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  1. Mohd SNA, Ishak AA, Selvaratnam DP
    Front Public Health, 2021;9:731554.
    PMID: 35004564 DOI: 10.3389/fpubh.2021.731554
    This study investigates the impact of the ageing population on the economic growth for short- and long-run estimations in Malaysia, by using time series data from 1981 to 2019. This study adopts the autoregressive distributed lag (ARDL) method with the Bound test approach for the long-run estimation and the vector error correction model for the short-run estimation. Several econometric diagnostic tests were applied for validation and the appropriate model specification basis. The estimated result of this work indicates that the age dependency ratio proxy for the ageing population variable has a significant negative impact on economic growth in Malaysia. A 1% increase in old age dependency will decline gross domestic product's (GDP's) growth by an average of 6.6043% at the 5% level of significance. Hence, an increase in the ageing population will impede economic growth. Although controlled variables (e.g., physical capital, labour participation, and human capital) have a significant positive impact on economic growth in Malaysia, there is evidence of a long- and short-run relationship between economic growth and the ageing population variable, and also the control variable.
  2. Lee LC, Ishak AA, Nai Eyan AA, Zakaria AF, Kharudin NS, Noor NAM
    Forensic Sci Res, 2022;7(4):761-773.
    PMID: 36817254 DOI: 10.1080/20961790.2021.1899407
    Soil is of particular interest to the forensic community because it can be used as valuable associative evidence to link a suspect to a victim or a crime scene. Liquid chromatography is a powerful analytical tool for organic compound analysis. Recently, high-performance liquid chromatography (HPLC) has proven to be an efficient method for forensic soil analysis, especially in discriminating soils from proximity locations. However, ultra-performance liquid chromatography (UPLC), which is much more sensitive than HPLC, has never been explored in this context. This study proposed a UPLC method for profiling non-volatile organic compounds in three Malaysian soils (red, brown and yellowish-brown soils). The three soils were analysed separately to assess the effects of individual chromatographic parameters: (a) elution programme (isocratic vs. two gradient programmes); (b) flow rate (0.1 vs. 0.2 mL/min); (c) extraction solvent (acetonitrile vs. methanol) and (d) detection wavelength (230 vs. 254 nm). The injection volume and total run time were set to 5 µL and 35 min, respectively. Consequently, each soil sample gave 24 different chromatograms. Results showed that the most desirable chromatographic parameters were (a) isocratic elution; (b) flow rate at 0.2 mL/min and (c) acetonitrile extraction solvent. The proposed UPLC system is expected to be a feasible method for profiling non-volatile organic compounds in soil, and is more chemical-efficient than a comparable HPLC system.
  3. Ishak AA, Selamat J, Sulaiman R, Sukor R, Abdulmalek E, Jambari NN
    Molecules, 2019 Oct 24;24(21).
    PMID: 31652883 DOI: 10.3390/molecules24213828
    The formation of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) was investigated using a kinetic study approach as described by first-order, Arrhenius, and Eyring equations. Chemical model systems with different amino acid precursors (proline, phenylalanine, and glycine) were examined at different times (4, 8, 12, and 16 min) and temperatures (150, 180, 210, 240, and 270 °C). PhIP was detected using high-performance liquid chromatography equipped with fluorescence detector (HPLC-FLD). The good fit in first-order suggested that PhIP formation was influenced by the types of amino acids and PhIP concentration significantly increased with time and temperature (up to 240 °C). PhIP was detected in proline and phenylalanine model systems but not in the glycine model system. The phenylalanine model system demonstrated low activation energy (Ea) of 95.36 kJ/mol that resulted in a high rate of PhIP formation (great amount of PhIP formed). Based on the ∆S‡ values both proline and phenylalanine demonstrated bimolecular rate-limiting steps for PhIP formation. Altogether these kinetic results could provide valuable information in predicting the PhIP formation pathway.
  4. Ahmad MAB, Lee LC, Mohd Rosdi NAN, Abd Hamid NB, Ishak AA, Sino H
    Forensic Sci Res, 2023 Dec;8(4):313-320.
    PMID: 38405627 DOI: 10.1093/fsr/owad045
    Soil is commonly collected from an outdoor crime scene, and thus it is helpful in linking a suspect and a victim to a crime scene. The chemical profiles of soils can be acquired via chemical instruments such as Ultra-Performance Liquid Chromatography (UPLC). However, the UPLC chromatogram often interferes with an unstable baseline. In this paper, we compared the performance of five baseline correction (BC) algorithms, i.e. asymmetric least squares (AsLS), fill peak, iterative restricted least squares, median window (MW), and modified polynomial fitting, in discriminating 30 chromatograms of brownish soils by five locations of origin, i.e. PP, HK, KU, BL, and KB. The performances of the preprocessed sub-datasets were first visually inspected through the mean chromatograms and then further explored via scores plots of principal component analysis (PCA). Eventually, the predictive performances of the partial least squares-discriminant analysis (PLS-DA) models estimated from 1 000 pairs of training and testing samples (i.e. prepared via iterative random resampling split at 75:25) were studied to identify the best BC method. Mean raw chromatograms of the 10 soil samples were different from each other, with evident fluctuated baselines. AsLS and MW corrected chromatograms demonstrated the most significant improvement compared with the raw counterpart. Meanwhile, the scores plot of PCA revealed that most of the sub-datasets produced three separate clusters. Then, the sub-datasets were modelled via the PLS-DA technique. MW emerged as the excellent BC method based on the mean prediction accuracy estimated using 1 000 pairs of training and testing samples. In conclusion, MW outperformed the other BC methods in correcting the UPLC data of soil.

    KEY POINTS: UPLC data of soil interfere with baseline drifts.BC can improve the quality of the pixel-level UPLC data.MW emerges as the most desired algorithm in improving the quality of UPLC data of soil.

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