Displaying publications 1 - 20 of 51 in total

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  1. Rana MM, Sulaiman N, Sivertsen B, Khan MF, Nasreen S
    Environ Sci Pollut Res Int, 2016 Sep;23(17):17393-403.
    PMID: 27230142 DOI: 10.1007/s11356-016-6950-4
    Dhaka and its neighboring areas suffer from severe air pollution, especially during dry season (November-April). We investigated temporal and directional variations in particulate matter (PM) concentrations in Dhaka, Gazipur, and Narayanganj from October 2012 to March 2015 to understand different aspects of PM concentrations and possible sources of high pollution in this region. Ninety-six-hour backward trajectories for the whole dry season were also computed to investigate incursion of long-range pollution into this area. We found yearly PM10 concentrations in this area about three times and yearly PM2.5 concentrations about six times greater than the national standards of Bangladesh. Dhaka and its vicinity experienced several air pollution episodes in dry season when PM2.5 concentrations were 8-13 times greater than the World Health Organization (WHO) guideline value. Higher pollution and great contribution of PM2.5 most of the time were associated with the north-westerly wind. Winter (November to January) was found as the most polluted season in this area, when average PM10 concentrations in Dhaka, Gazipur, and Narayanganj were 257.1, 240.3, and 327.4 μg m(-3), respectively. Pollution levels during wet season (May-October) were, although found legitimate as per the national standards of Bangladesh, exceeded WHO guideline value in 50 % of the days of that season. Trans-boundary source identifications using concentration-weighted trajectory method revealed that the sources in the eastern Indian region bordering Bangladesh, in the north-eastern Indian region bordering Nepal and in Nepal and its neighboring areas had high probability of contributing to the PM pollutions at Gazipur station.
  2. Najurudeen NANB, Khan MF, Suradi H, Mim UA, Raim INJ, Rashid SB, et al.
    Sci Total Environ, 2023 Mar 29;878:163129.
    PMID: 37001671 DOI: 10.1016/j.scitotenv.2023.163129
    Polycyclic aromatic hydrocarbons (PAHs) in the atmospheric particles constitute a topic of growing health concern. This study aims to calculate PAH concentrations, identify the source, assess the health risk from exposure to carcinogenic PAHs, and the respiratory deposition flux. PM10 and PM2.5 were collected in September 2019 in the urban, semi-urban, and semi-urban-industrial areas of Kuala Lumpur, Batu Pahat, and Bukit Rambai, respectively. A total of 18 PAHs from PM10 and 17 PAHs from PM2.5 were extracted using dichloromethane and determined using gas chromatography coupled with a flame ionization detector (GC-FID). The health risk assessment (HRA) calculated included B[a]P equivalent (B[a]Peq), lifetime lung cancer risk (LLCR), incremental lifetime cancer risk (ILCR), and respiratory deposition dose (RDD). The results show PAHs in PM10 recorded in Kuala Lumpur (DBKL), Batu Pahat (UTHM), and Bukit Rambai are 9.91, 8.45, and 9.57 ng/m3, respectively. The average PAHs in PM2.5 at the three sampling sites are 11.65, 9.68, and 9.37 ng/m3, respectively. The major source of PAHs obtained from the DRs indicates pyrogenic activities for both particle sizes. For PM10, the total B[a]Peq in DBKL, UTHM, and Bukit Rambai were 1.97, 1.82, and 2.32 ng/m3, respectively. For PM2.5 samples, the total B[a]Peq in DBKL, UTHM, and Bukit Rambai were 2.80, 2.33, and 2.57 ng/m3, respectively. The LLCR and ILCR show low to moderate risk for all age groups. The RDD of adults and adolescents is highest in both PM10 and PM2.5, followed by children, toddlers, and infants. Overall, we perceive that adults and adolescents living in the urban area of Kuala Lumpur are at the highest risk for respiratory health problems because of prolonged exposure to PAHs in PM10 and PM2.5, followed by children, toddlers, and infants.
  3. Abdul Halim ND, Latif MT, Ahamad F, Dominick D, Chung JX, Juneng L, et al.
    Heliyon, 2018 Dec;4(12):e01054.
