<?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%">Holly Dixon</style></author><author><style face="normal" font="default" size="100%">Armstrong, Georgina</style></author><author><style face="normal" font="default" size="100%">Michael L Barton</style></author><author><style face="normal" font="default" size="100%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Melissa Bondy</style></author><author><style face="normal" font="default" size="100%">Mary L Halbleib</style></author><author><style face="normal" font="default" size="100%">Winnifred Hamilton</style></author><author><style face="normal" font="default" size="100%">Erin N Haynes</style></author><author><style face="normal" font="default" size="100%">Julie Herbstman</style></author><author><style face="normal" font="default" size="100%">Peter D Hoffman</style></author><author><style face="normal" font="default" size="100%">Paul C Jepson</style></author><author><style face="normal" font="default" size="100%">Molly Kile</style></author><author><style face="normal" font="default" size="100%">Laurel D Kincl</style></author><author><style face="normal" font="default" size="100%">Paul J Laurienti</style></author><author><style face="normal" font="default" size="100%">Paula E North</style></author><author><style face="normal" font="default" size="100%">Paulik, L Blair</style></author><author><style face="normal" font="default" size="100%">Petrosino, Joe</style></author><author><style face="normal" font="default" size="100%">Points, Gary L</style></author><author><style face="normal" font="default" size="100%">Carolyn M Poutasse</style></author><author><style face="normal" font="default" size="100%">Diana Rohlman</style></author><author><style face="normal" font="default" size="100%">Richard P Scott</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Lane G Tidwell</style></author><author><style face="normal" font="default" size="100%">Cheryl Walker</style></author><author><style face="normal" font="default" size="100%">Katrina M Waters</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%">Discovery of common chemical exposures across three continents using silicone wristbands.</style></title><secondary-title><style face="normal" font="default" size="100%">R Soc Open Sci</style></secondary-title><alt-title><style face="normal" font="default" size="100%">R Soc Open Sci</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">181836</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;To assess differences and trends in personal chemical exposure, volunteers from 14 communities in Africa (Senegal, South Africa), North America (United States (U.S.)) and South America (Peru) wore 262 silicone wristbands. We analysed wristband extracts for 1530 unique chemicals, resulting in 400 860 chemical data points. The number of chemical detections ranged from 4 to 43 per wristband, with 191 different chemicals detected, and 1339 chemicals were not detected in any wristband. No two wristbands had identical chemical detections. We detected 13 potential endocrine disrupting chemicals in over 50% of all wristbands and found 36 chemicals in common between chemicals detected in three geographical wristband groups (Africa, North America and South America). U.S. children (less than or equal to 11 years) had the highest percentage of flame retardant detections compared with all other participants. Wristbands worn in Texas post-Hurricane Harvey had the highest mean number of chemical detections (28) compared with other study locations (10-25). Consumer product-related chemicals and phthalates were a high percentage of chemical detections across all study locations (36-53% and 18-42%, respectively). Chemical exposures varied among individuals; however, many individuals were exposed to similar chemical mixtures. Our exploratory investigation uncovered personal chemical exposure trends that can help prioritize certain mixtures and chemical classes for future studies.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></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%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Points, Gary L</style></author><author><style face="normal" font="default" size="100%">Richard P Scott</style></author><author><style face="normal" font="default" size="100%">Glenn R Wilson</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%">Development of quantitative screen for 1550 chemicals with GC-MS.</style></title><secondary-title><style face="normal" font="default" size="100%">Anal Bioanal Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Anal Bioanal Chem</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">410</style></volume><pages><style face="normal" font="default" size="100%">3101-3110</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;With hundreds of thousands of chemicals in the environment, effective monitoring requires high-throughput analytical techniques. This paper presents a quantitative screening method for 1550 chemicals based on statistical modeling of responses with identification and integration performed using deconvolution reporting software. The method was evaluated with representative environmental samples. We tested biological extracts, low-density polyethylene, and silicone passive sampling devices spiked with known concentrations of 196 representative chemicals. A multiple linear regression (R = 0.80) was developed with molecular weight, logP, polar surface area, and fractional ion abundance to predict chemical responses within a factor of 2.5. Linearity beyond the calibration had R &amp;gt; 0.97 for three orders of magnitude. Median limits of quantitation were estimated to be 201&amp;nbsp;pg/μL (1.9× standard deviation). The number of detected chemicals and the accuracy of quantitation were similar for environmental samples and standard solutions. To our knowledge, this is the most precise method for the largest number of semi-volatile organic chemicals lacking authentic standards. Accessible instrumentation and software make this method cost effective in quantifying a large, customizable list of chemicals. When paired with silicone wristband passive samplers, this quantitative screen will be very useful for epidemiology where binning of concentrations is common. Graphical abstract A multiple linear regression of chemical responses measured with GC-MS allowed quantitation of 1550 chemicals in samples such as silicone wristbands.