Displaying publications 101 - 120 of 142 in total

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  1. Predicting arsenic solubility in contaminated soils using isotopic dilution techniques
    Tye AM, Young SD, Crout NM, Zhang H, Preston S, Bailey EH, et al.
    Environ Sci Technol, 2002 Mar 1;36(5):982-8.
    PMID: 11924544
    An isotopic dilution assay was developed to measure radiolabile As concentration in a diverse range of soils (pH 3.30-7.62; % C = 1.00-6.55). Soils amended with 50 mg of As kg(-1) (as Na2HAsO4 x 7H2O) were incubated for over 800 d in an aerated "microcosm" experiment. After 818 d, radiolabile As ranged from 27 to 57% of total applied As and showed a pH-dependent increase above pH 6. The radiolabile assay was also applied to three sets of soils historically contaminated with sewage sludge or mine-spoil. Results reflected the various geochemical forms in which the arsenic was present. On soils from a sewage disposal facility, radiolabile arsenate ranged from 3 to 60% of total As; mean lability was lower than in the equivalent pH range of the microcosm soils, suggesting occlusion of As into calcium phosphate compounds in the sludge-amended soils. In soils from mining areas in the U.K. and Malaysia, radiolabile As accounted for 0.44-19% of total As. The lowest levels of lability were associated with extremely large As concentrations, up to 17,000 mg kg(-1), from arsenopyrite. Soil pore water was extracted from the microcosm experiment and speciated using "GEOCHEM". The solid<==>solution equilibria of As in the microcosm soils was described by a simple model based on competition between HAsO4(2-) and HPO4(2-) for "labile" adsorption sites.
    Matched MeSH terms: Mining
  2. Fulltext Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset
    M. Hafiz Fazren Abd Rahman, Wan Wardatul Amani Wan Salim, M. Firdaus Abd-Wahab
    Biological and Natural Resources Engineering Journal, 2020;3(1):48-61.
    MyJurnal
    The steep rise of cases pertaining to Diabetes Mellitus (DM) condition among global population has encouraged extensive researches on DM, which led to exhaustive accumulation of data related to DM. In this case, data mining and machine learning applications prove to be a powerful tool in transforming data into meaningful deductions. Several machine learning tools have shown great promise in diabetes classification. However, challenges remain in obtaining an accurate model suitable for real world application. Most disease risk-prediction modelling are found to be specific to a local population. Moreover, real-world data are likely to be complex, incomplete and unorganized, thus, convoluting efforts to develop models around it. This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using three different machine learning algorithms; Decision Tree, Support Vector Machine and Naïve Bayes. Data pre-processing methods are utilised to the raw data to improve model performance. This study uses datasets obtained from the IIUM Medical Centre for classification and modelling. Ultimately, the performance of each model is validated, evaluated and compared based on several statistical metrics that measures accuracy, precision, sensitivity and efficiency. This study shows that the random forest model provides the best overall prediction performance in terms of accuracy (0.87), sensitivity (0.9), specificity (0.8), precision (0.9), F1-score (0.9) and AUC value (0.93) (Normal).
    Matched MeSH terms: Data Mining
  3. Fulltext YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis
    Teng S, Khong KW, Pahlevan Sharif S, Ahmed A
    JMIR Public Health Surveill, 2020 10 01;6(4):e19618.
    PMID: 33001036 DOI: 10.2196/19618
    BACKGROUND: Poor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities.

    OBJECTIVE: The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters' perceptions and sentiments of healthy eating through text mining techniques.

    METHODS: This paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.

    RESULTS: With a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.

    CONCLUSIONS: This study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.