    PMID: 30603693 DOI: 10.1016/j.heliyon.2018.e01054
    This study aims to evaluate the air quality on Langkawi Island, a famous tourist destination in Malaysia, using 13 years of data (1999-2011) recorded by the Malaysian Department of Environment. Variations of seven air pollutants (O3, CO, NO, NO2, NOx, SO2 and PM10) and three meteorological factors (temperature, humidity and wind speed) were analysed. Statistical methods used to analyse the data included principal component regression (PCR) and sensitivity analysis. The results showed PM10 was the dominant air pollutant in Langkawi and values ranged between 5.0 μg m-3 and 183.2 μg m-3. The patterns of monthly values showed that the concentrations of measured air pollutants on Langkawi were higher during the south-west monsoon (June-September) due to seasonal biomass burning activities. High CO/NOx ratio values (between 28.3 and 43.6), low SO2/NOx ratio values (between 0.04 and 0.12) and NO/NO2 ratio values exceeding 2.2 indicate the source of air pollutants in this area was motor vehicles. PCR analysis grouped the seven variables into two factor components: the F1 component consisted of SO2, NO and NOx and the F2 component consisted of PM10. The F1 component (R2 = 0.931) indicated a stronger standardized coefficient value for meteorological variables compared to the F2 component (R2 = 0.059). The meteorological variables were statistically significant (p < 0.05) in influencing the distribution of the air pollutants. The status of air quality on the island could be improved through control on motor vehicle emissions as well as collaborative efforts to reduce regional air pollution, especially from biomass burning.
  4. Yatim ANM, Latif MT, Sofwan NM, Ahamad F, Khan MF, Mahiyuddin WRW, et al.
    Environ Sci Pollut Res Int, 2021 Nov;28(42):60209-60220.
    PMID: 34156627 DOI: 10.1007/s11356-021-14962-8
    This study aims to examine the relationship between daily temperature and mortality in the Klang Valley, Malaysia, over the period 2006-2015. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM) was used to estimate the association between the mean temperature and mortality categories (natural n=69,542, cardiovascular n= 15,581, and respiratory disease n=10,119). Particulate matter with an aerodynamic diameter below 10 μm (PM10) and surface ozone (O3) was adjusted as a potential confounding factor. The relative risk (RR) of natural mortality associated with extreme cold temperature (1st percentile of temperature, 25.2 °C) over lags 0-28 days was 1.26 (95% confidence interval (CI): 1.00, 1.60), compared with the minimum mortality temperature (28.2 °C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 30.2 °C) over lags 0-3 days was 1.09 (95% CI: 1.02, 1.17). Heat effects were immediate whereas cold effects were delayed and lasted longer. People with respiratory diseases, the elderly, and women were the most vulnerable groups when it came to the effects of extremely high temperatures. Extreme temperatures did not dramatically change the temperature-mortality risk estimates made before and after adjustments for air pollutant (PM10 and O3) levels.
  5. Jaafar SA, Latif MT, Chian CW, Han WS, Wahid NB, Razak IS, et al.
    Mar Pollut Bull, 2014 Jul 15;84(1-2):35-43.
    PMID: 24930738 DOI: 10.1016/j.marpolbul.2014.05.047
    This study was conducted to determine the composition of surfactants in the sea-surface microlayer (SML) and atmospheric aerosol around the southern region of the Peninsular Malaysia. Surfactants in samples taken from the SML and atmospheric aerosol were determined using a colorimetric method, as either methylene blue active substances (MBAS) or disulphine blue active substances (DBAS). Principal component analysis with multiple linear regressions (PCA-MLR), using the anion and major element composition of the aerosol samples, was used to determine possible sources of surfactants in atmospheric aerosol. The results showed that the concentrations of surfactants in the SML and atmospheric aerosol were dominated by anionic surfactants and that surfactants in aerosol were not directly correlated (p>0.05) with surfactants in the SML. Further PCA-MLR from anion and major element concentrations showed that combustion of fossil fuel and sea spray were the major contributors to surfactants in aerosol in the study area.
  6. Shaharom S, Latif MT, Khan MF, Yusof SNM, Sulong NA, Wahid NBA, et al.
    Environ Sci Pollut Res Int, 2018 Sep;25(27):27074-27089.
    PMID: 30019134 DOI: 10.1007/s11356-018-2745-0
    This study aims to determine the concentrations of surfactants in the surface microlayer (SML), subsurface water (SSW) and fine mode aerosol (diameter size
  7. Razak IS, Latif MT, Jaafar SA, Khan MF, Mushrifah I
    Environ Sci Pollut Res Int, 2015 Apr;22(8):6024-33.
