Integrated Assessment of Heavy Metal Contamination in Sediments from a Coastal Industrial Basin, NE China

The purpose of this study is to investigate the current status of metal pollution of the sediments from urban-stream, estuary and Jinzhou Bay of the coastal industrial city, NE China. Forty surface sediment samples from river, estuary and bay and one sediment core from Jinzhou bay were collected and analyzed for heavy metal concentrations of Cu, Zn, Pb, Cd, Ni and Mn. The data reveals that there was a remarkable change in the contents of heavy metals among the sampling sediments, and all the mean values of heavy metal concentration were higher than the national guideline values of marine sediment quality of China (GB 18668-2002). This is one of the most polluted of the world’s impacted coastal systems. Both the correlation analyses and geostatistical analyses showed that Cu, Zn, Pb and Cd have a very similar spatial pattern and come from the industrial activities, and the concentration of Mn mainly caused by natural factors. The estuary is the most polluted area with extremely high potential ecological risk; however the contamination decreased with distance seaward of the river estuary. This study clearly highlights the urgent need to make great efforts to control the industrial emission and the exceptionally severe heavy metal pollution in the coastal area, and the immediate measures should be carried out to minimize the rate of contamination, and extent of future pollution problems

Increased Membrane Cholesterol in Lymphocytes Diverts T-Cells toward an Inflammatory Response

Cell signaling for T-cell growth, differentiation, and apoptosis is initiated in the cholesterol-rich microdomains of the plasma membrane known as lipid rafts. Herein, we investigated whether enrichment of membrane cholesterol in lipid rafts affects antigen-specific CD4 T-helper cell functions. Enrichment of membrane cholesterol by 40–50% following squalene administration in mice was paralleled by an increased number of resting CD4 T helper cells in periphery. We also observed sensitization of the Th1 differentiation machinery through co-localization of IL-2Rα, IL-4Rα, and IL-12Rβ2 subunits with GM1 positive lipid rafts, and increased STAT-4 and STAT-5 phosphorylation following membrane cholesterol enrichment. Antigen stimulation or CD3/CD28 polyclonal stimulation of membrane cholesterol-enriched, resting CD4 T-cells followed a path of Th1 differentiation, which was more vigorous in the presence of increased IL-12 secretion by APCs enriched in membrane cholesterol. Enrichment of membrane cholesterol in antigen-specific, autoimmune Th1 cells fostered their organ-specific reactivity, as confirmed in an autoimmune mouse model for diabetes. However, membrane cholesterol enrichment in CD4+ Foxp3+ T-reg cells did not alter their suppressogenic function. These findings revealed a differential regulatory effect of membrane cholesterol on the function of CD4 T-cell subsets. This first suggests that membrane cholesterol could be a new therapeutic target to modulate the immune functions, and second that increased membrane cholesterol in various physiopathological conditions may bias the immune system toward an inflammatory Th1 type response

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India)

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. Highlights The effectiveness of existing river water quality monitoring network is assessed Significance of seasonal redesign of the monitoring network is demonstrated Rationalization of water quality parameters is performed in a statistical framework