Within- and Between-Child Variation in Repeated Urinary Pesticide Metabolite Measurements over a 1-Year Period

Background: Children are exposed to pesticides from many sources and routes, including dietary and incidental ingestion, dermal absorption, and inhalation. Linking health outcomes to these exposures using urinary metabolites requires understanding temporal variability within subjects to avoid exposure misclassification. Objectives: We characterized the within- and between-child variability of urinary organophosphorus and pyrethroid metabolites in 23 participants of the Children’s Pesticide Exposure Study–Washington over 1 year and examined the ability of one to four spot urine samples to categorize mean exposures. Methods: Each child provided urine samples twice daily over 7- to 16-day sessions in four seasons in 2003 and 2004. Samples were analyzed for five pyrethroid and five organophosphorus (OP) metabolites. After adjusting for specific gravity, we used a customized maximum likelihood estimation linear mixed-effects model that accounted for values below the limit of detection to calculate intraclass correlation coefficients (ICC) and conducted surrogate category analyses. Results: Within-child variability was 2–11 times greater than between-child variability. When restricted to samples collected during a single season, ICCs were higher in the fall, winter, and spring than in summer for OPs, and higher in summer and winter for pyrethroids, indicating an increase in between-person variability relative to within-person variability during these seasons. Surrogate category analyses demonstrated that a single spot urine sample did not categorize metabolite concentrations well, and that four or more samples would be needed to categorize children into quartiles consistently. Conclusions: Urinary biomarkers of these short half-life pesticides exhibited substantial within-person variability in children observed over four seasons. Researchers investigating pesticides and health outcomes in children may need repeated biomarker measurements to derive accurate estimates of exposure and relative risks. Citation: Attfield KR, Hughes MD, Spengler JD, Lu C. 2014. Within- and between-child variation in repeated urinary pesticide metabolite measurements over a 1-year period. Environ Health Perspect 122:201–206; http://dx.doi.org/10.1289/ehp.130673

Mapping and Prediction of Coal Workers’ Pneumoconiosis with Bioavailable Iron Content in the Bituminous Coals

Based on the first National Study of Coal Workers’ Pneumoconiosis (CWP) and the U.S. Geological Survey database of coal quality, we show that the prevalence of CWP in seven coal mine regions correlates with levels of bioavailable iron (BAI) in the coals from that particular region (correlation coefficient r = 0.94, p < 0.0015). CWP prevalence is also correlated with contents of pyritic sulfur (r = 0.91, p < 0.0048) or total iron (r = 0.85, p < 0.016) but not with coal rank (r = 0.59, p < 0.16) or silica (r = 0.28, p < 0.54). BAI was calculated using our model, taking into account chemical interactions of pyrite, sulfuric acid, calcite, and total iron. That is, iron present in coals can become bioavailable by pyrite oxidation, which produces ferrous sulfate and sulfuric acid. Calcite is the major component in coals that neutralizes the available acid and inhibits iron’s bioavailability. Therefore, levels of BAI in the coals are determined by the available amounts of acid after neutralization of calcite and the amount of total iron in the coals. Using the linear fit of CWP prevalence and the calculated BAI in the seven coal mine regions, we have derived and mapped the pneumoconiotic potencies of 7,000 coal samples. Our studies indicate that levels of BAI in the coals may be used to predict coal’s toxicity, even before large-scale mining

Висновок експерта в криміналістичних технологіях

Досліджується висновок експерта в аспекті технологій експертних та технологій слідчих. Встановлюються умови технологічності цього процесуального документу. Конкретизуються критерії та дії експерта з забезпечення процесуальних вимог при складанні висновку за результатами проведених досліджень, та операції з оцінки висновку експерта слідчим.Исследуется заключение эксперта в аспекте технологий экспертных и технологий следственных. Устанавливаются условия технологичности этого процессуального документа. Конкретизируются критерии и действия эксперта по обеспечению процессуальных требований при составлении заключения по результатам проведенных исследований, и операции по оценке заключения эксперта следователем.The expert's conclusion is investigated in the aspect of expertise technologies and investigation technologies . The conditions for manufacturability of this procedural document are established. The criteria and expert's actions providing the procedural requirements while preparation of the report on the research results, and the operation on the assessment of the expert conclusion by investigator are concretized

The Diesel Exhaust in Miners Study: IV. Estimating Historical Exposures to Diesel Exhaust in Underground Non-metal Mining Facilities