    Matched MeSH terms: Data Mining
  4. Water Quality Modelling for River Activities Management: Example from a Low- and Middle-Income Country
    Zahidi I, Wilson G, Brown K, Hou FKK
    J Health Pollut, 2020 Dec;10(28):201207.
    PMID: 33324504 DOI: 10.5696/2156-9614-10.28.201207
    Background: Rivers are susceptible to pollution and water pollution is a growing problem in low- and middle-income countries (LMIC) with rapid development and minimal environmental protections. There are universal pollutant threshold values, but they are not directly linked to river activities such as sand mining and aquaculture. Water quality modelling can support assessments of river pollution and provide information on this important environmental issue.

    Objectives: The objective of the present study was to demonstrate water quality modelling methodology in reviewing existing policies for Malaysian river catchments based on an example case study.

    Methods: The MIKE 11 software developed by the Danish Hydraulic Institute was used to model the main pollutant point sources within the study area - sand mining and aquaculture. Water quality data were obtained for six river stations from 2000 to 2015. All sand mining and aquaculture locations and approximate production capacities were quantified by ground survey. Modelling of the sand washing effluents was undertaken with the advection-dispersion module due to the nature of the fine sediment. Modelling of the fates of aquaculture deposits required both advection-dispersion and Danish Hydraulic Institute ECO Lab modules to simulate the detailed interactions between water quality determinants.

    Results: According to the Malaysian standard, biochemical oxygen command (BOD) and ammonium (NH4) parameters fell under Class IV at most of the river reaches, while the dissolved oxygen (DO) parameter varied between Classes II to IV. Total suspended solids (TSS) fell within Classes IV to V along the mid river reaches of the catchment.

    Discussion: Comparison between corresponding constituents and locations showed that the water quality model reproduced the long-term duration exceedance for the main body of the curves. However, the water quality model underestimated the infrequent high concentration observations. A standard effluent disposal was proposed for the development of legislation and regulations by authorities in the district that could be replicated for other similar catchments.

    Conclusions: Modelling pollutants enables observation of trends over the years and the percentage of time a certain class is exceeded for each individual pollutant. The catchment did not meet Class II requirements and may not be able to reach Class I without extensive improvements in the quality and reducing the quantity of both point and non-point effluent sources within the catchment.

    Competing Interests: The authors declare no competing financial interests.

