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  1. Abu Bakar AR, Manaharan T, Merican AF, Mohamad SB
    Nat Prod Res, 2018 Feb;32(4):473-476.
    PMID: 28391727 DOI: 10.1080/14786419.2017.1312393
    Ficus deltoidea leaves extract are known to have good therapeutic properties such as antioxidant, anti-inflammatory and anti-diabetic. We showed that 50% ethanol-water extract of F. deltoidea leaves and its pungent compounds vitexin and isovitexin exhibited significant (p 
  2. Abu Bakar AR, Lai KW, Hamzaid NA
    Neurosci Lett, 2021 11 20;765:136250.
    PMID: 34536511 DOI: 10.1016/j.neulet.2021.136250
    Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (EEG). The electrophysiological behaviour response emanated from EEG auditory evoked potential (AEP) requires highly trained professionals for analysis and interpretation. Reliable automated methods using techniques of machine learning would assist the auditory assessment process for informed treatment and practice. It is thus highly required to develop models that are more efficient and precise by considering the characteristics of brain signals. This study aims to provide a comprehensive review of several state-of-the-art techniques of machine learning that adopt EEG evoked response for the auditory assessment within the last 13 years. Out of 161 initially screened articles, 11 were retained for synthesis. The outcome of the review presented that the Support Vector Machine (SVM) classifier outperformed with over 80% accuracy metric and was recognized as the best suited model within the field of auditory research. This paper discussed the comprehensive iterative properties of the proposed computed algorithms and the feasible future direction in hearing impaired rehabilitation.
  3. Abu Bakar AR, Ripen AM, Merican AF, Mohamad SB
    Nat Prod Res, 2019 Jun;33(12):1765-1768.
    PMID: 29394875 DOI: 10.1080/14786419.2018.1434631
    Dysregulation of matrix metalloproteinases (MMPs) activity is known in many pathological conditions with which most of the conditions are related to elevate MMPs activities. Ficus deltoidea (FD) is a plant known for its therapeutic properties. In order to evaluate the therapeutic potential of FD leaf extract, we study the enzymatic inhibition properties of FD leaf extract and its major bioactive compounds (vitexin and isovitexin) on a panel of MMPs (MMP-2, MMP-8 and MMP-9) using experimental and computational approaches. FD leaf extract and its major bioactive compounds showed pronounced inhibition activity towards the MMPs tested. Computational docking analysis revealed that vitexin and isovitexin bind to the active site of the three tested MMPs. We also evaluated the cytotoxicity and cell migration inhibition activity of FD leaf extract in the endothelial EA.hy 926 cell line. Conclusively, this study provided additional information on the potential of FD leaf extract for therapeutical application.
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