Displaying all 8 publications

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  1. M. Hafiz, C.M.Salmi, M.Kamarol, M.Mariatti
    MyJurnal
    Nowadays Silicone Rubber (SiR) is recommended in high voltage cable accessories fabrication as it offers excellent electrical and mechanical properties. Electrical tree is one of the phenomenon which contributes to the main factor of SiR insulation breakdown. Recently, a new approach has been applied in order to enhance the insulation strength properties by introducing nano filler in undoped material. Thus, this paper presents the influence of nano-alumina and halloysite nanoclay on electrical tree growth in SiR at 0, 1 vol%, 2 vol% and 3 vol% concentration. The electrical tree growth was investigated at 8kVrms after tree inception voltage (TIV) within 30 minutes under room temperature. The results show reductions of electrical tree growth speed and accumulate damage (%) up to 2 vol% nano-alumina and up to 3 vol% halloysite nanoclay. Nevertheless the presence of 3 vol% nano-alumina in SiR leads to the faster electrical tree growth rate and the worst accumulate damage within 1 minute of electrical tree growth process.
  2. M. Hafiz Fazren Abd Rahman, Wan Wardatul Amani Wan Salim, M. Firdaus Abd-Wahab
    MyJurnal
    The steep rise of cases pertaining to Diabetes Mellitus (DM) condition among global population has encouraged extensive researches on DM, which led to exhaustive accumulation of data related to DM. In this case, data mining and machine learning applications prove to be a powerful tool in transforming data into meaningful deductions. Several machine learning tools have shown great promise in diabetes classification. However, challenges remain in obtaining an accurate model suitable for real world application. Most disease risk-prediction modelling are found to be specific to a local population. Moreover, real-world data are likely to be complex, incomplete and unorganized, thus, convoluting efforts to develop models around it. This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using three different machine learning algorithms; Decision Tree, Support Vector Machine and Naïve Bayes. Data pre-processing methods are utilised to the raw data to improve model performance. This study uses datasets obtained from the IIUM Medical Centre for classification and modelling. Ultimately, the performance of each model is validated, evaluated and compared based on several statistical metrics that measures accuracy, precision, sensitivity and efficiency. This study shows that the random forest model provides the best overall prediction performance in terms of accuracy (0.87), sensitivity (0.9), specificity (0.8), precision (0.9), F1-score (0.9) and AUC value (0.93) (Normal).
  3. Aznin Baharudin, Nor Akmalazura Jani, Azyati Azreen, A. A. Assyura, Hawa Pornomo, M. Hafiz Mehat
    Borneo Akademika, 2020;4(1):1-12.
    MyJurnal
    This study is focused on formulating a natural-based fabric softener using baking
    soda and vinegar with the addition of insect repellent finish of citronella oil and
    vanillin. The effectiveness of the fabric softener was evaluated by conducting a fabric
    stiffness test on both untreated and treated fabric samples with the softener
    formulated in this study. The assessment for the efficacy of insect repellence was
    carried out using 3 human participants of the same gender and build but different
    blood type, positioned at a mosquito infested area. Three tests; negative, positive, and
    normal tests were conducted to evaluate the effectiveness of the formulated mosquito
    repellent finishes in the fabric softener. The results show that the formulated fabric
    softener is good mosquito repellent and it is good at giving a soft effect on the treated
    fabric.
  4. Che-Othman MH, Jacoby RP, Millar AH, Taylor NL
    New Phytol, 2020 02;225(3):1166-1180.
    PMID: 30688365 DOI: 10.1111/nph.15713
    Mitochondrial respiration and tricarboxylic acid (TCA) cycle activity are required during salt stress in plants to provide ATP and reductants for adaptive processes such as ion exclusion, compatible solute synthesis and reactive oxygen species (ROS) detoxification. However, there is a poor mechanistic understanding of how salinity affects mitochondrial metabolism, particularly respiratory substrate source. To determine the mechanism of respiratory changes under salt stress in wheat leaves, we conducted an integrated analysis of metabolite content, respiratory rate and targeted protein abundance measurements. Also, we investigated the direct effect of salt on mitochondrial enzyme activities. Salt-treated wheat leaves exhibit higher respiration rate and extensive metabolite changes. The activity of the TCA cycle enzymes pyruvate dehydrogenase complex and the 2-oxoglutarate dehydrogenase complex were shown to be directly salt-sensitive. Multiple lines of evidence showed that the γ-aminobutyric acid (GABA) shunt was activated under salt treatment. During salt exposure, key metabolic enzymes required for the cyclic operation of the TCA cycle are physiochemically inhibited by salt. This inhibition is overcome by increased GABA shunt activity, which provides an alternative carbon source for mitochondria that bypasses salt-sensitive enzymes, to facilitate the increased respiration of wheat leaves.
  5. Che-Othman MH, Millar AH, Taylor NL
    Plant Cell Environ, 2017 Dec;40(12):2875-2905.