    PMID: 25382497 DOI: 10.1007/s11356-014-3781-z
    This study was conducted to determine the composition of surfactants in atmospheric aerosols and rainwater in the vicinity of Lake Chini, Malaysia. Samples of atmospheric aerosol and rainwater were collected between March and September 2011 using a high volume air sampler (HVAS) and glass bottles equipped with funnel. Colorimetric analysis was undertaken to determine the concentration of anionic surfactants as methylene blue active substances (MBAS) and cationic surfactants as disulphine blue active substances (DBAS). The water-soluble ionic compositions were determined using inductively coupled plasma mass spectrometry for cations (Na, K, Mg and Ca) and ion chromatography equipped with a conductivity detector for anions (F(-), Cl(-), NO3(-), and SO4(2-)) and the Nessler Method was used to obtain the NH4(+) concentrations. The source apportionment of MBAS and DBAS in atmospheric aerosols was identified using a combination of principal component analysis (PCA) and multiple linear regression (MLR). The results revealed that the concentrations of surfactants in atmospheric aerosols and rainwater were dominated by anionic surfactants as MBAS. The concentration of surfactants as MBAS and DBAS was dominated in fine mode compared to coarse mode aerosols. Using PCA/MLR analysis, two major sources of atmospheric surfactants to Lake Chini were identified as soil dust (75 to 93%) and biomass burning (2 to 22%).
  8. Alsalahi MA, Latif MT, Ali MM, Dominick D, Khan MF, Mustaffa NI, et al.
    Mar Pollut Bull, 2015 Apr 15;93(1-2):278-83.
    PMID: 25682566 DOI: 10.1016/j.marpolbul.2015.01.011
    This study aims to determine the concentration of sterols used as biomarkers in the surface microlayer (SML) in estuarine areas of the Selangor River, Malaysia. Samples were collected during different seasons through the use of a rotation drum. The analysis of sterols was performed using gas chromatography equipped with a flame ionisation detector (GC-FID). The results showed that the concentrations of total sterols in the SML ranged from 107.06 to 505.55 ng L(-1). The total sterol concentration was found to be higher in the wet season. Cholesterol was found to be the most abundant sterols component in the SML. The diagnostic ratios of sterols show the influence of natural sources and waste on the contribution of sterols in the SML. Further analysis, using principal component analysis (PCA), showed distinct inputs of sterols derived from human activity (40.58%), terrigenous and plant inputs (22.59%) as well as phytoplankton and marine inputs (17.35%).
  9. Nadzir MSM, Ashfold MJ, Khan MF, Robinson AD, Bolas C, Latif MT, et al.
    Environ Sci Pollut Res Int, 2018 Jan;25(3):2194-2210.
    PMID: 29116536 DOI: 10.1007/s11356-017-0521-1
    The Antarctic continent is known to be an unpopulated region due to its extreme weather and climate conditions. However, the air quality over this continent can be affected by long-lived anthropogenic pollutants from the mainland. The Argentinian region of Ushuaia is often the main source area of accumulated hazardous gases over the Antarctic Peninsula. The main objective of this study is to report the first in situ observations yet known of surface ozone (O3) over Ushuaia, the Drake Passage, and Coastal Antarctic Peninsula (CAP) on board the RV Australis during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC'16). Hourly O3 data was measured continuously for 23 days using an EcoTech O3 analyzer. To understand more about the distribution of surface O3 over the Antarctic, we present the spatial and temporal of surface O3 of long-term data (2009-2015) obtained online from the World Meteorology Organization of World Data Centre for greenhouse gases (WMO WDCGG). Furthermore, surface O3 satellite data from the free online NOAA-Atmospheric Infrared Sounder (AIRS) database and online data assimilation from the European Centre for Medium-Range Weather Forecasts (ECMWF)-Monitoring Atmospheric Composition and Climate (MACC) were used. The data from both online products are compared to document the data sets and to give an indication of its quality towards in situ data. Finally, we used past carbon monoxide (CO) data as a proxy of surface O3 formation over Ushuaia and the Antarctic region. Our key findings were that the surface O3 mixing ratio during MASEC'16 increased from a minimum of 5 ppb to ~ 10-13 ppb approaching the Drake Passage and the Coastal Antarctic Peninsula (CAP) region. The anthropogenic and biogenic O3 precursors from Ushuaia and the marine region influenced the mixing ratio of surface O3 over the Drake Passage and CAP region. The past data from WDCGG showed that the annual O3 cycle has a maximum during the winter of 30 to 35 ppb between June and August and a minimum during the summer (January to February) of 10 to 20 ppb. The surface O3 mixing ratio during the summer was controlled by photochemical processes in the presence of sunlight, leading to the depletion process. During the winter, the photochemical production of surface O3 was more dominant. The NOAA-AIRS and ECMWF-MACC analysis agreed well with the MASEC'16 data but twice were higher during the expedition period. Finally, the CO past data showed the surface O3 mixing ratio was influenced by the CO mixing ratio over both the Ushuaia and Antarctic regions. Peak surface O3 and CO hourly mixing ratios reached up to ~ 38 ppb (O3) and ~ 500 ppb (CO) over Ushuaia. High CO over Ushuaia led to the depletion process of surface O3 over the region. Monthly CO mixing ratio over Antarctic (South Pole) were low, leading to the production of surface O3 over the Antarctic region.