We developed quantitative estimates of historical exposures to respirable elemental carbon (REC) for an epidemiologic study of mortality, including lung cancer, among diesel-exposed miners at eight non-metal mining facilities [the Diesel Exhaust in Miners Study (DEMS)]. Because there were no historical measurements of diesel exhaust (DE), historical REC (a component of DE) levels were estimated based on REC data from monitoring surveys conducted in 1998–2001 as part of the DEMS investigation. These values were adjusted for underground workers by carbon monoxide (CO) concentration trends in the mines derived from models of historical CO (another DE component) measurements and DE determinants such as engine horsepower (HP; 1 HP = 0.746 kW) and mine ventilation. CO was chosen to estimate historical changes because it was the most frequently measured DE component in our study facilities and it was found to correlate with REC exposure. Databases were constructed by facility and year with air sampling data and with information on the total rate of airflow exhausted from the underground operations in cubic feet per minute (CFM) (1 CFM = 0.0283 m3 min−1), HP of the diesel equipment in use (ADJ HP), and other possible determinants. The ADJ HP purchased after 1990 (ADJ HP1990+) was also included to account for lower emissions from newer, cleaner engines. Facility-specific CO levels, relative to those in the DEMS survey year for each year back to the start of dieselization (1947–1967 depending on facility), were predicted based on models of observed CO concentrations and log-transformed (Ln) ADJ HP/CFM and Ln(ADJ HP1990+). The resulting temporal trends in relative CO levels were then multiplied by facility/department/job-specific REC estimates derived from the DEMS surveys personal measurements to obtain historical facility/department/job/year-specific REC exposure estimates. The facility-specific temporal trends of CO levels (and thus the REC estimates) generated from these models indicated that CO concentrations had been generally greater in the past than during the 1998–2001 DEMS surveys, with the highest levels ranging from 100 to 685% greater (median: 300%). These levels generally occurred between 1970 and the early 1980s. A comparison of the CO facility-specific model predictions with CO air concentration measurements from a 1976–1977 survey external to the modeling showed that our model predictions were slightly lower than those observed (median relative difference of 29%; range across facilities: 49 to –25%). In summary, we successfully modeled past CO concentration levels using selected determinants of DE exposure to derive retrospective estimates of REC exposure. The results suggested large variations in REC exposure levels both between and within the underground operations of the facilities and over time. These REC exposure estimates were in a plausible range and were used in the investigation of exposure–response relationships in epidemiologic analyses

Retro American

Diesel exhaust is a suggested risk factor for ischemic heart disease (IHD), but evidence from cohorts using quantitative exposure metrics is limited. We examined the impact of respirable elemental carbon (REC), a key surrogate for diesel exhaust, and respirable dust (RD) on IHD mortality, using data from the Diesel Exhaust in Miners Study in the United States. Using data from a cohort of male workers followed from 1948–1968 until 1997, we fitted Cox proportional hazards models to estimate hazard ratios for IHD mortality for cumulative and average intensity of exposure to REC and RD. Segmented linear regression models allowed for nonmonotonicity. Hazard ratios for cumulative and average REC exposure declined relative to the lowest exposure category before increasing to 0.79 and 1.25, respectively, in the highest category. Relative to the category containing the segmented regression change points, hazard ratios for the highest category were 1.69 and 1.54 for cumulative and average REC exposure, respectively. Hazard ratios for RD exposure increased across the full exposure range to 1.33 and 2.69 for cumulative and average RD exposure, respectively. Tests for trend were statistically significant for cumulative REC exposure (above the change point) and for average RD exposure. Our findings suggest excess risk of IHD mortality in relation to increased exposure to REC and RD. © 2018 Oxford University Press. All Rights Reserved

Predicting crystal growth via a unified kinetic three-dimensional partition model

Understanding and predicting crystal growth is fundamental to the control of functionality in modern materials. Despite investigations for more than one hundred years1, 2, 3, 4, 5, it is only recently that the molecular intricacies of these processes have been revealed by scanning probe microscopy6, 7, 8. To organize and understand this large amount of new information, new rules for crystal growth need to be developed and tested. However, because of the complexity and variety of different crystal systems, attempts to understand crystal growth in detail have so far relied on developing models that are usually applicable to only one system9, 10, 11. Such models cannot be used to achieve the wide scope of understanding that is required to create a unified model across crystal types and crystal structures. Here we describe a general approach to understanding and, in theory, predicting the growth of a wide range of crystal types, including the incorporation of defect structures, by simultaneous molecular-scale simulation of crystal habit and surface topology using a unified kinetic three-dimensional partition model. This entails dividing the structure into ‘natural tiles’ or Voronoi polyhedra that are metastable and, consequently, temporally persistent. As such, these units are then suitable for re-construction of the crystal via a Monte Carlo algorithm. We demonstrate our approach by predicting the crystal growth of a diverse set of crystal types, including zeolites, metal–organic frameworks, calcite, urea and L-cystine

<i>CrystalGrower</i>: a generic computer program for Monte Carlo modelling of crystal growth.

From Europe PMC via Jisc Publications RouterHistory: ppub 2020-11-01, epub 2020-11-18Publication status: PublishedA Monte Carlo crystal growth simulation tool, CrystalGrower, is described which is able to simultaneously model both the crystal habit and nanoscopic surface topography of any crystal structure under conditions of variable supersaturation or at equilibrium. This tool has been developed in order to permit the rapid simulation of crystal surface maps generated by scanning probe microscopies in combination with overall crystal habit. As the simulation is based upon a coarse graining at the nanoscopic level features such as crystal rounding at low supersaturation or undersaturation conditions are also faithfully reproduced. CrystalGrower permits the incorporation of screw dislocations with arbitrary Burgers vectors and also the investigation of internal point defects in crystals. The effect of growth modifiers can be addressed by selective poisoning of specific growth sites. The tool is designed for those interested in understanding and controlling the outcome of crystal growth through a deeper comprehension of the key controlling experimental parameters