Freely dissolved Organochlorine Pesticides (OCPs) and Polychlorinated Biphenyls (PCBs) along the Indus River Pakistan: Spatial pattern and Risk assessment

Freely dissolved OCPs and PCBs were measured by using polyethylene passive samplers at 15 sites during 2014 throughout the stretch of the Indus River to investigate the spatial pattern and risk assess. Levels (pg/L) of dissolved ∑OCPs and ∑PCBs ranged from 34 to 1600 and from 3 to 230. Among the detected OCPs, dissolved DDTs (p,p′-DDE, followed by p,p′-DDT) predominated with levels of 0.48 to 220 pg/L. The order of occurrence for other studied OCPs was as follows: HCB, endosulfans, chlordanes, and HCHs. Spatially, dissolved (pg/L) ∑OCPs varied (p \u3c 0.05) as the following: surface water of the alluvial riverine zone (ARZ) showed the highest levels (114) followed by the frozen mountain zone (FMZ) (52.9), low-lying zone (LLZ) (28.73), and wet mountain zone (WMZ) (14.43), respectively. However, our zone-wise PCB data did not exhibit significant differences (p \u3e 0.05). Principal component analysis/multilinear regression results showed pesticide usage in the crop/orchard fields and health sector, electric and electronic materials, and widespread industrial activities as the main source of OCPs and PCBs along the Indus River. Our results showed that OCPs and PCBs contaminated water intake, playing an important role towards the considerable cancer/non-cancer risk (HI and CR values) along the Indus River Flood-Plain

Organochlorine pesticides in surface soils from obsolete pesticide dumping ground in Hyderabad City, Pakistan:contamination levels and their potential for air-soil exchange

This study was conducted to examine organochlorine pesticides (OCPs) contamination levels in the surface soil and air samples together with air-soil exchange fluxes at an obsolete pesticide dumping ground and the associated areas from Hyderabad City, Pakistan. Among all the sampling sites, concentrations of OCPs in the soil and air samples were found highest in obsolete pesticide dumping ground, whereas dominant contaminants were dichlorodiphenyltrichloroethane (DDTs) (soil: 77-212,200 ng g(-1); air: 90,700 pg m(-3)) and hexachlorocyclohexane (HCHs) (soil: 43-4,090 ng g(-1); air: 97,400 pg m(-3)) followed by chlordane, heptachlor and hexachlorobenzene (HCB). OCPs diagnostic indicative ratios reflect historical use as well as fresh input in the study area. Moreover, the air and soil fugacity ratios (0.9-1.0) at the dumping ground reflecting a tendency towards net volatilization of OCPs, while at the other sampling sites, the fugacity ratios indicate in some cases deposition and in other cases volatilization. Elevated concentrations of DDTs and HCHs at pesticide dumping ground and its surroundings pose potential exposure risk to biological organisms, to the safety of agricultural products and to the human health. Our study thus emphasizes the need of spatio-temporal monitoring of OCPs at local and regional scale to assess and remediate the future adverse implications

Newborn Meconium and Urinary Metabolome Response to Maternal Gestational Diabetes Mellitus: A Preliminary Case–Control Study

Recently, the number of women suffering from gestational diabetes mellitus (GDM) has risen dramatically. GDM attracts increasing attention due to its potential harm to the heath of both the fetus and the mother. We designed this case–control study to investigate the metabolome response of newborn meconium and urine to maternal GDM. GDM mothers (<i>n</i> = 142) and healthy controls (<i>n</i> = 197) were recruited during June–July 2012 in Xiamen, China. The newborns’ metabolic profiles were acquired using liquid chromatography coupled to mass spectrometry. The data showed that meconium and urine metabolome patterns clearly discriminated GDM cases from controls. Fourteen meconium metabolic biomarkers and three urinary metabolic biomarkers were tentatively identified for GDM. Altered levels of various endogenous biomarkers revealed that GDM may induce disruptions in lipid metabolism, amino acid metabolism, and purine metabolism. An unbalanced lipid pattern is suspected to be a GDM-specific feature. Furthermore, the relationships between the potential biomarkers and GDM risk were evaluated by binary logistic regression and receiver operating characteristic analysis. A combined model of nine meconium biomarkers showed a great potential in diagnosing GDM-induced disorders