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Fulltext Effects of amyloid precursor protein overexpression on nuclear factor kappa beta pathway in neuronal cells

Pan, M. L., Koh, R. Y., Chan, H. H., Leong, C. O.

Malaysian Journal of Medicine and Health Sciences, 2019;15(102):33-33.
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Introduction: The aging process is the most significant risk factor for developing Alzheimer’s disease (AD). AD is the most common neurodegenerative disease that causes cognitive and memory impairment in the elderly. Excessive build-up of amyloid protein leads to cell death, brain atrophy, and cognitive and functional decline in AD. The nuclear factor kappa beta (NF-κB) is a family of inducible transcription factors composed of NF-κB1, NF-κB2, RelA, RelB and c-Rel. It is activated by genotoxic agents, as well as oxidative and inflammatory stresses. It regulates expression of genes that control apoptosis, cell cycle progression, cell senescence, and inflammation. NF-κB regulates amyloid precursor protein (APP) processing by activating transcription of β and γ secretases, which promotes amyloid dysregulation in AD. In addition, NF-κB activation is linked with many of the known lifespan regulators including insulin/IGF- 1, FOXO, SIRT, and mTOR. Therefore, NF-κB pathway contributes to the pathophysiology of AD. This study aims to evaluate the effects of APP overexpression on NF-κB pathway in neuronal cells. Methods: SH-SY5Y neuronal cells were transduced with APP plasmid. Overexpression of APP in the cells was validated by western blotting. Western blot analysis using antibodies targeting NF-κB signalling pathway was performed using the APP-overexpressed cells. Results: Overexpression of APP in cells caused a significant down-regulation of phosphorylated NF-κB. Overexpression of APP also slightly up-regulated IkappaB-alpha, IKK alpha, and IKK beta. Conclusion: APP overexpression affected NF-κB pathway by down-regulating NF-κB protein.
Fulltext Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

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.
Comparing various cut-offs of aspartate aminotransferase-to-platelet ratio index (APRI) in liver cirrhosis diagnosis among hepatitis C patients in Malaysia

Mohd Suan MA, Chan HK, Sem XH, Shilton S, Abu Hassan MR

Med J Malaysia, 2021 Nov;76(6):828-832.
PMID: 34806668

INTRODUCTION: A major challenge in providing hepatitis C virus (HCV) treatment at primary healthcare clinics is the lack of radiological facilities to guide the decision making of liver cirrhosis (LC). This study aimed to compare the performance of three commonly used cut-offs of the aspartate aminotransferase-to-platelet ratio index (APRI) in diagnosing LC among hepatitis C patients in Malaysia.
METHODS: This cross-sectional study was based on the data collected from the Hepatitis C Elimination through Access to Diagnostics (HEAD-Start) study in 25 primary healthcare clinics across three regions of Malaysia. The findings of biochemical tests were used to calculate the APRI for each study participant. Transient elastography was used as a standard reference for the diagnosis of cirrhosis. The area under the receiver operating curve (AUROC) was used to determine the discriminative ability of APRI in both HCV mono-infected and HCV/HIV co-infected patients. The diagnostic performance of APRI at three different cutoffs (>1.0, ≥1.5 and >2.0) were also evaluated.
RESULTS: This study included 867 HCV-RNA-positive patients, 158 (16.1%) were co-infected with HIV. For the HCV mono-infected patients, the sensitivity, specificity, positive predictive value (PPV) and negative predictive values (NPV) for the cut-off of >1.0 were 61.8%, 88.7%, 73.8% and 81.9%, and for the cut-off of ≥1.5, 45.6%, 97.0%, 88.7% and 77.6%, respectively. A much lower sensitivity (29.9%) was observed for the cut-off of >2.0. The diagnostic accuracy of APRI at the cut-off of ≥1.5 in the HCV/HIV co-infected patients was relatively suboptimal.
CONCLUSION: APRI, with a cut-off of ≥1.5, can more accurately predict LC among hepatitis C patients in Malaysia. However, additional physical examination and laboratory assessment are likely to be required to support the diagnosis, especially in those with HCV/HIV co-infection.
Exploring measurement tools to optimise hospital physician distribution

Suan NAM, Soelar SA, Rani RA, Anuar NA, Aziz KAA, Chan HK, et al.

Med J Malaysia, 2024 Mar;79(2):222-233.
PMID: 38553930

INTRODUCTION: Equitable healthcare delivery is essential and requires resources to be distributed, which include assets and healthcare workers. To date, there is no gold standard for measuring the correct number of physicians to meet healthcare needs. This rapid review aims to explore measurement tools employed to optimise the distribution of hospital physicians, with a focus on ensuring fair resource allocation for equitable healthcare delivery.
MATERIALS AND METHODS: A literature search was performed across PubMed, EMBASE, Emerald Insight and grey literature sources. The key terms used in the search include 'distribution', 'method', and 'physician', focusing on research articles published in English from 2002 to 2022 that described methods or tools to measure hospital-based physicians' distribution. Relevant articles were selected through a two-level screening process and critically appraised. The primary outcome is the measurement tools used to assess the distribution of hospital-based physicians. Study characteristics, tool advantages and limitations were also extracted. The extracted data were synthesised narratively.
RESULTS: Out of 7,199 identified articles, 13 met the inclusion criteria. Among the selected articles, 12 were from Asia and one from Africa. The review identified eight measurement tools: Gini coefficients and Lorenz curve, Robin Hood index, Theil index, concentration index, Workload Indicator of Staffing Need method, spatial autocorrelation analysis, mixed integer linear programming model and cohortcomponent model. These tools rely on fundamental data concerning population and physician numbers to generate outputs. Additionally, five studies employed a combination of these tools to gain a comprehensive understanding of physician distribution dynamics.
CONCLUSION: Measurement tools can be used to assess physician distribution according to population needs. Nevertheless, each tool has its own merits and limitations, underscoring the importance of employing a combination of tools. The choice of measuring tool should be tailored to the specific context and research objectives.