Statistical analysis of heavy metal concentrations in sediment was studied to understand the interrelationship between different parameters and also to identify probable source component in order to explain the pollution status of selected estuaries. Concentrations of heavy metals (Cu, Zn, Cd, Fe, Pb, Cr, Hg and Mn) were analyzed in sediments from Juru and Jejawi Estuaries in Malaysia with ten sampling points of each estuary. The results of multivariate statistical techniques showed that the two regions have different characteristics in terms of heavy metals selected and indicates that each region receives pollution from different sources. The results also showed that Fe, Mn, Cd, Hg, and Cu are responsible for large spatial variations explaining 51.15% of the total variance, whilst Zn and Pb explain only 18.93 of the total variance. This study illustrates the usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets to get better information about the heavy metal concentrations and design of monitoring network.
Water from 15 sampling stations in Tasik Chini (Chini Lake), Peninsular Malaysia were sampled for 12 months from September 2004 until August 2005 and analyzed for 11 metals including iron (Fe), aluminum (Al), manganese (Mn), barium (Ba), zinc (Zn), lead (Pb), copper (Cu), cadmium (Cd), nickel (Ni), chromium (Cr) and cobalt (Co). Results showed that the mean (min-max) metal concentrations (in micrograms per liter) in Tasik Chini waters for the 12 months sampling based on 15 sampling stations (in descending order) for Fe, Al, Mn, Ba, Zn, Pb, Cu and Cd were 794.84 (309.33-1609.07), 194.53 (62.37-665.93), 29.16 (16.68-79.85), 22.07 (15.64-29.71), 5.12 (2.224-6.553), 2.36 (1.165-4.240), 0.832 (0.362-1.443) and 0.421 (0.254-0.696) respectively. Concentration for three metals i.e. Ni, Cr and Co were too low and not detected by the graphite furnace Atomic Absorption Spectrophotometry (AAS). Comparison with various water quality standards showed that the mean metals concentration in surface water of Tasik Chini were low and within the range of natural background except for Fe and Al. In general, metal concentrations in Tasik Chini water varied temporally and spatially. The main factors influencing these metal concentrations in the water were the raining season and mining activities. Stations located at Tanjung Jerangking and Melai areas were the most effected due to those factors.
This study was undertaken to determine the effects of varied salinity regimes on the morphological traits (plant height, number of leaves, number of flowers, fresh and dry weight) and major mineral composition of 13 selected purslane accessions. Most of the morphological traits measured were reduced at varied salinity levels (0.0, 8, 16, 24 and 32 dS m(-1)), but plant height was found to increase in Ac1 at 16 dS m(-1) salinity, and Ac13 was the most affected accession. The highest reductions in the number of leaves and number of flowers were recorded in Ac13 at 32 dS m(-1) salinity compared to the control. The highest fresh and dry weight reductions were noted in Ac8 and Ac6, respectively, at 32 dS m(-1) salinity, whereas the highest increase in both fresh and dry weight was recorded in Ac9 at 24 dS m(-1) salinity compared to the control. In contrast, at lower salinity levels, all of the measured mineral levels were found to increase and later decrease with increasing salinity, but the performance of different accessions was different depending on the salinity level. A dendrogram was also constructed by UPGMA based on the morphological traits and mineral compositions, in which the 13 accessions were grouped into 5 clusters, indicating greater diversity among them. A three-dimensional principal component analysis also confirmed the output of grouping from cluster analysis.
While associations between trace elements and heavy metals with prostate cancer are still debatable, they have been considered as risk factors for prostate cancer. Thus, this study aimed to detect any links between selected minerals and heavy metals including Se, Zn, Cu, Mn and Fe with prostate cancer. A case control study was carried out among 100 subjects (case n=50, control n=50), matched for age and ethnicity. Trace elements and heavy metals level in hair and nail samples were determined by ICP-MS. Mean selenium levels in hair and nail of the cases were significantly lower as compared to controls. A similar trend was noted for zinc in both hair and nail samples, whereas the mean level of copper was significantly higher in cases than controls. Similar elevation was noted for iron and manganese (p<0.05 for all parameters). Low levels of selenium and zinc and high levels of copper, iron and manganese appear to be associated with the risk of prostate cancer. Further studies to elucidate the causal mechanisms and appropriate chemopreventive measures are needed.