  10. Othman M, Latif MT, Jamhari AA, Abd Hamid HH, Uning R, Khan MF, et al.
    Chemosphere, 2021 Jan;262:127767.
    PMID: 32763576 DOI: 10.1016/j.chemosphere.2020.127767
    This study aimed to determine the spatial distribution of PM2.5 and PM10 collected in four regions (North, Central, South and East Coast) of Peninsular Malaysia during the southwest monsoon. Concurrent measurements of PM2.5 and PM10 were performed using a high volume sampler (HVS) for 24 h (August to September 2018) collecting a total of 104 samples. All samples were then analysed for water soluble inorganic ions (WSII) using ion chromatography, trace metals using inductively coupled plasma-mass spectroscopy (ICP-MS) and polycyclic aromatic hydrocarbon (PAHs) using gas chromatography-mass spectroscopy (GC-MS). The results showed that the highest average PM2.5 concentration during the sampling campaign was in the North region (33.2 ± 5.3 μg m-3) while for PM10 the highest was in the Central region (38.6 ± 7.70 μg m-3). WSII recorded contributions of 22% for PM2.5 and 20% for PM10 mass, with SO42- the most abundant species with average concentrations of 1.83 ± 0.42 μg m-3 (PM2.5) and 2.19 ± 0.27 μg m-3 (PM10). Using a Positive Matrix Factorization (PMF) model, soil fertilizer (23%) was identified as the major source of PM2.5 while industrial activity (25%) was identified as the major source of PM10. Overall, the studied metals had hazard quotients (HQ) value of <1 indicating a very low risk of non-carcinogenic elements while the highest excess lifetime cancer risk (ELCR) was recorded for Cr VI in the South region with values of 8.4E-06 (PM2.5) and 6.6E-05 (PM10). The incremental lifetime cancer risk (ILCR) calculated from the PAH concentrations was within the acceptable range for all regions.
  11. Ee-Ling O, Mustaffa NI, Amil N, Khan MF, Latif MT
    Bull Environ Contam Toxicol, 2015 Apr;94(4):537-42.
    PMID: 25652682 DOI: 10.1007/s00128-015-1477-9
    This study determined the source contribution of PM2.5 (particulate matter <2.5 μm) in air at three locations on the Malaysian Peninsula. PM2.5 samples were collected using a high volume sampler equipped with quartz filters. Ion chromatography was used to determine the ionic composition of the samples and inductively coupled plasma mass spectrometry was used to determine the concentrations of heavy metals. Principal component analysis with multilinear regressions were used to identify the possible sources of PM2.5. The range of PM2.5 was between 10 ± 3 and 30 ± 7 µg m(-3). Sulfate (SO4 (2-)) was the major ionic compound detected and zinc was found to dominate the heavy metals. Source apportionment analysis revealed that motor vehicle and soil dust dominated the composition of PM2.5 in the urban area. Domestic waste combustion dominated in the suburban area, while biomass burning dominated in the rural area.
  12. Mustaffa NI, Latif MT, Ali MM, Khan MF
    Environ Sci Pollut Res Int, 2014 May;21(10):6590-602.