    PMID: 28741669 DOI: 10.1111/pce.13034
    Salinity exerts a severe detrimental effect on crop yields globally. Growth of plants in saline soils results in physiological stress, which disrupts the essential biochemical processes of respiration, photosynthesis, and transpiration. Understanding the molecular responses of plants exposed to salinity stress can inform future strategies to reduce agricultural losses due to salinity; however, it is imperative that signalling and functional response processes are connected to tailor these strategies. Previous research has revealed the important role that plant mitochondria play in the salinity response of plants. Review of this literature shows that 2 biochemical processes required for respiratory function are affected under salinity stress: the tricarboxylic acid cycle and the transport of metabolites across the inner mitochondrial membrane. However, the mechanisms by which components of these processes are affected or react to salinity stress are still far from understood. Here, we examine recent findings on the signal transduction pathways that lead to adaptive responses of plants to salinity and discuss how they can be involved in and be affected by modulation of the machinery of energy metabolism with attention to the role of the tricarboxylic acid cycle enzymes and mitochondrial membrane transporters in this process.
  6. Othman SMIS, Mustaffa AF, Che-Othman MH, Samad AFA, Goh HH, Zainal Z, et al.
    Plants (Basel), 2023 Feb 03;12(3).
    PMID: 36771753 DOI: 10.3390/plants12030669
    The application of miRNA mimic technology for silencing mature miRNA began in 2007. This technique originated from the discovery of the INDUCED BY PHOSPHATE STARVATION 1 (IPS1) gene, which was found to be a competitive mimic that prevents the cleavage of the targeted mRNA by miRNA inhibition at the post-transcriptional level. To date, various studies have been conducted to understand the molecular mimic mechanism and to improve the efficiency of this technology. As a result, several mimic tools have been developed: target mimicry (TM), short tandem target mimic (STTM), and molecular sponges (SPs). STTM is the most-developed tool due to its stability and effectiveness in decoying miRNA. This review discusses the application of STTM technology on the loss-of-function studies of miRNA and members from diverse plant species. A modified STTM approach for studying the function of miRNA with spatial-temporal expression under the control of specific promoters is further explored. STTM technology will enhance our understanding of the miRNA activity in plant-tissue-specific development and stress responses for applications in improving plant traits via miRNA regulation.
  7. Othman SMIS, Mustaffa AF, Mohd Zahid NII, Che-Othman MH, Samad AFA, Goh HH, et al.
    Plant Physiol Biochem, 2024 Feb;207:108387.
    PMID: 38266565 DOI: 10.1016/j.plaphy.2024.108387
    Plants have developed diverse physical and chemical defence mechanisms to ensure their continued growth and well-being in challenging environments. Plants also have evolved intricate molecular mechanisms to regulate their responses to biotic stress. Non-coding RNA (ncRNA) plays a crucial role in this process that affects the expression or suppression of target transcripts. While there have been numerous reviews on the role of molecules in plant biotic stress, few of them specifically focus on how plant ncRNAs enhance resistance through various mechanisms against different pathogens. In this context, we explored the role of ncRNA in exhibiting responses to biotic stress endogenously as well as cross-kingdom regulation of transcript expression. Furthermore, we address the interplay between ncRNAs, which can act as suppressors, precursors, or regulators of other ncRNAs. We also delve into the regulation of ncRNAs in response to attacks from different organisms, such as bacteria, viruses, fungi, nematodes, oomycetes, and insects. Interestingly, we observed that diverse microorganisms interact with distinct ncRNAs. This intricacy leads us to conclude that each ncRNA serves a specific function in response to individual biotic stimuli. This deeper understanding of the molecular mechanisms involving ncRNAs in response to biotic stresses enhances our knowledge and provides valuable insights for future research in the field of ncRNA, ultimately leading to improvements in plant traits.
  8. Jikal M, Mori D, Yusoff AF, Rai SB, Mukhsam MH, Ali I, et al.
    Am J Trop Med Hyg, 2021 07 12;105(3):777-782.
    PMID: 34255740 DOI: 10.4269/ajtmh.21-0036
    Foodborne outbreaks of hepatitis A virus (HAV) are most commonly associated with fresh and frozen produce and with various types of shellfish. Alcoholic beverage-borne outbreaks of hepatitis A are extremely rare. Here, we report an outbreak of hepatitis A associated with the consumption of a traditional wine at a funeral ceremony in the Sabah state of Malaysian Borneo. Confirmed cases were determined by serum anti-HAV immunoglobulin M and/or for fecal HAV by reverse transcription polymerase chain reaction (RT-PCR). The amplicons of RT-PCR were subjected to nucleotide sequencing followed by phylogenetic analysis. We conducted a 1:2 case-control study to identify the possible exposure that led to the outbreak. Sixteen patients met the case definition, they were 18 to 58 years old and 90% of them were males. The case-control study showed that the consumption of nipa palm wine during the ceremony was significantly associated (P = 0.0017) with hepatitis A infection (odds ratio, 5.44; 95% CI, 1.80-16.43). Untreated river water was used to dilute the traditional wine, which was assumed to be the source of the infection. Phylogenetically, these viruses belonged to genotype IA and formed an independent cluster with strains from Taiwan, Japan, and the Philippines. This strain might be an emerging HAV in Asian countries. Environmental assessments were performed and environmental samples were negative for HAV. The incidence of hepatitis A in Sabah was also determined and it was 0.795/100,000 population. Strict monitoring of traditional wine production should be implemented by the local authority to prevent future outbreaks.
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