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">13</style></issue></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%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Paula E North</style></author><author><style face="normal" font="default" size="100%">Vasquez, Luis</style></author><author><style face="normal" font="default" size="100%">Bello, Hernan</style></author><author><style face="normal" font="default" size="100%">Maria del Carmen Ruiz</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%">Multi-class chemical exposure in rural Peru using silicone wristbands.</style></title><secondary-title><style face="normal" font="default" size="100%">J Expo Sci Environ Epidemiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Expo Sci Environ Epidemiol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jul 26</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Exposure monitoring with personal silicone wristband samplers was demonstrated in Peru in four agriculture and urban communities where logistic and practical constraints hinder use of more traditional approaches. Wristbands and associated methods enabled quantitation of 63 pesticides and screening for 1397 chemicals including environmental contaminants and personal care products. Sixty-eight wristbands were worn for approximately one month by volunteers from four communities of Alto Mayo, Peru. We identified 106 chemicals from eight chemical classes among all wristbands. Agricultural communities were characterized by pesticides and PAHs, while the urban communities had more personal care products present. Multiple linear regressions explained up to 40% of variance in wristbands from chlorpyrifos, cypermethrin, and DDT and its metabolites (DDx) (r(2)=0.39, 0.30, 0.40, respectively). All three pesticides were significantly different between communities, and cypermethrin and DDx were associated with participant age. The calculated relative age of DDT suggested some communities had more recent exposure than others. This work aids health research in the Alto Mayo and beyond by identifying typical mixtures and potential sources of exposure to organic chemicals in the personal environment. Silicone wristband sampling with chemical screening is a candidate for widespread use in exposure monitoring in remote areas.Journal of Exposure Science and Environmental Epidemiology advance online publication, 26 July 2017; doi:10.1038/jes.2017.12.&lt;/p&gt;
</style></abstract></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%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Robyn L Tanguay</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%">Using passive sampling and zebrafish to identify developmental toxicants in complex mixtures.</style></title><secondary-title><style face="normal" font="default" size="100%">Environ Toxicol Chem</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Environ. Toxicol. Chem.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Mar 22</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Using effects-directed analysis, we investigated associations previously observed between polycyclic aromatic hydrocarbons (PAHs) and embryotoxicity in field-deployed low-density polyethylene (LDPE). We conducted effects-directed analysis using a zebrafish embryo assay and iterative fractionation of extracts of LDPE that were deployed in the Portland Harbor superfund megasite, Oregon (USA). Whole extracts induced toxicity including mortality, edema, and notochord distortion at 20% effect concentration (EC20) values of approximately 100, 100, and 10 mg LDPE/mL, respectively. Through fractionation, we determined that PAHs at concentrations similar to previous research did not contribute markedly to toxicity. We also eliminated pesticides, phthalates, musks, and other substances identified in toxic fractions by testing surrogate mixtures. We identified free fatty acids as lethal components of LDPE extracts and confirmed their toxicity with authentic standards. We found chromatographic evidence that dithiocarbamates are responsible for notochord and other sublethal effects, although exact matches were not obtained. Fatty acids and dithiocarbamates were previously unrecorded components of LDPE extracts and likely contribute to the toxicity of the whole mixture. The present study demonstrates the success of effects-directed analysis in nontargeted hazard identification using the zebrafish embryo test as a self-contained battery of bioassays that allows identification of multiple chemicals with different modes of action. This is the first effects-directed analysis to combine LDPE and zebrafish, approaches that are widely applicable to identifying developmental hazards in the bioavailable fraction of hydrophobic organic compounds. Environ Toxicol Chem 2017;9999:1-9. © 2017 SETAC.&lt;/p&gt;
</style></abstract></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%">LB Paulik</style></author><author><style face="normal" font="default" size="100%">Brian W Smith</style></author><author><style face="normal" font="default" size="100%">Alan J Bergmann</style></author><author><style face="normal" font="default" size="100%">Gregory J Sower</style></author><author><style face="normal" font="default" size="100%">Norman D Forsberg</style></author><author><style face="normal" font="default" size="100%">JG Teeguarden</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%">Passive samplers accurately predict PAH levels in resident crayfish.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Total Environ</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci. Total Environ.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2016</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">544</style></volume><pages><style face="normal" font="default" size="100%">782-791</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4±1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests that it could be easily adapted to predict contamination in other shellfish of concern.&lt;/p&gt;
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