Parsons Hsu (sweetssquare3)

When building the novel public mammalian toxicokinetic database (MamTKDB) we collected and included 3927 elimination half-lives (elimt1/2) for 1407 xenobiotics in various species (rat, human, mouse, dog, monkey, rabbit, cattle, pig, sheep, guinea pig, hamster, horse and goat) with specification of compartment (whole body, organ/tissue, cell type, medium) studied. Here we describe and analyse the collected data in MamTKDB 1.0. Most elimt1/2 are for humans and rats and their data differ in some ways whereas the rat data are mainly for pesticides, the human data are mainly for pharmaceuticals and environmental contaminants. There are also differences in types of compartments studied and in metabolites followed human elimt1/2 are mainly whole body based (i.e. based on blood plasma or excretion), animal data are additionally for various organs/tissues, cells or media. Contrary to human studies, animal studies regularly administrate radiolabeled (e.g. 14C) substances and distribution of both parent and eventual metd blood cells. MamTKDB 1.0 allows investigation on how certain chemical characteristics influence elimt1/2 and is a promising database for assessment of bioaccumulation potential.Metals are involved in glucose metabolism, and some may alter glycemic regulation. However, joint effects of essential and non-essential metals on glucose concentrations during pregnancy are unclear. This study explored the joint associations of pregnancy exposures to essential (copper, magnesium, manganese, selenium, zinc) and non-essential (arsenic, barium, cadmium, cesium, lead, mercury) metals with gestational glucose concentrations using 1,311 women enrolled 1999-2002 in Project Viva, a Boston, MA-area pregnancy cohort. The study measured erythrocyte metal concentrations from 1st trimester blood samples and used glucose concentrations measured 1 h after non-fasting 50-gram glucose challenge tests (GCT) from clinical gestational diabetes screening at 26-28 weeks gestation. Bayesian Kernel Machine Regression (BKMR) and quantile-based g-computation were applied to model the associations of metal mixtures-including their interactions-with glucose concentrations post-GCT. We tested for reproducibility of BKMR results using generalized additive models. The BKMR model showed an inverse U-shaped association for barium and a linear inverse association for mercury. Specifically, estimated mean glucose concentrations were highest around 75th percentile of barium concentrations [2.1 (95% confidence interval -0.2, 4.4) mg/dL higher comparing to the 25th percentile], and each interquartile range increase of erythrocyte mercury was associated with 1.9 mg/dL lower mean glucose concentrations (95% credible interval -4.2, 0.4). Quantile g-computation showed joint associations of all metals, essential-metals, and non-essential metals on gestational glucose concentrations were all null, however, we observed evidences of interaction for barium and lead. Overall, we found early pregnancy barium and mercury erythrocytic concentrations were associated with altered post-load glucose concentrations in later pregnancy, with potential interactions between barium and lead.There are global concerns about dietary exposure to metal(loid)s in foods. However, little is known about the relative contribution of rice versus fish to multiple metal(loid) exposure for the general population, especially in Asia where rice and fish are major food sources. We compared relative contributions of rice and fish consumption to multi-metal(loid) exposure on the city-scale (Nanjing) and province-scale in China. The effects of ingestion rate, metal(loid) level, and bioaccessibility were examined to calculate modeled risk from Cu, Zn, total As (TAs), inorganic As (iAs), Se, Cd, Pb, and methylmercury (MeHg). Metal(loid) levels in rice and fish samples collected from Nanjing City were generally low, except iAs. Metal(loid) bioaccessibilities in fish were higher than those in rice, except Se.