD.

No abstract

No abstract

No abstract