    PMID: 24532245 DOI: 10.1007/s11356-014-2562-z
    This study aims to determine the source apportionment of surfactants in marine aerosols at two selected stations along the Malacca Straits. The aerosol samples were collected using a high volume sampler equipped with an impactor to separate coarse- and fine-mode aerosols. The concentrations of surfactants, as methylene blue active substance and disulphine blue active substance, were analysed using colorimetric method. Ion chromatography was employed to determine the ionic compositions. Principal component analysis combined with multiple linear regression was used to identify and quantify the sources of atmospheric surfactants. The results showed that the surfactants in tropical coastal environments are actively generated from natural and anthropogenic origins. Sea spray (generated from sea-surface microlayers) was found to be a major contributor to surfactants in both aerosol sizes. Meanwhile, the anthropogenic sources (motor vehicles/biomass burning) were predominant contributors to atmospheric surfactants in fine-mode aerosols.
  13. Mohamad N, Latif MT, Khan MF
    Ecotoxicol Environ Saf, 2016 Feb;124:351-362.
    PMID: 26590697 DOI: 10.1016/j.ecoenv.2015.11.002
    This study aimed to investigate the chemical composition and potential sources of PM10 as well as assess the potential health hazards it posed to school children. PM10 samples were taken from classrooms at a school in Kuala Lumpur's city centre (S1) and one in the suburban city of Putrajaya (S2) over a period of eight hours using a low volume sampler (LVS). The composition of the major ions and trace metals in PM10 were then analysed using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. The results showed that the average PM10 concentration inside the classroom at the city centre school (82µg/m(3)) was higher than that from the suburban school (77µg/m(3)). Principal component analysis-absolute principal component scores (PCA-APCS) revealed that road dust was the major source of indoor PM10 at both school in the city centre (36%) and the suburban location (55%). The total hazard quotient (HQ) calculated, based on the formula suggested by the United States Environmental Protection Agency (USEPA), was found to be slightly higher than the acceptable level of 1, indicating that inhalation exposure to particle-bound non-carcinogenic metals of PM10, particularly Cr exposure by children and adults occupying the school environment, was far from negligible.
  14. Sulong NA, Latif MT, Khan MF, Amil N, Ashfold MJ, Wahab MIA, et al.
    Sci Total Environ, 2017 Dec 01;601-602:556-570.
    PMID: 28575833 DOI: 10.1016/j.scitotenv.2017.05.153
    This study aims to determine PM2.5concentrations and their composition during haze and non-haze episodes in Kuala Lumpur. In order to investigate the origin of the measured air masses, the Numerical Atmospheric-dispersion Modelling Environment (NAME) and Global Fire Assimilation System (GFAS) were applied. Source apportionment of PM2.5was determined using Positive Matrix Factorization (PMF). The carcinogenic and non-carcinogenic health risks were estimated using the United State Environmental Protection Agency (USEPA) method. PM2.5samples were collected from the centre of the city using a high-volume air sampler (HVS). The results showed that the mean PM2.5concentrations collected during pre-haze, haze and post-haze periods were 24.5±12.0μgm-3, 72.3±38.0μgm-3and 14.3±3.58μgm-3, respectively. The highest concentration of PM2.5during haze episode was five times higher than World Health Organisation (WHO) guidelines. Inorganic compositions of PM2.5, including trace elements and water soluble ions were determined using inductively coupled plasma-mass spectrometry (ICP-MS) and ion chromatography (IC), respectively. The major trace elements identified were K, Al, Ca, Mg and Fe which accounted for approximately 93%, 91% and 92% of the overall metals' portions recorded during pre-haze, haze and post-haze periods, respectively. For water-soluble ions, secondary inorganic aerosols (SO42-, NO3-and NH4+) contributed around 12%, 43% and 16% of the overall PM2.5mass during pre-haze, haze and post-haze periods, respectively. During haze periods, the predominant source identified using PMF was secondary inorganic aerosol (SIA) and biomass burning where the NAME simulations indicate the importance of fires in Sumatra, Indonesia. The main source during pre-haze and post-haze were mix SIA and road dust as well as mineral dust, respectively. The highest non-carcinogenic health risk during haze episode was estimated among the infant group (HI=1.06) while the highest carcinogenic health risk was estimated among the adult group (2.27×10-5).
  15. Dahari N, Muda K, Latif MT, Dominick D, Hussein N, Khan MF
    PMID: 34596792 DOI: 10.1007/s10653-021-01099-3
    The smaller particles that dominate the particle number concentration (PNC) in the ambient air only contribute to a small percentage of particulate matter (PM) mass concentration although present in high particle number concentration. These small particles may be neglected upon assessing the health impacts of the PM. Hence, the knowledge on the particle number concentration size distribution deserves greater attention than the particulate mass concentration. This study investigates the measurement of the particle mass concentrations (PM2.5) and PNC of 0.27 μm 
  16. Latif MT, Dominick D, Ahamad F, Ahamad NS, Khan MF, Juneng L, et al.
    Sci Total Environ, 2016 Dec 15;573:494-504.
