Evaluation of extractants for estimation of the phytoavailable trace metals in soils

Despite its environmental (and financial) importance, there is no agreement in the literature as to which extractant most accurately estimates the phytoavailability of trace metals in soils. A large dataset was taken from the literature, and the effectiveness of various extractants to predict the phytoavailability of Cd, Zn, Ni, Cu, and Pb examined across a range of soil types and contamination levels. The data suggest that generally, the total soil trace metal content, and trace metal concentrations determined by complexing agents (such as the widely used DTPA and EDTA extractants) or acid extractants (such as 0.1 M HCl and the Mehlich 1 extractant) are only poorly correlated to plant phytoavailability. Whilst there is no consensus, it would appear that neutral salt extractants (such as 0.01 M CaCl2 and 0.1 M NaNO3) provide the most useful indication of metal phytoavailability across a range of metals of interest, although further research is required.

Bioelectrical impedance analysis for the estimation of body composition in rats

Bioelectrical impedance analysis (BIA) was used to assess body composition in rats fed on either standard laboratory diet or on a high-fat diet designed to induce obesity. Bioelectrical impedance analysis predictions of total body water and thus fat-free mass (FFM) for the group mean values were generally within 5% of the measured values by tritiated water ((H2O)-H-3) dilution. The limits of agreement for the procedure were, however, large, approximately +/-25%, limiting the applicability of the technique for measurement of body composition in individual animals.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations

Background From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates across the populations. Methods In men and women aged 35-64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, body-mass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.

Comparative analysis of dendritic cell density and total number in commonly transplanted organs: morphometric estimation in normal mice

Dendritic cells (DC) are considered to be the major cell type responsible for induction of primary immune responses. While they have been shown to play a critical role in eliciting allosensitization via the direct pathway, there is evidence that maturational and/or activational heterogeneity between DC in different donor organs may be crucial to allograft outcome. Despite such an important perceived role for DC, no accurate estimates of their number in commonly transplanted organs have been reported. Therefore, leukocytes and DC were visualized and enumerated in cryostat sections of normal mouse (C57BL/10, B10.BR, C3H) liver, heart, kidney and pancreas by immunohistochemistry (CD45 and MHC class II staining, respectively). Total immunopositive cell number and MHC class II+ cell density (C57BL/10 mice only) were estimated using established morphometric techniques - the fractionator and disector principles, respectively. Liver contained considerably more leukocytes (similar to 5-20 x 10(6)) and DC (similar to 1-3 x 10(6)) than the other organs examined (pancreas: similar to 0.6 x 10(6) and similar to 0.35 x 10(6): heart: similar to 0.8 x 10(6) and similar to 0.4 x 10(6); kidney similar to 1.2 x 10(6) and 0.65 x 10(6), respectively). In liver, DC comprised a lower proportion of all leukocytes (similar to 15-25%) than in the other parenchymal organs examined (similar to 40-60%). Comparatively, DC density in C57BL/10 mice was heart > kidney > pancreas much greater than liver (similar to 6.6 x 10(6), 5 x 10(6), 4.5 x 10(6) and 1.1 x 10(6) cells/cm(3), respectively). When compared to previously published data on allograft survival, the results indicate that the absolute number of MHC class II+ DC present in a donor organ is a poor predictor of graft outcome. Survival of solid organ allografts is more closely related to the density of the donor DC network within the graft. (C) 2000 Elsevier Science B.V. All rights reserved.

Estimation of crystalline phase present in the glucose crystal-solution mixture by water activity measurement

The amount of crystalline fraction present in monohydrate glucose crystal-solution mixture up to 110% crystal in relation to solution (crystal:solution=110:100) was determined by water activity measurement. It was found that the water activity had a strong linear correlation (R-2=0.994) with the amount of glucose present above saturation. Difference in the water activities of the crystal-solution mixture (a(w1)) and the supersaturated solution (a(w2)) by re-dissolving the crystalline fraction allowed calculation of the amount of crystalline phase present (DeltaG) in the mixture by an equation DeltaG=846.97(a(w1)-a(w2)). Other methods such as Raoult's, Norrish and Money-Born equations were also tested for the prediction of water activity of supersaturated glucose solution. (C) 2003 Swiss Society of Food Science and Technology. Published by Elsevier Science Ltd. All rights reserved.