    Matched MeSH terms: Mining
  5. Fulltext Radiological hazard associated with amang processing industry in Peninsular Malaysia and its environmental impacts
    Sanusi MSM, Ramli AT, Hashim S, Lee MH
    Ecotoxicol Environ Saf, 2021 Jan 15;208:111727.
    PMID: 33396058 DOI: 10.1016/j.ecoenv.2020.111727
    Continuous depletion in tin productions has led to a newly emerging industry that is a tin by-product (amang) processing industry to harness mega tons of tin by-products produced in the past. Amang composed of profitable multi-heavy minerals and rare-earth elements. With poorly established safety and health practices in operating plant, amang poses extremely high radioactivity problem associated with high occupational ionizing radiation exposures to workers and continuously impacting the local environment with radioactive contamination from industrial effluent and solid waste into lithosphere and water bodies. The radioactivity level of 238U and 232Th series in the mineral varies from few hundreds up to ~200,000 and ~400,000 Bq kg-1 respectively and are potential to yield more than ~ 30,000 nGy h-1 of gamma (γ) radiation exposure to plant workers. The study found out that for 8 h of work time, a worker is estimated to receive an average effective dose of 0.1 mSv per day from external γ radiation source with a maximum up to 2 mSv per day for extreme exposure situation. Interferences of different exposure routes for examples inhalation of equivalent equilibrium concentration (ECC) of 222Rn and 220Rn progenies and airborne long-lived α particles from the dusty working environment could pose a higher total effective dose as much as 5 mSv per day and 115 mSv per year. The value is 5 times higher than the annual dose limit for designated radiation worker (20 mSv) in Peninsular Malaysia. The study found that 41% of the total received an effective dose received by a worker is contributed by 222Rn, 32% of airborne particulates and dust, 23% from external γ exposure and 4% from 220Rn. Based on radioecological risk assessment, the study found out that the aquatic environment is the highly exposed group to ionizing radiation from industrial effluent discharge and sand residues. With the impotent establishment of radiation protection in the industry, plus the country newly introduced long-term plan to revive tin mining as well as its accessory amang mineral, it is necessary for the government to harmonize current regulation to improve the worker safety and health as well as sustaining local environment.
    Matched MeSH terms: Mining
  6. The influence of industrial medicine on economic geography
    Ffrench G
    Trans Soc Occup Med, 1972 Oct;22(4):109-15.
    PMID: 4565477
    Matched MeSH terms: Mining
  7. Assessing drivers of benthic macroinvertebrate community structure in African highland streams: An exploration using multivariate analysis
    Dalu T, Wasserman RJ, Tonkin JD, Alexander ME, Dalu MTB, Motitsoe SN, et al.
    Sci Total Environ, 2017 Dec 01;601-602:1340-1348.
    PMID: 28605853 DOI: 10.1016/j.scitotenv.2017.06.023
    Understanding the drivers of community structure is fundamental for adequately managing ecosystems under global change. Here we used a large dataset of eighty-four headwater stream sites in three catchments in the Eastern Highlands of Zimbabwe, which represent a variety of abiotic conditions and levels of impairment, to examine the drivers of benthic macroinvertebrate community structure. We focused our assessment on macroinvertebrate family level community composition and functional feeding group classifications. Taxonomic richness was weakly positively correlated with ammonium, phosphates and pH, and weakly negatively correlated with detrital cover and dissolved oxygen. Measured abiotic variables, however, had limited influence on both macroinvertebrate diversity and functional feeding group structure, with the exception of ammonium, channel width and phosphates. This reflected the fact that many macroinvertebrate families and functional feeding guilds were well represented across a broad range of habitats. Predatory macroinvertebrates were relatively abundant, with collector-filterers having the lowest relative abundances. The findings of the study suggest that for certain ecological questions, a more detailed taxonomic resolution may be required to adequately understand the ecology of aquatic macroinvertebrates within river systems. We further recommend management and conservation initiatives on the Save River system, which showed significant impact from catchment developmental pressures, such as urbanisation, agriculture and illegal mining.
    Matched MeSH terms: Mining
  8. Geochemical characteristics of rare earth elements in different types of soil: A chemometric approach
    Khan AM, Behkami S, Yusoff I, Md Zain SB, Bakar NKA, Bakar AFA, et al.
