Helicobacter pylori infection of a distinct subtype of cagA may lead to different pathological manifestation. The aim of this study is to determine the presence of cagA gene and its variants in H. pylori infection among different ethnic groups and its effect on gastroduodenal diseases. Overall detection of cagA among the 205 clinical isolates of H. pylori was 94%. Variations in size of the 3' region of cagA gene were examined among 192 Malaysian H. pylori cagA-positive strains. Results showed that three cagA variants differing in fragment length of PCR products were detected and designated as type A (621-651bp), type B (732-735bp) and type C (525 bp). Although there was no association between any of the cagA subtypes with peptic ulcer disease (p>0.05), an association between cagA subtypes with a specific ethnic group was observed. Specific-cagA subtype A strains were predominantly isolated from Chinese compared to Malays and Indians (p<0.0005), and cagA subtype B strains were predominantly isolated from Malays and Indians compared to Chinese (p<0.05). The cagA type A strains of H. pylori is commonly found in the Chinese patients who have a higher risk of peptic ulcer disease, thus indicating that it could be used as an important clinical biomarker for a more severe infection.
The unusual heavy rainfall episodes over Kelantan River Basin in 2014 had caused massive destruction and several deaths. The unprecedented storm events at the north-eastern Peninsular Malaysia and many other places indicate the need for enhanced storm forecasting to improve disaster preparedness among the civilian. Quantitative precipitation forecast (QPF) from atmospheric model combined with geostationary meteorological satellite information as input to hydrodynamic model for flood forecasting system can potentially provide improved lead time for warning. In this study, a QPF model is developed using the multilayer neural network with data inputs from the numerical weather prediction (NWP) model products combined with the geostationary meteorological satellite infrared and visible image features to forecast precipitation for a flood-prone area in a tropical region. The results indicate that the model can satisfactorily produce 1-hour rainfall forecast with improved accuracy for larger forecast area. The R2 for areal average rainfall for Kelantan river basin is 0.674 and for Klang river basin is 0.893 whereas the R2 for point rainfall is 0.392 for Kelantan river basin and 0.495 for Klang river basin.
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