Predicting sheetwash and rill erosion over the Australian continent

Soil erosion is a major environmental issue in Australia. It reduces land productivity and has off-site effects of decreased water quality. Broad-scale spatially distributed soil erosion estimation is essential for prioritising erosion control programs and as a component of broader assessments of natural resource condition. This paper describes spatial modelling methods and results that predict sheetwash and rill erosion over the Australian continent using the revised universal soil loss equation (RUSLE) and spatial data layers for each of the contributing environmental factors. The RUSLE has been used before in this way but here we advance the quality of estimation. We use time series of remote sensing imagery and daily rainfall to incorporate the effects of seasonally varying cover and rainfall intensity, and use new digital maps of soil and terrain properties. The results are compared with a compilation of Australian erosion plot data, revealing an acceptable consistency between predictions and observations. The modelling results show that: (1) the northern part of Australia has greater erosion potential than the south; (2) erosion potential differs significantly between summer and winter; (3) the average erosion rate is 4.1 t/ha. year over the continent and about 2.9 x 10(9) tonnes of soil is moved annually which represents 3.9% of global soil erosion from 5% of world land area; and (4) the erosion rate has increased from 4 to 33 times on average for agricultural lands compared with most natural vegetated lands.

Optimal estimation of one-parameter quantum channels

We explore the task of optimal quantum channel identification and in particular, the estimation of a general one-parameter quantum process. We derive new characterizations of optimality and apply the results to several examples including the qubit depolarizing channel and the harmonic oscillator damping channel. We also discuss the geometry of the problem and illustrate the usefulness of using entanglement in process estimation.

Optimal quantum measurements for phase-shift estimation in optical interferometry

Quantum information theory, applied to optical interferometry, yields a 1/n scaling of phase uncertainty Delta phi independent of the applied phase shift phi, where n is the number of photons in the interferometer. This 1/n scaling is achieved provided that the output state is subjected to an optimal phase measurement. We establish this scaling law for both passive (linear) and active (nonlinear) interferometers and identify the coefficient of proportionality. Whereas a highly nonclassical state is required to achieve optimal scaling for passive interferometry, a classical input state yields a 1/n scaling of phase uncertainty for active interferometry.

Estimation of the pore size of the large-conductance mechanosensitive ion channel of Escherichia coli

The open channel diameter of Escherichia coli recombinant large-conductance mechanosensitive ion channels (MscL) was estimated using the model of Hille (Hille, B. 1968. Pharmacological modifications of the sodium channels of frog nerve. J. Gen. Physiol. 51:199-219)that relates the pore size to conductance. Based on the MscL conductance of 3.8 nS, and assumed pore lengths, a channel diameter of 34 to 46 Angstrom was calculated. To estimate the pore size experimentally, the effect of large organic ions on the conductance of MscL was examined. Poly-L-lysines (PLLs) with a diameter of 37 Angstrom or larger significantly reduced channel conductance, whereas spermine (similar to 15 Angstrom), PLL19 (similar to 25 Angstrom) and 1,1'-bis-(3-(1'-methyl-(4,4'-bipyridinium)-1-yl)-propyl)-4,4'-bipyridinium (similar to 30 Angstrom) had no effect. The smaller organic ions putrescine, cadaverine, spermine, and succinate all permeated the channel. We conclude that the open pore diameter of the MscL is similar to 40 Angstrom, indicating that the MscL has one of the largest channel pores yet described. This channel diameter is consistent with the proposed homohexameric model of the MscL.