<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hillwalker, Wendy E</style></author><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bioaccessibility of metals in alloys: evaluation of three surrogate biofluids.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Pollut</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Pollut.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alloys</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Fluids</style></keyword><keyword><style  face="normal" font="default" size="100%">Hazardous Substances</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Biological</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Chemical</style></keyword><keyword><style  face="normal" font="default" size="100%">Solubility</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2014</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">185</style></volume><pages><style face="normal" font="default" size="100%">52-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Bioaccessibility in&amp;nbsp;vitro tests measure the solubility of materials in surrogate biofluids. However, the lack of uniform methods and the effects of variable test parameters on material solubility limit interpretation. One aim of this study was to measure and compare bioaccessibility of selected economically important alloys and metals in surrogate physiologically based biofluids representing oral, inhalation and dermal exposures. A second aim was to experimentally test different biofluid formulations and residence times in&amp;nbsp;vitro. A third aim was evaluation of dissolution behavior of alloys with in&amp;nbsp;vitro lung and dermal biofluid surrogates. This study evaluated the bioaccessibility of sixteen elements in six alloys and 3 elemental/metal powders. We found that the alloys/metals, the chemical properties of the surrogate fluid, and residence time all had major impacts on metal solubility. The large variability of bioaccessibility indicates the relevancy of assessing alloys as toxicologically distinct relative to individual metals.&lt;/p&gt;
</style></abstract><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/24212234?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chemical Profiling to Differentiate Geographic Origin of Pistachios</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Agric. Food Chem.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Analysis of Variance</style></keyword><keyword><style  face="normal" font="default" size="100%">California</style></keyword><keyword><style  face="normal" font="default" size="100%">Iran</style></keyword><keyword><style  face="normal" font="default" size="100%">Metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Pistacia</style></keyword><keyword><style  face="normal" font="default" size="100%">Spectrophotometry, Atomic</style></keyword><keyword><style  face="normal" font="default" size="100%">Turkey</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2005</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">53</style></volume><pages><style face="normal" font="default" size="100%">410-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objective of this study was to demonstrate the feasibility of chemical profiling methods combined with multivariate methods to differentiate the geographical growing regions of pistachios (Pistachia vera). Elemental analysis (Ba, Be, Ca, Cu, Cr, K, Mg, Mn, Na, V, Fe, Co, Ni, Cu, Zn, Sr, Ti, Cd, and P) of pistachios samples was performed using inductively coupled plasma atomic emission spectrometry. Analysis of inorganic anions and organic acids (selenite, bromate, fumarate, malate, selenate, pyruvate, acetate, phosphate, and ascorbate) of pistachio samples was performed using capillary electrophoresis. Bulk carbon and nitrogen isotope ratios were performed using stable isotope MS. There were nearly 400 pistachio samples analyzed from the three major pistachio growing regions: Turkey, Iran, and California (United States). A computational evaluation of the trace element data sets was carried out using statistical pattern recognition methods including principal component analysis, canonical discriminant analysis, discriminant analysis, and neural network modeling. Several linear discriminant function models classified the data sets with 95% or higher accuracy. We report the development of a method combining elemental analysis and classification techniques that may be widely applied to the determination of the geographical origin of foods.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/15656681?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim A Anderson</style></author><author><style face="normal" font="default" size="100%">Magnuson, B A</style></author><author><style face="normal" font="default" size="100%">Tschirgi, M L</style></author><author><style face="normal" font="default" size="100%">Smith, B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Determining the geographic origin of potatoes with trace metal analysis using statistical and neural network classifiers.</style></title><secondary-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Agric Food Chem</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Analysis of Variance</style></keyword><keyword><style  face="normal" font="default" size="100%">Discriminant Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Geography</style></keyword><keyword><style  face="normal" font="default" size="100%">Idaho</style></keyword><keyword><style  face="normal" font="default" size="100%">Metals</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks, Computer</style></keyword><keyword><style  face="normal" font="default" size="100%">Quality Control</style></keyword><keyword><style  face="normal" font="default" size="100%">Solanum tuberosum</style></keyword><keyword><style  face="normal" font="default" size="100%">Trace Elements</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">47</style></volume><pages><style face="normal" font="default" size="100%">1568-75</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objective of this research was to develop a method to confirm the geographical authenticity of Idaho-labeled potatoes as Idaho-grown potatoes. Elemental analysis (K, Mg, Ca, Sr, Ba, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Mo, S, Cd, Pb, and P) of potato samples was performed using ICPAES. Six hundred eight potato samples were collected from known geographic growing sites in the U.S. and Canada. An exhaustive computational evaluation of the 608 x 18 data sets was carried out using statistical (PCA, CDA, discriminant function analysis, and k-nearest neighbors) and neural network techniques. The neural network classification of the samples into two geographic regions (defined as Idaho and non-Idaho) using a bagging technique had the highest percentage of correct classifications, with a nearly 100% degree of accuracy. We report the development of a method combining elemental analysis and neural network classification that may be widely applied to the determination of the geographical origin of unprocessed, fresh commodities.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record></records></xml>