    PMID: 27572541 DOI: 10.1016/j.scitotenv.2016.08.121
    Malaysian Borneo has a lower population density and is an area known for its lush rainforests. However, changes in pollutant profiles are expected due to increasing urbanisation and commercial-industrial activities. This study aims to determine the variation of surface O3concentration recorded at seven selected stations in Malaysian Borneo. Hourly surface O3data covering the period 2002 to 2013, obtained from the Malaysian Department of Environment (DOE), were analysed using statistical methods. The results show that the concentrations of O3recorded in Malaysian Borneo during the study period were below the maximum Malaysian Air Quality Standard of 100ppbv. The hourly average and maximum O3concentrations of 31 and 92ppbv reported at Bintulu (S3) respectively were the highest among the O3concentrations recorded at the sampling stations. Further investigation on O3precursors show that sampling sites located near to local petrochemical industrial activities, such as Bintulu (S3) and Miri (S4), have higher NO2/NO ratios (between 3.21 and 5.67) compared to other stations. The normalised O3values recorded at all stations were higher during the weekend compared to weekdays (unlike its precursors) which suggests the influence of O3titration by NO during weekdays. The results also show that there are distinct seasonal variations in O3across Borneo. High surface O3concentrations were usually observed between August and September at all stations with the exception of station S7 on the east coast. Majority of the stations (except S1 and S6) have recorded increasing averaged maximum concentrations of surface O3over the analysed years. Increasing trends of NO2and decreasing trends of NO influence the yearly averaged maximum of O3especially at S3. This study also shows that variations of meteorological factors such as wind speed and direction, humidity and temperature influence the concentration of surface O3.
  17. Nisa FY, Rahman MA, Hossen MA, Khan MF, Khan MAN, Majid M, et al.
    Ann Med, 2021 Dec;53(1):1476-1501.
    PMID: 34433343 DOI: 10.1080/07853890.2021.1966088
    Alzheimer's disease (AD) is the most conspicuous chronic neurodegenerative syndrome, which has become a significant challenge for the global healthcare system. Multiple studies have corroborated a clear association of neurotoxicants with AD pathogenicity, such as Amyloid beta (Aβ) proteins and neurofibrillary tangles (NFTs), signalling pathway modifications, cellular stress, cognitive dysfunctions, neuronal apoptosis, neuroinflammation, epigenetic modification, and so on. This review, therefore, aimed to address several essential mechanisms and signalling cascades, including Wnt (wingless and int.) signalling pathway, autophagy, mammalian target of rapamycin (mTOR), protein kinase C (PKC) signalling cascades, cellular redox status, energy metabolism, glutamatergic neurotransmissions, immune cell stimulations (e.g. microglia, astrocytes) as well as an amyloid precursor protein (APP), presenilin-1 (PSEN1), presenilin-2 (PSEN2) and other AD-related gene expressions that have been pretentious and modulated by the various neurotoxicants. This review concluded that neurotoxicants play a momentous role in developing AD through modulating various signalling cascades. Nevertheless, comprehension of this risk agent-induced neurotoxicity is far too little. More in-depth epidemiological and systematic investigations are needed to understand the potential mechanisms better to address these neurotoxicants and improve approaches to their risk exposure that aid in AD pathogenesis.Key messagesInevitable cascade mechanisms of how Alzheimer's Disease-related (AD-related) gene expressions are modulated by neurotoxicants have been discussed.Involvement of the neurotoxicants-induced pathways caused an extended risk of AD is explicited.Integration of cell culture, animals and population-based analysis on the clinical severity of AD is addressed.
  18. Tajudin MABA, Khan MF, Mahiyuddin WRW, Hod R, Latif MT, Hamid AH, et al.
    Ecotoxicol Environ Saf, 2019 Apr 30;171:290-300.
