Displaying all 9 publications

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  1. Gan SC, Yeoh CW
    Med J Malaysia, 1980 Jun;34(4):379-82.
    PMID: 6971393
    Strict precautions were taken in our methodology to exclude any monocytes from being included in the total T and B cell estimation. There is a progressive drop in the percentage of T and B cells with age, but no significant differences between the races nor between the sexes of the same age group. Aberrancies of T and B cell percentages were noted in most infections, malignancies and even malnutrition.
  2. Elango S, Purohit GN, Gan SC, Manap Z, Raza H
    Med J Malaysia, 1989 Sep;44(3):231-5.
    PMID: 2696872
    Ninety five patients with perennial rhinitis were examined clinically and various investigations were done in order to find out the common allergens and to assess the value of various tests in perennial rhinitis. In this study group 94% of cases were proven to be cases of allergic rhinitis. Cat fur was found to be the commonest allergen. Grass pollen which is a common allergen in European countries was found in only 18% of cases in the present study. X-ray of the paranasal sinuses as a routine investigation was not found to be of much use in perennial rhinitis. There was significant correlation between results for allergens tested by enzyme immunoassay and skin prick test.
  3. Lim SJ, Gan SC, Ong HT, Ngeow YF
    Biochem Biophys Rep, 2024 Sep;39:101814.
    PMID: 39263317 DOI: 10.1016/j.bbrep.2024.101814
    BACKGROUND: Vascular endothelial growth factor (VEGF) is one of the proteins involved in dengue immunopathogenesis. It is overexpressed in severe dengue and contributes to vascular permeability and plasma leakage. In this study, we investigated the effects of VEGF and anti-VEGF treatments on endothelial cells in vitro, to assess the potential use of anti-VEGF antibodies in managing severe dengue.

    METHODS: Human pulmonary microvascular endothelial cells were treated with VEGF and a VEGF/anti-VEGF combination. The effects of the treatments were studied using an endothelial permeability assay and microarray gene expression profiling. In the permeability assay, the fluorescein isothiocyanate (FITC)-dextran fluorescence signal across the endothelial monolayer was recorded, and the cells were stained with PECAM-1 to detect gap formation. RNA was extracted from treated cells for microarray gene profiling and analysis. The results were analyzed for differentially expressed genes (DEGs) and gene enrichment analysis. The DEGs were subjected to STRING to construct the protein-protein interaction network and then Cytoscape to identify the hub genes.

    RESULTS: VEGF-treated endothelial cells showed greater movement of FITC-dextran across the monolayer than VEGF/anti-VEGF-treated cells. There were 111 DEGs for VEGF-treated cells and 118 DEGs for VEGF/anti-VEGF-treated cells. The genes upregulated in VEGF-treated cells were enriched in inflammatory responses and regulation of the endothelial barrier, nitric oxide synthesis, angiogenesis, and the nucleotide-binding oligomerization domain-like receptor signaling pathway. Top 10 hub genes were identified from the DEGs.

    CONCLUSIONS: VEGF treatment increased permeability across endothelial cells, while anti-VEGF reduced this leakage. Analysis of VEGF-treated endothelial cells identified hub genes implicated in severe dengue. The top 10 hub genes were TNF, IL1B, IL6, CCL2, PTGS2, ICAM1, CXCL2, CXCL1, CSF2, and TLR2. The results of this study show that using anti-VEGF antibodies to neutralize VEGF may be a promising therapy to prevent the progression of dengue to severe dengue.

  4. Gan SC, Fok ASL, Sedky RA, Sukumaran P, Chew HP
    Dent Mater, 2020 11;36(11):1379-1387.
    PMID: 32907752 DOI: 10.1016/j.dental.2020.08.003
    OBJECTIVE: The aim of this research was to determine the association between sorptivity of water and the state of mineralization in carious enamel of different stages of severity.

    METHODS: As a preliminary work, water droplets of 1.5 μL were placed on the surfaces of hydroxyapatite (HA) discs of different densities. The water droplet profile was dynamically recorded every second over a period of 10 s using a contact angle meter to determine the relationship between sorptivity and density. To measure and calculate sorptivity on enamel surfaces, varnish was painted on the labial surface of 96 extracted caries-free human teeth, leaving two 1.4 ± 0.1 mm diameter circular exposed test sites. The specimens were randomly divided into 6 groups (n = 16) and subjected to 0(G0), 7(G7), 14(G14), 21(G21), 28(G28) and 35(G35) days of pH cycling, respectively. A 0.7 μL water droplet was placed on each exposed site and Optical Coherence Tomography was used to measure its height every 10 seconds for 2 min. Sorptivity was computed by considering sorption equations and Washburn's analysis of capillary kinetics and correction for evaporation was also performed. Micro-Computed Tomography scans of the specimens were obtained and delta Z (ΔZ) is the parameter used to measure mineral loss. ΔZ at 10 μm (ΔZ10) and 50 μm (ΔZ50) from the surface were calculated. One-way ANOVA and Post-hoc Tukey tests were used to compare sorptivity between groups and bivariate correlations were used to analyze the association between sorptivity and ΔZ.

