Bioavailability in soils

The consumption of locally-produced vegetables by humans may be an important exposure pathway for soil contaminants in many urban settings and for agricultural land use. Hence, prediction of metal and metalloid uptake by vegetables from contaminated soils is an important part of the Human Health Risk Assessment procedure. The behaviour of metals (cadmium, chromium, cobalt, copper, mercury, molybdenum, nickel, lead and zinc) and metalloids (arsenic, boron and selenium) in contaminated soils depends to a large extent on the intrinsic charge, valence and speciation of the contaminant ion, and soil properties such as pH, redox status and contents of clay and/or organic matter. However, chemistry and behaviour of the contaminant in soil alone cannot predict soil-to-plant transfer. Root uptake, root selectivity, ion interactions, rhizosphere processes, leaf uptake from the atmosphere, and plant partitioning are important processes that ultimately govern the accumulation ofmetals and metalloids in edible vegetable tissues. Mechanistic models to accurately describe all these processes have not yet been developed, let alone validated under field conditions. Hence, to estimate risks by vegetable consumption, empirical models have been used to correlate concentrations of metals and metalloids in contaminated soils, soil physico-chemical characteristics, and concentrations of elements in vegetable tissues. These models should only be used within the bounds of their calibration, and often need to be re-calibrated or validated using local soil and environmental conditions on a regional or site-specific basis.Mike J. McLaughlin, Erik Smolders, Fien Degryse, and Rene Rietr

Tikhonov adaptively regularized gamma variate fitting to assess plasma clearance of inert renal markers

The Tk-GV model fits Gamma Variates (GV) to data by Tikhonov regularization (Tk) with shrinkage constant, λ, chosen to minimize the relative error in plasma clearance, CL (ml/min). Using 169Yb-DTPA and 99mTc-DTPA (n = 46, 8–9 samples, 5–240 min) bolus-dilution curves, results were obtained for fit methods: (1) Ordinary Least Squares (OLS) one and two exponential term (E1 and E2), (2) OLS-GV and (3) Tk-GV. Four tests examined the fit results for: (1) physicality of ranges of model parameters, (2) effects on parameter values when different data subsets are fit, (3) characterization of residuals, and (4) extrapolative error and agreement with published correction factors. Test 1 showed physical Tk-GV results, where OLS-GV fits sometimes-produced nonphysical CL. Test 2 showed the Tk-GV model produced good results with 4 or more samples drawn between 10 and 240 min. Test 3 showed that E1 and E2 failed goodness-of-fit testing whereas GV fits for t > 20 min were acceptably good. Test 4 showed CLTk-GV clearance values agreed with published CL corrections with the general result that CLE1 > CLE2 > CLTk-GV and finally that CLTk-GV were considerably more robust, precise and accurate than CLE2, and should replace the use of CLE2 for these renal markers