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  1. Chien F, Sadiq M, Nawaz MA, Hussain MS, Tran TD, Le Thanh T
    J Environ Manage, 2021 Nov 01;297:113420.
    PMID: 34333309 DOI: 10.1016/j.jenvman.2021.113420
    Environmental degradation is significantly studied both in the past and the current literature; however, steps towards reducing the environmental pollution in carbon emission and haze pollution like PM2.5 are not under rational attention. This study tries to cover this gap while considering the carbon emission and PM2.5 through observing the role of renewable energy, non-renewable energy, environmental taxes, and ecological innovation for the top Asian economies from 1990 to 2017. For analysis purposes, this research considers cross-sectional dependence analysis, unit root test with and without structural break (Pesaran, 2007), slope heterogeneity analysis, Westerlund and Edgerton (2008) panel cointegration analysis, Banerjee and Carrion-i-Silvestre (2017) cointegration analysis, long-short run CS-ARDL results, as well as AMG and CCEMG for robustness check. The empirical evidence in both the short- and long-run has confirmed the negative and significant effect of renewable energy sources, ecological innovation, and environmental taxes on carbon emissions and PM2.5. Whereas, non-renewable energy sources are causing environmental degradation in the targeted economies. Finally, various policy implications related to carbon emission and haze pollution like PM2.5 are also provided to control their harmful effect on the natural environment.
  2. Khor CC, Do T, Jia H, Nakano M, George R, Abu-Amero K, et al.
    Nat Genet, 2016 May;48(5):556-62.
    PMID: 27064256 DOI: 10.1038/ng.3540
    Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 × 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 × 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 × 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 × 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 × 10(-12)). We also confirmed significant association at three previously described loci (P < 5 × 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18), providing new insights into the biology of PACG.
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