    RESULTS: Sorptivity was found to be inversely and linearly correlated with HA density with R2 value of 0.95. With enamel, there is a general trend of increase in mean sorptivity from G0 to G35, except for a decrease in G21. The same trends were observed for both ΔZ10 and ΔZ50. The decrease in sorptivity in G21 coincided with the presence of a surface hypermineralized layer in G21 samples. Post-hoc Tukey showed significant differences in mean sorptivity between G0 and G14, G0 and G21 as well as G14 and G21. Post-hoc Dunnett's T3 showed significant differences for ΔZ10 between G0 and G14 as well as G14 and G21. Significant correlation between mean sorptivity and ΔZ10 was detected with Pearson correlation coefficient of 0.461. For ΔZ50, post-hoc Tukey showed significant differences between G0 and G14 but no significant difference was detected between G14 and G21. No correlations were detected between mean sorptivity and ΔZ50.

    SIGNIFICANCE: Sorptivity was found to be inversely and linearly correlated with HA density with R2 value of 0.95. With enamel, there is a general trend of increase in mean sorptivity from G0 to G35, except for a decrease in G21. The same trends were observed for both ΔZ10 and ΔZ50. The decrease in sorptivity in G21 coincided with the presence of a surface hypermineralized layer in G21 samples.

  5. Low GKK, Papapreponis P, Isa RM, Gan SC, Chee HY, Te KK, et al.
    Geospat Health, 2018 05 07;13(1):642.
    PMID: 29772885 DOI: 10.4081/gh.2018.642
    Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia's leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds.
  6. See HQ, Chan JN, Ling SJ, Gan SC, Leong CO, Mai CW
    J Pharm Pharm Sci, 2018;21(1):217-221.
    PMID: 29935548 DOI: 10.18433/jpps29869
    Big data is anticipated to have large implications in clinical pharmacy, in view of its potential in enhancing precision medicine and to avoid medication error. However, it is equally debatable since such a powerful tool may also disrupt the need of pharmacist in healthcare industry. In this article, we commented the contribution of Big Data in various aspects of clinical pharmacy including advancing pharmaceutical care service, optimising drug supplies, managing clinical trials, and strengthening pharmacovigilance. The future direction of the usage of Big Data related to clinical pharmacy will be discussed. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
  7. Low GK, Ogston SA, Yong MH, Gan SC, Chee HY
    Acta Trop, 2018 Jun;182:237-245.
    PMID: 29545158 DOI: 10.1016/j.actatropica.2018.03.014
    BACKGROUND: Since the introduction of 2009 WHO dengue case classification, no literature was found regarding its effect on dengue death. This study was to evaluate the effect of 2009 WHO dengue case classification towards dengue case fatality rate.

    METHODS: Various databases were used to search relevant articles since 1995. Studies included were cohort and cross-sectional studies, all patients with dengue infection and must report the number of death or case fatality rate. The Joanna Briggs Institute appraisal checklist was used to evaluate the risk of bias of the full-texts. The studies were grouped according to the classification adopted: WHO 1997 and WHO 2009. Meta-regression was employed using a logistic transformation (log-odds) of the case fatality rate. The result of the meta-regression was the adjusted case fatality rate and odds ratio on the explanatory variables.

    RESULTS: A total of 77 studies were included in the meta-regression analysis. The case fatality rate for all studies combined was 1.14% with 95% confidence interval (CI) of 0.82-1.58%. The combined (unadjusted) case fatality rate for 69 studies which adopted WHO 1997 dengue case classification was 1.09% with 95% CI of 0.77-1.55%; and for eight studies with WHO 2009 was 1.62% with 95% CI of 0.64-4.02%. The unadjusted and adjusted odds ratio of case fatality using WHO 2009 dengue case classification was 1.49 (95% CI: 0.52, 4.24) and 0.83 (95% CI: 0.26, 2.63) respectively, compared to WHO 1997 dengue case classification. There was an apparent increase in trend of case fatality rate from the year 1992-2016. Neither was statistically significant.

    CONCLUSIONS: The WHO 2009 dengue case classification might have no effect towards the case fatality rate although the adjusted results indicated a lower case fatality rate. Future studies are required for an update in the meta-regression analysis to confirm the findings.

  8. Low GKK, Gan SC, Zainal N, Naidu KD, Amin-Nordin S, Khoo CS, et al.
    Pathog Glob Health, 2018 09;112(6):334-341.
    PMID: 30246621 DOI: 10.1080/20477724.2018.1516417
    This study aimed to evaluate vascular endothelial growth factor (VEGF) and pentraxin 3 (PTX-3) as predictive and diagnostic markers in differentiating severe dengue from non-severe dengue. The study was conducted in Ampang Health Clinic, Ampang Hospital and Serdang Hospital. The plasma levels of VEGF and PTX-3 were compared between severe dengue and non-severe dengue by ELISA from the day of presentation until discharged. Multiple logistic regression was used to develop predictive and diagnostic models by incorporating other clinical parameters. The receiver operating characteristics (ROC) analysis was used to assess the accuracy of the biomarkers and the developed models. Eighty-two patients were recruited, 29 with severe dengue and four died. The Area Under the Curve (AUC) was statistically significant in VEGF as diagnostic marker at Day 2 and 3 of illness with sensitivity of 80.00%-100.00% and specificity of 76.47%-80.00%. The predictive model with AUC of 0.84 (p 
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