    Chemosphere, 2017 Oct;184:673-678.
    PMID: 28628904 DOI: 10.1016/j.chemosphere.2017.06.032
    Rare earth elements (REEs) are becoming significant due to their huge applications in many industries, large-scale mining and refining activities. Increasing usage of such metals pose negative environmental impacts. In this research ICP-MS has been used to analyze soil samples collected from former ex-mining areas in the depths of 0-20 cm, 21-40 cm, and 41-60 cm of residential, mining, natural, and industrial areas of Perak. Principal component analysis (PCA) revealed that soil samples taken from different mining, industrial, residential, and natural areas are separated into four clusters. It was observed that REEs were abundant in most of the samples from mining areas. Concentration of the rare elements decrease in general as we move from surface soil to deeper soils.
    Matched MeSH terms: Mining
  9. Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models
    Azareh A, Rahmati O, Rafiei-Sardooi E, Sankey JB, Lee S, Shahabi H, et al.
    Sci Total Environ, 2019 Mar 10;655:684-696.
    PMID: 30476849 DOI: 10.1016/j.scitotenv.2018.11.235
    Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.
    Matched MeSH terms: Data Mining
  10. Cyanide degradation by pseudomonas pseudoalcaligenes strain W2 Isolated from mining effluent
    Belinda Tiong, Zaratulnur Mohd Bahari, Nor Sahslin Irwan Shah Lee, Zaharah Ibrahim, Shafinaz Shahir
    Sains Malaysiana, 2015;44:233-238.
    Cyanide is highly toxic to the living organisms as it inhibits respiration system in the cell mitochondria. Cyanide is commonly used in gold extraction process and its discharge into the environment not only causes pollution but it also brings harm to the surrounding population. Chemical treatment is expensive and the use of hazardous compound can exacerbate the problem. Biodegradation offers cheap and safe alternative as it overcomes the problems faced by chemical treatment. In this study, indigenous bacteria from mining wastewater were isolated. Cyanide degradation was done via shake flask method. A bacterium, designated W2 was found able to grow in the mining wastewater. 16S rRNA analysis identified the strain as Pseudomonas pseudoalcaligenes which could tolerate up to 39 mg/L cyanide concentration and growth was depleted at 52 mg/L. 60% cyanide degradation was achieved in wastewater containing medium. End-product analysis from high performance liquid chromatography (HPLC) detected formamide implicating the role of cyanide hydratase in cyanide degradation. It can be concluded that P. pseudoalcaligenes is capable of biodegrading cyanide and its potential in wastewater treatment containing cyanide is feasible.
    Matched MeSH terms: Mining
  11. Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm
    Bui DT, Khosravi K, Karimi M, Busico G, Khozani ZS, Nguyen H, et al.
    Sci Total Environ, 2020 May 01;715:136836.
    PMID: 32007881 DOI: 10.1016/j.scitotenv.2020.136836
    Groundwater resources constitute the main source of clean fresh water for domestic use and it is essential for food production in the agricultural sector. Groundwater has a vital role for water supply in the Campanian Plain in Italy and hence a future sustainability of the resource is essential for the region. In the current paper novel data mining algorithms including Gaussian Process (GP) were used in a large groundwater quality database to predict nitrate (contaminant) and strontium (potential future increasing) concentrations in groundwater. The results were compared with M5P, random forest (RF) and random tree (RT) algorithms as a benchmark to test the robustness of the modeling process. The dataset includes 246 groundwater quality samples originating from different wells, municipals and agricultural. It was divided for the modeling process into two subgroups by using the 10-fold cross validation technique including 173 samples for model building (training dataset) and 73 samples for model validation (testing dataset). Different water quality variables including T, pH, EC, HCO3-, F-, Cl-, SO42-, Na+, K+, Mg2+, and Ca2+ have been used as an input to the models. At first stage, different input combinations have been constructed based on correlation coefficient and thus the optimal combination was chosen for the modeling phase. Different quantitative criteria alongside with visual comparison approach have been used for evaluating the modeling capability. Results revealed that to obtain reliable results also variables with low correlation should be considered as an input to the models together with those variables showing high correlation coefficients. According to the model evaluation criteria, GP algorithm outperforms all the other models in predicting both nitrate and strontium concentrations followed by RF, M5P and RT, respectively. Result also revealed that model's structure together with the accuracy and structure of the data can have a relevant impact on the model's results.
