Premature Mortalities Attributable to Ozone and Fine Particulate Exposure: The Effect of Grid Size on Health Burden Estimates in the United States

We quantify how estimates of mortality in the United States attributable to ozone (O3) and fine particulate matter (PM2.5) driven with modeled concentrations at coarse resolution differ from those at finer resolution. Modeled concentrations of O3 and PM2.5 were used to estimate mortalities at 12 km and coarser resolutions greater than that of global models. We estimate that 66,000 (95% CI, 44,700 - 86,500) and 21,400 (5,600 - 34,200) mortalities per year are attributable to PM2.5 and O3 concentrations above low-concentration thresholds, respectively. Coarse grid resolutions produce mortality estimates that are substantially biased low for PM2.5 (38% lower than the best estimate at >300 km resolution), but only 5% higher for O3 (at >96 km resolution). Mortality estimates for primary PM2.5 species were more affected by grid resolution than for secondary species. These results suggest that using coarse resolution global models (>100 km) are likely biased low for PM2.5, but with little error for ozone

Parental genome unification is highly error-prone in mammalian embryos

Most human embryos are aneuploid. Aneuploidy frequently arises during the early mitotic divisions of the embryo, but its origin remains elusive. Human zygotes that cluster their nucleoli at the pronuclear interface are thought to be more likely to develop into healthy euploid embryos. Here, we show that the parental genomes cluster with nucleoli in each pronucleus within human and bovine zygotes, and clustering is required for the reliable unification of the parental genomes after fertilization. During migration of intact pronuclei, the parental genomes polarize toward each other in a process driven by centrosomes, dynein, microtubules, and nuclear pore complexes. The maternal and paternal chromosomes eventually cluster at the pronuclear interface, in direct proximity to each other, yet separated. Parental genome clustering ensures the rapid unification of the parental genomes on nuclear envelope breakdown. However, clustering often fails, leading to chromosome segregation errors and micronuclei, incompatible with healthy embryo development

Determining the Competitive Edge: Diversified Dairy Production Systems in the United States and the European Union

Agricultural and Food Policy, Farm Management, Livestock Production/Industries, Production Economics, Productivity Analysis,

Maternal ethnicity and socioeconomic deprivation: influence on adverse pregnancy outcomes.

OBJECTIVES: To evaluate the relative importance of ethnicity and socioeconomic deprivation in determining the likelihood and the percentage of composite adverse pregnancy outcomes (CAPO) and composite of severe adverse pregnancy outcomes (CAPO-S) METHODS: This is a single centre retrospective cohort study conducted in a tertiary maternity unit. Data regarding the ethnicity and socioeconomic deprivation were collected for 13,165 singleton pregnant women routinely screened in the first trimester for preeclampsia using the Fetal Medicine Foundation combined algorithm. RESULTS: The prevalence or risk of CAPO was 16.3% for White women, 29.3% for Black women and 29.3% for South Asian women. However, half of all CAPO cases (51.7%) occurred in White women. There is a strong interaction between ethnicity and socioeconomic deprivation (as measured with indices of multiple deprivation). Both influence the prevalence of CAPO and CAPO-S, with the contribution of ethnicity being strongest. CONCLUSIONS: Black and Asian ethnicity as well as socioeconomic deprivation influence the prevalence of placentally-mediated adverse pregnancy outcomes. Despite this, most adverse pregnancy outcomes occur in White women, who represent the majority of the population and are also affected by socioeconomic deprivation. For these reasons, inclusion of socioeconomic deprivation should be considered in early pregnancy risk assessment for placentally-mediated CAPO. This article is protected by copyright. All rights reserved

Predicting hospital cost in CKD patients through blood chemistry values

<p>Abstract</p> <p>Background</p> <p>Controversy exists in predicting costly hospitalization in patients with chronic kidney disease and co-morbid conditions. We therefore tested associations between serum chemistry values and the occurrence of in-patient hospital costs over a thirteen month study period. Secondarily, we derived a linear combination of variables to estimate probability of such occurrences in any patient.</p> <p>Method</p> <p>We calculated parsimonious values for select variables associated with in-patient hospitalization and compared sensitivity and specificity of these models to ordinal staging of renal disease.</p> <p>Data from 1104 de-identified patients which included 18 blood chemistry observations along with complete claims data for all medical expenses.</p> <p>We employed multivariable logistic regression for serum chemistry values significantly associated with in-patient hospital costs exceeding $3,000 in any single month and contrasted those results to other models by ROC area curves.</p> <p>Results</p> <p>The linear combination of weighted Z scores for parathyroid hormone, phosphorus, and albumin correlated with in-patient hospital care at p < 0.005. ROC curves derived from weighted variables of age, eGFR, hemoglobin, albumin, creatinine, and alanine aminotransferase demonstrated significance over models based on non-weighted Z scores for those same variables or CKD stage alone. In contrast, the linear combination of weighted PTH, PO4 and albumin demonstrated better prediction, but not significance over non-weighted Z scores for PTH alone.</p> <p>Conclusion</p> <p>Further study is justified to explore indices that predict costly hospitalization. Such metrics could assist Accountable Care Organizations in evaluating risk adjusted compensation for providers.</p