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Palmitic acid-1-C14 was given intravenously to volunteer subjects before, and toward the end of, 35–45 min of exercise. The fractional turnover rate and total turnover rates for plasma free fatty acids were greater during exercise. The concentration of free fatty acids in the plasma fell at the beginning of exercise, then rose and exceeded the resting levels. Immediately after exercise, there was a further abrupt rise and then another decline. The results indicate that exercise accelerates the efflux of plasma free fatty acids and then, secondarily, increases mobilization of free fatty acids from depots.

Dole's titrimetric method for determination of the free fatty acids of plasma has been modified to improve its specificity. The fatty acid solution which is to be titrated is first washed with 0.05 per cent H2SO4 and thus freed of lactic acid and of an acetone-insoluble material which interferes. With this change, the Dole procedure yields results which agree well with those of Gordon's method.

Most of currently reported models for predicting PM(2.5) concentrations from satellite retrievals of aerosol optical depth are global methods without considering local variations, which might introduce significant biases into prediction results. In this paper, a geographically weighted regression model was developed to examine the relationship among PM(2.5), aerosol optical depth, meteorological parameters, and land use information. Additionally, two meteorological datasets, North American Regional Reanalysis and North American Land Data Assimilation System, were fitted into the model separately to compare their performances. The study area is centered at the Atlanta Metro area, and data were collected from various sources for the year 2003. The results showed that the mean local R(2) of the models using North American Regional Reanalysis was 0.60 and those using North American Land Data Assimilation System reached 0.61. The root mean squared prediction error showed that the prediction accuracy was 82.7% and 83.0% for North American Regional Reanalysis and North American Land Data Assimilation System in model fitting, respectively, and 69.7% and 72.1% in cross validation. The results indicated that geographically weighted regression combined with aerosol optical depth, meteorological parameters, and land use information as the predictor variables could generate a better fit and achieve high accuracy in PM(2.5) exposure estimation, and North American Land Data Assimilation System could be used as an alternative of North American Regional Reanalysis to provide some of the meteorological fields., (Copyright © 2012 Elsevier Inc. All rights reserved.)