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  1. Ahmad R, Sahidin I, Taher M, Low C, Noor NM, Sillapachaiyaporn C, et al.
    Sci Rep, 2018 03 09;8(1):4202.
    PMID: 29523802 DOI: 10.1038/s41598-018-22485-5
    Polygonumins A, a new compound, was isolated from the stem of Polygonum minus. Based on NMR results, the compound's structure is identical to that of vanicoside A, comprising four phenylpropanoid ester units and a sucrose unit. The structure differences were located at C-3″″'. The cytotoxic activity of polygonumins A was evaluated on several cancer cell lines by a cell viability assay using tetrazolium dye 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The compound showed the highest antiproliferative (p 
  2. Klionsky DJ, Abdel-Aziz AK, Abdelfatah S, Abdellatif M, Abdoli A, Abel S, et al.
    Autophagy, 2021 Jan;17(1):1-382.
    PMID: 33634751 DOI: 10.1080/15548627.2020.1797280
    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
  3. Klionsky DJ, Abdelmohsen K, Abe A, Abedin MJ, Abeliovich H, Acevedo Arozena A, et al.
    Autophagy, 2016;12(1):1-222.
    PMID: 26799652 DOI: 10.1080/15548627.2015.1100356
  4. Pichitpunpong C, Thongkorn S, Kanlayaprasit S, Yuwattana W, Plaingam W, Sangsuthum S, et al.
    PLoS One, 2019;14(3):e0214198.
    PMID: 30921354 DOI: 10.1371/journal.pone.0214198
    BACKGROUND: The mechanisms underlying autism spectrum disorder (ASD) remain unclear, and clinical biomarkers are not yet available for ASD. Differences in dysregulated proteins in ASD have shown little reproducibility, which is partly due to ASD heterogeneity. Recent studies have demonstrated that subgrouping ASD cases based on clinical phenotypes is useful for identifying candidate genes that are dysregulated in ASD subgroups. However, this strategy has not been employed in proteome profiling analyses to identify ASD biomarker proteins for specific subgroups.

    METHODS: We therefore conducted a cluster analysis of the Autism Diagnostic Interview-Revised (ADI-R) scores from 85 individuals with ASD to predict subgroups and subsequently identified dysregulated genes by reanalyzing the transcriptome profiles of individuals with ASD and unaffected individuals. Proteome profiling of lymphoblastoid cell lines from these individuals was performed via 2D-gel electrophoresis, and then mass spectrometry. Disrupted proteins were identified and compared to the dysregulated transcripts and reported dysregulated proteins from previous proteome studies. Biological functions were predicted using the Ingenuity Pathway Analysis (IPA) program. Selected proteins were also analyzed by Western blotting.

    RESULTS: The cluster analysis of ADI-R data revealed four ASD subgroups, including ASD with severe language impairment, and transcriptome profiling identified dysregulated genes in each subgroup. Screening via proteome analysis revealed 82 altered proteins in the ASD subgroup with severe language impairment. Eighteen of these proteins were further identified by nano-LC-MS/MS. Among these proteins, fourteen were predicted by IPA to be associated with neurological functions and inflammation. Among these proteins, diazepam-binding inhibitor (DBI) protein was confirmed by Western blot analysis to be expressed at significantly decreased levels in the ASD subgroup with severe language impairment, and the DBI expression levels were correlated with the scores of several ADI-R items.

    CONCLUSIONS: By subgrouping individuals with ASD based on clinical phenotypes, and then performing an integrated transcriptome-proteome analysis, we identified DBI as a novel candidate protein for ASD with severe language impairment. The mechanisms of this protein and its potential use as an ASD biomarker warrant further study.

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