    Matched MeSH terms: Data Mining
  12. The Extended Polydimensional Immunome Characterization (EPIC) web-based reference and discovery tool for cytometry data
    Yeo JG, Wasser M, Kumar P, Pan L, Poh SL, Ally F, et al.
    Nat Biotechnol, 2020 06;38(6):679-684.
    PMID: 32440006 DOI: 10.1038/s41587-020-0532-1
    Matched MeSH terms: Data Mining
  13. Assessment of impact of urbanisation on background radiation exposure and human health risk estimation in Kuala Lumpur, Malaysia
    Sanusi MSM, Ramli AT, Hassan WMSW, Lee MH, Izham A, Said MN, et al.
    Environ Int, 2017 07;104:91-101.
    PMID: 28412010 DOI: 10.1016/j.envint.2017.01.009
    Kuala Lumpur has been undergoing rapid urbanisation process, mainly in infrastructure development. The opening of new township and residential in former tin mining areas, particularly in the heavy mineral- or tin-bearing alluvial soil in Kuala Lumpur, is a contentious subject in land-use regulation. Construction practices, i.e. reclamation and dredging in these areas are potential to enhance the radioactivity levels of soil and subsequently, increase the existing background gamma radiation levels. This situation is worsened with the utilisation of tin tailings as construction materials apart from unavoidable soil pollutions due to naturally occurring radioactive materials in construction materials, e.g. granitic aggregate, cement and red clay brick. This study was conducted to assess the urbanisation impacts on background gamma radiation in Kuala Lumpur. The study found that the mean value of measured dose rate was 251±6nGyh-1(156-392nGyh-1) and 4 times higher than the world average value. High radioactivity levels of238U (95±12Bqkg-1),232Th (191±23Bqkg-1,) and40K (727±130Bqkg-1) in soil were identified as the major source of high radiation exposure. Based on statistical ANOVA, t-test, and analyses of cumulative probability distribution, this study has statistically verified the dose enhancements in the background radiation. The effective dose was estimated to be 0.31±0.01mSvy-1per man. The recommended ICRP reference level (1-20mSvy-1) is applicable to the involved existing exposure situation in this study. The estimated effective dose in this study is lower than the ICRP reference level and too low to cause deterministic radiation effects. Nevertheless based on estimations of lifetime radiation exposure risks, this study found that there was small probability for individual in Kuala Lumpur being diagnosed with cancer and dying of cancer.
    Matched MeSH terms: Mining
  14. Radioecological impacts of tin mining
    Aliyu AS, Mousseau TA, Ramli AT, Bununu YA
    Ambio, 2015 Dec;44(8):778-87.
    PMID: 26093469 DOI: 10.1007/s13280-015-0677-1
    The tin mining activities in the suburbs of Jos, Plateau State, Nigeria, have resulted in technical enhancement of the natural background radiation as well as higher activity concentrations of primordial radionuclides in the topsoil of mining sites and their environs. Several studies have considered the radiological human health risks of the mining activity; however, to our knowledge no documented study has investigated the radiological impacts on biota. Hence, an attempt is made to assess potential hazards using published data from the literature and the ERICA Tool. This paper considers the effects of mining and milling on terrestrial organisms like shrubs, large mammals, small burrowing mammals, birds (duck), arthropods (earth worm), grasses, and herbs. The dose rates and risk quotients to these organisms are computed using conservative values for activity concentrations of natural radionuclides reported in Bitsichi and Bukuru mining areas. The results suggest that grasses, herbs, lichens, bryophytes and shrubs receive total dose rates that are of potential concern. The effects of dose rates to specific indicator species of interest are highlighted and discussed. We conclude that further investigation and proper regulations should be set in place in order to reduce the risk posed by the tin mining activity on biota. This paper also presents a brief overview of the impact of mineral mining on biota based on documented literature for other countries.
    Matched MeSH terms: Mining
  15. Development of ESTs and data mining of pineapple EST-SSRs
    Ong WD, Voo CL, Kumar SV
    Mol Biol Rep, 2012 May;39(5):5889-96.
    PMID: 22207174 DOI: 10.1007/s11033-011-1400-3
