Environmental Science & Technology · 2012 · 343 citations · 31 references
PharmacyEnvironmental SciencesToxicologyBioavailabilityEnvironmental ToxicologyHeavy Metal ToxicologyArsenic ToxicologyEnvironmental Heavy Metal ExposureHeavy Metal BioaccumulationHeavy Metal ContaminationSoil ContaminationSoil PollutionArsenic Exposure AssessmentBioaccessibility AnalysisEnvironmental Arsenic ContaminationIngestion Pathway AnalysisMetalloid ContaminationPotentially Toxic ElementsSoil Heavy Metal AssessmentSoil Heavy Metal Testing
The relative bioavailability of arsenic, antimony, cadmium, and lead for the ingestion pathway was measured in 16 soils contaminated by either smelting or mining activities using a juvenile swine model. The soils contained 18 to 25,000 mg kg(-1) As, 18 to 60,000 mg kg(-1) Sb, 20 to 184 mg kg(-1) Cd, and 1460 to 40,214 mg kg(-1) Pb. The bioavailability in the soils was measured in kidney, liver, bone, and urine relative to soluble salts of the four elements. The variety of soil types, the total concentrations of the elements, and the range of bioavailabilities found were considered to be suitable for calibrating the in vitro Unified BARGE bioaccessibility method. The bioaccessibility test has been developed by the BioAccessibility Research Group of Europe (BARGE) and is known as the Unified BARGE Method (UBM). The study looked at four end points from the in vivo measurements and two compartments in the in vitro study ("stomach" and "stomach and intestine"). Using benchmark criteria for assessing the "fitness for purpose" of the UBM bioaccessibility data to act as an analogue for bioavailability in risk assessment, the study shows that the UBM met criteria on repeatability (median relative standard deviation value <10%) and the regression statistics (slope 0.8 to 1.2 and r-square > 0.6) for As, Cd, and Pb. The data suggest a small bias in the UBM relative bioaccessibility of As and Pb compared to the relative bioavailability measurements of 3% and 5% respectively. Sb did not meet the criteria due to the small range of bioaccessibility values found in the samples.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Robust regression using repeated medians
Andrew F. Siegel · Biometrika · 1982 · 580 citations