    PMID: 30612017 DOI: 10.1016/j.ecoenv.2018.12.057
    Rapid urbanisation in Malaysian cities poses risks to the health of residents. This study aims to estimate the relative risk (RR) of major air pollutants on cardiovascular and respiratory hospitalisations in Kuala Lumpur. Daily hospitalisations due to cardiovascular and respiratory diseases from 2010 to 2014 were obtained from the Hospital Canselor Tuanku Muhriz (HCTM). The trace gases, PM10 and weather variables were obtained from the Department of Environment (DOE) Malaysia in consistent with the hospitalisation data. The RR was estimated using a Generalised Additive Model (GAM) based on Poisson regression. A "lag" concept was used where the analysis was segregated into risks of immediate exposure (lag 0) until exposure after 5 days (lag 5). The results showed that the gases could pose significant risks towards cardiovascular and respiratory hospitalisations. However, the RR value of PM10 was not significant in this study. Immediate effects on cardiovascular hospitalisations were observed for NO2 and O3 but no immediate effect was found on respiratory hospitalisations. Delayed effects on cardiovascular and respiratory hospitalisations were found with SO2 and NO2. The highest RR value was observed at lag 4 for respiratory admissions with SO2 (RR = 1.123, 95% CI = 1.045-1.207), followed by NO2 at lag 5 for cardiovascular admissions (RR = 1.025, 95% CI = 1.005-1.046). For the multi-pollutant model, NO2 at lag 5 showed the highest risks towards cardiovascular hospitalisations after controlling for O3 8 h mean lag 1 (RR = 1.026, 95% CI = 1.006-1.047), while SO2 at lag 4 showed highest risks towards respiratory hospitalisations after controlling for NO2 lag 3 (RR = 1.132, 95% CI = 1.053-1.216). This study indicated that exposure to trace gases in Kuala Lumpur could lead to both immediate and delayed effects on cardiovascular and respiratory hospitalisations.
  19. Hossen MA, Reza ASMA, Ahmed AMA, Islam MK, Jahan I, Hossain R, et al.
    Biomed Pharmacother, 2021 Mar;135:111211.
    PMID: 33421733 DOI: 10.1016/j.biopha.2020.111211
    Blumea lacera (Burm.f.) DC. is described as a valuable medicinal plant in various popular systems of medicine. The aim of the experiment reports the in vivo antiulcer activity of methanol extract of Blumea lacera (MEBLL) and in silico studies of bioactive constituents of MEBLL. In this study, fasted Long-Evans rat treated with 80 % ethanol (0.5 mL) to induce gastric ulcer, were pretreated orally with MEBLL at different doses (250 and 500 mg/kg, p.o., b.w) and omeprazole (20 mg/kg, p.o.) and distilled water were used as a reference drug and normal control respectively. In silico activity against gastric H+-K+ATPase enzyme was also studied. The findings demonstrated that the treatment with MEBLL attenuated markedly ulcer and protected the integrity of the gastric mucosa by preventing the mucosal ulceration altered biochemical parameters of gastric juice such total carbohydrate, total protein and pepsin activity. Additionally, the experimental groups significantly (p 
  20. Ali MYM, Hanafiah MM, Khan MF
    Sci Total Environ, 2018 Jun 01;626:1-10.
    PMID: 29331833 DOI: 10.1016/j.scitotenv.2018.01.080
    This study aimed to measure the equilibrium equivalent radon (EECRn) concentration in an old building (Building-1) and a new building (Building-2) with mechanical ventilation and a natural ventilation system, respectively. Both buildings were located at the campus of University Kebangsaan Malaysia. The concentration of indoor radon was measured at 25 sampling stations using a radon detector model DOSEman PRO. The sampling was conducted for 8 h to represent daily working hours. A correlation of the radon concentration was made with the annual inhalation dose of the occupants at the indoor stations. The equilibrium factor and the annual effective dose on the lung cancer risks of each occupant were calculated at each sampling station. The average equilibrium equivalent radon measured in Building-1 and Building-2 was 2.33 ± 0.99 and 3.17 ± 1.74 Bqm-3, respectively. The equilibrium factor for Building 1 ranged from 0.1053 to 0.2273, and it ranged from 0.1031 to 0.16 for Building 2. The average annual inhalation doses recorded at Building-1 and Building-2 were 0.014 ± 0.005 mSv y-1and 0.020 ± 0.013 mSv y-1, respectively. The annual effective dose for Building-1 was 0.034 ± 0.012 mSv y-1, and it was 0.048 ± 0.031 mSv y-1for Building-2. The values of equilibrium equivalent radon concentration for both buildings were below the standard recommended by the International Commission on Radiological Protection (ICRP). However, people may have different radon tolerance levels. Therefore, the inhalation of the radon concentration can pose a deleterious health effect for people in an indoor environment.
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