    Improving the quality of the non-climacteric fruit, pineapple, is possible with information on the expression of genes that occur during the process of fruit ripening. This can be made known though the generation of partial mRNA transcript sequences known as expressed sequence tags (ESTs). ESTs are useful not only for gene discovery but also function as a resource for the identification of molecular markers, such as simple sequence repeats (SSRs). This paper reports on firstly, the construction of a normalized library of the mature green pineapple fruit and secondly, the mining of EST-SSRs markers using the newly obtained pineapple ESTs as well as publically available pineapple ESTs deposited in GenBank. Sequencing of the clones from the EST library resulted in 282 good sequences. Assembly of sequences generated 168 unique transcripts (UTs) consisting of 34 contigs and 134 singletons with an average length of ≈500 bp. Annotation of the UTs categorized the known proteins transcripts into the three ontologies as: molecular function (34.88%), biological process (38.43%), and cellular component (26.69%). Approximately 7% (416) of the pineapple ESTs contained SSRs with an abundance of trinucleotide SSRs (48.3%) being identified. This was followed by dinucleotide and tetranucleotide SSRs with frequency of 46 and 57%, respectively. From these EST-containing SSRs, 355 (85.3%) matched to known proteins while 133 contained flanking regions for primer design. Both the ESTs were sequenced and the mined EST-SSRs will be useful in the understanding of non-climacteric ripening and the screening of biomarkers linked to fruit quality traits.
    Matched MeSH terms: Data Mining*
  16. Geochemical and mineralogical assessment of sedimentary limestone mine waste and potential for mineral carbonation
    Mohd Isha NS, Mohd Kusin F, Ahmad Kamal NM, Syed Hasan SNM, Molahid VLM
    Environ Geochem Health, 2021 May;43(5):2065-2080.
    PMID: 33392897 DOI: 10.1007/s10653-020-00784-z
    This paper attempts to evaluate the mineralogical and chemical composition of sedimentary limestone mine waste alongside its mineral carbonation potential. The limestone mine wastes were recovered as the waste materials after mining and crushing processes and were analyzed for mineral, major and trace metal elements. The major mineral composition discovered was calcite (CaCO3) and dolomite [CaMg(CO3)2], alongside other minerals such as bustamite [(Ca,Mn)SiO3] and akermanite (Ca2MgSi2O7). Calcium oxide constituted the greatest composition of major oxide components of between 72 and 82%. The presence of CaO facilitated the transformation of carbon dioxide into carbonate form, suggesting potential mineral carbonation of the mine waste material. Geochemical assessment indicated that mean metal(loid) concentrations were found in the order of Al > Fe > Sr > Pb > Mn > Zn > As > Cd > Cu > Ni > Cr > Co in which Cd, Pb and As exceeded some regulatory guideline values. Ecological risk assessment demonstrated that the mine wastes were majorly influenced by Cd as being classified having moderate risk. Geochemical indices depicted that Cd was moderately accumulated and highly enriched in some of the mine waste deposited areas. In conclusion, the limestone mine waste material has the potential for sequestering CO2; however, the presence of some trace metals could be another important aspect that needs to be considered. Therefore, it has been shown that limestone mine waste can be regarded as a valuable feedstock for mineral carbonation process. Despite this, the presence of metal(loid) elements should be of another concern to minimize potential ecological implication due to recovery of this waste material.
    Matched MeSH terms: Mining*
  17. Radiation-induced chromosomal aberrations among TENORM workers: amang- and ilmenite-processing workers of Malaysia
    Kandar MZ, Bhari IB
    Mutat Res, 1996 Apr 13;351(2):157-61.
    PMID: 8622709
    The usefulness of peripheral human lymphocytes as a bioindicator for ionizing radiation effect was tested in a survey of Malaysian workers in two industries producing technologically enhanced naturally occurring radioactive material (TENORM). Workers in amang processing plants who have been with the plant for an average of 12.9 years and who were exposed to radioactive dust showed significantly higher frequencies of chromosomal aberration compared to control and even ilmenite-processing workers. Such frequency was not significantly different between workers in ilmenite-processing plant and control. The differences in duration of employment, occupational hygiene, together with the difference in the percentage of 'old' and 'new' aberrations among the groups sampled were used to explain the high chromosomal aberration frequency among amang workers. The presence of significantly high chromosome damage (dicentrics and fragments) in workers who were chronically exposed to doses below 50 mSv per year or 20 mSv per year averaged over 5 years (ICRP, 1991) provided additional experimental data on the dose-effect relationship at these low-dose ranges. The results confirm the usefulness of using human lymphocytes as a bioindicator for chronic exposure to ionizing radiation and in cases where physical radiation detectors are not available.
    Matched MeSH terms: Mining*
  18. Environmental geochemistry of the abandoned Mamut Copper Mine (Sabah) Malaysia
    van der Ent A, Edraki M
    Environ Geochem Health, 2018 Feb;40(1):189-207.
    PMID: 27848090 DOI: 10.1007/s10653-016-9892-3
    The Mamut Copper Mine (MCM) located in Sabah (Malaysia) on Borneo Island was the only Cu-Au mine that operated in the country. During its operation (1975-1999), the mine produced 2.47 Mt of concentrate containing approximately 600,000 t of Cu, 45 t of Au and 294 t of Ag, and generated about 250 Mt of overburden and waste rocks and over 150 Mt of tailings, which were deposited at the 397 ha Lohan tailings storage facility, 15.8 km from the mine and 980 m lower in altitude. The MCM site presents challenges for environmental rehabilitation due to the presence of large volumes of sulphidic minerals wastes, the very high rainfall and the large volume of polluted mine pit water. This indicates that rehabilitation and treatment is costly, as for example, exceedingly large quantities of lime are needed for neutralisation of the acidic mine pit discharge. The MCM site has several unusual geochemical features on account of the concomitant occurrence of acid-forming sulphide porphyry rocks and alkaline serpentinite minerals, and unique biological features because of the very high plant diversity in its immediate surroundings. The site hence provides a valuable opportunity for researching natural acid neutralisation processes and mine rehabilitation in tropical areas. Today, the MCM site is surrounded by protected nature reserves (Kinabalu Park, a World Heritage Site, and Bukit Hampuan, a Class I Forest Reserve), and the environmental legacy prevents de-gazetting and inclusion in these protected area in the foreseeable future. This article presents a preliminary geochemical investigation of waste rocks, sediments, secondary precipitates, surface water chemistry and foliar elemental uptake in ferns, and discusses these results in light of their environmental significance for rehabilitation.
    Matched MeSH terms: Mining*
  19. Fulltext First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene
    Mohamoud HS, Hussain MR, El-Harouni AA, Shaik NA, Qasmi ZU, Merican AF, et al.
    Comput Math Methods Med, 2014;2014:904052.
    PMID: 24723968 DOI: 10.1155/2014/904052
    GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.
    Matched MeSH terms: Data Mining/methods
  20. Molecular diversity of the ammonia-oxidizing bacteria community in disused tin-mining ponds located within Kampar, Perak, Malaysia
    Sow SL, Khoo G, Chong LK, Smith TJ, Harrison PL, Ong HK
    World J Microbiol Biotechnol, 2014 Feb;30(2):757-66.
    PMID: 24078113
    Disused tin-mining ponds make up a significant amount of water bodies in Malaysia particularly at the Kinta Valley in the state of Perak where tin-mining activities were the most extensive, and these abundantly available water sources are widely used in the field of aquaculture and agriculture. However, the natural ecology and physicochemical conditions of these ponds, many of which have been altered due to secondary post-mining activities, remains to be explored. As ammonia-oxidizing bacteria (AOB) are directly related to the nutrient cycles of aquatic environments and are useful bioindicators of environmental variations, the focus of this study was to identify AOBs associated with disused tin-mining ponds that have a history of different secondary activities in comparison to ponds which were left untouched and remained as part of the landscape. The 16S rDNA gene was used to detect AOBs in the sediment and water sampled from the three types of disused mining ponds, namely ponds without secondary activity, ponds that were used for lotus cultivation and post-aquaculture ponds. When the varying pond types were compared with the sequence and phylogenetic analysis of the AOB clone libraries, both Nitrosomonas and Nitrosospira-like AOB were detected though Nitrosospira spp. was seen to be the most ubiquitous AOB as it was present in all ponds types. However, AOBs were not detected in the sediments of idle ponds. Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture indicated the highest richness of AOBs. Canonical correspondence analysis indicated that among the physicochemical properties of the pond sites, TAN and nitrite were shown to be the main factors that influenced the community structure of AOBs in these disused tin-mining ponds.
    Matched MeSH terms: Mining*
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