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Are dose-response relationships for benzene and health effects such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) supra-linear, with disproportionately high risks at low concentrations, e.g. below 1 ppm? To investigate this hypothesis, we apply recent mode of action (MoA) and mechanistic information and modern data science techniques to quantify air benzene-urinary metabolite relationships in a previously studied data set for Tianjin, China factory workers. We find that physiologically based pharmacokinetics (PBPK) models and data for Tianjin workers show approximately linear production of benzene metabolites for air benzene (AB) concentrations below about 15 ppm, with modest sublinearity at low concentrations (e.g. below 5 ppm). Analysis of the Tianjin worker data using partial dependence plots reveals that production of metabolites increases disproportionately with increases in air benzene (AB) concentrations above 10 ppm, exhibiting steep sublinearity (J shape) before becoming saturated. As a consequence, estimated cumulative exposure is not an adequate basis for predicting risk. Risk assessments must consider the variability of exposure concentrations around estimated exposure concentrations to avoid over-estimating risks at low concentrations. The same average concentration for a specified duration is disproportionately risky if it has higher variance. Conversely, if chronic inflammation via activation of inflammasomes is a critical event for induction of MDS and other health effects, then sufficiently low concentrations of benzene are predicted not to cause increased risks of inflammasome-mediated diseases, no matter how long the duration of exposure. Thus, we find no evidence that the dose-response relationship is supra-linear at low doses; instead sublinear or zero excess risk at low concentrations is more consistent with the data. A combination of physiologically based pharmacokinetic (PBPK) modeling, Bayesian network (BN) analysis and inference, and partial dependence plots appears a promising and practical approach for applying current data science methods to advance benzene risk assessment.

Robotic seals have been studied in long-term care settings; though, no studies of patients with dementia in the acute care setting have been reported. The purpose of this study was to evaluate the feasibility of PARO interventions for hospitalized patients with dementia, determine physiological effects and describe social-affective interactions. Using a prospective descriptive design with pre-post PARO intervention physiological measurements, we studied 55 participants who received up to five 15-min PARO interventions. The PARO was favorably accepted for 212 (95%) of the 223 PARO interventions. Differences in pre- and post-physiological measures for mean arterial pressure, pulse, respiration, oxygenation, stress, and pain levels were evaluated using Wilcoxon Signed Rank test with statistically significant pre and post differences (p=<0.05); however, the differences were not clinically significant. Participants (95%) demonstrated beneficial PARO interactions with the most frequent interactions being speaking and petting. The PARO shows promise for enhancing social and affective responses for hospitalized patients with dementia., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Baboons are a widely used nonhuman primate model for biomedical, evolutionary, and basic genetics research. Despite this importance, the genomic resources for baboons are limited. In particular, the current baboon reference genome Panu&#95;3.0 is a highly fragmented, reference-guided (i.e., not fully de novo) assembly, and its poor quality inhibits our ability to conduct downstream genomic analyses., Findings: Here we present a de novo genome assembly of the olive baboon (Papio anubis) that uses data from several recently developed single-molecule technologies. Our assembly, Panubis1.0, has an N50 contig size of ∼1.46 Mb (as opposed to 139 kb for Panu&#95;3.0) and has single scaffolds that span each of the 20 autosomes and the X chromosome., Conclusions: We highlight multiple lines of evidence (including Bionano Genomics data, pedigree linkage information, and linkage disequilibrium data) suggesting that there are several large assembly errors in Panu&#95;3.0, which have been corrected in Panubis1.0., (© The Author(s) 2020. Published by Oxford University Press GigaScience.)

Decision analysis and risk analysis have grown up around a set of organizing questions: what might go wrong, how likely is it to do so, how bad might the consequences be, what should be done to maximize expected utility and minimize expected loss or regret, and how large are the remaining risks? In probabilistic causal models capable of representing unpredictable and novel events, probabilities for what will happen, and even what is possible, cannot necessarily be determined in advance. Standard decision and risk analysis questions become inherently unanswerable ("undecidable") for realistically complex causal systems with "open-world" uncertainties about what exists, what can happen, what other agents know, and how they will act. Recent artificial intelligence (AI) techniques enable agents (e.g., robots, drone swarms, and automatic controllers) to learn, plan, and act effectively despite open-world uncertainties in a host of practical applications, from robotics and autonomous vehicles to industrial engineering, transportation and logistics automation, and industrial process control. This article offers an AI/machine learning perspective on recent ideas for making decision and risk analysis (even) more useful. It reviews undecidability results and recent principles and methods for enabling intelligent agents to learn what works and how to complete useful tasks, adjust plans as needed, and achieve multiple goals safely and reasonably efficiently when possible, despite open-world uncertainties and unpredictable events. In the near future, these principles could contribute to the formulation and effective implementation of more effective plans and policies in business, regulation, and public policy, as well as in engineering, disaster management, and military and civil defense operations. They can extend traditional decision and risk analysis to deal more successfully with open-world novelty and unpredictable events in large-scale real-world planning, policymaking, and risk management., (© 2020 Society for Risk Analysis.)

In the first half of 2020, much excitement in news media and some peer reviewed scientific articles was generated by the discovery that fine particulate matter (PM2.5) concentrations and COVID-19 mortality rates are statistically significantly positively associated in some regression models. This article points out that they are non-significantly negatively associated in other regression models, once omitted confounders (such as latitude and longitude) are included. More importantly, positive regression coefficients can and do arise when (generalized) linear regression models are applied to data with strong nonlinearities, including data on PM2.5, population density, and COVID-19 mortality rates, due to model specification errors. In general, statistical modeling accompanied by judgments about causal interpretations of statistical associations and regression coefficients - the current weight-of-evidence (WoE) approach favored in much current regulatory risk analysis for air pollutants - is not a valid basis for determining whether or to what extent risk of harm to human health would be reduced by reducing exposure. The traditional scientific method based on testing predictive generalizations against data remains a more reliable paradigm for risk analysis and risk management., (© 2020 The Authors.)

In humans, most germline mutations are inherited from the father. This observation has been widely interpreted as reflecting the replication errors that accrue during spermatogenesis. If so, the male bias in mutation should be substantially lower in a closely related species with similar rates of spermatogonial stem cell divisions but a shorter mean age of reproduction. To test this hypothesis, we resequenced two 3-4 generation nuclear families (totaling 29 individuals) of olive baboons (Papio anubis), who reproduce at approximately 10 years of age on average, and analyzed the data in parallel with three 3-generation human pedigrees (26 individuals). We estimated a mutation rate per generation in baboons of 0.57×10-8 per base pair, approximately half that of humans. Strikingly, however, the degree of male bias in germline mutations is approximately 4:1, similar to that of humans-indeed, a similar male bias is seen across mammals that reproduce months, years, or decades after birth. These results mirror the finding in humans that the male mutation bias is stable with parental ages and cast further doubt on the assumption that germline mutations track cell divisions. Our mutation rate estimates for baboons raise a further puzzle, suggesting a divergence time between apes and Old World monkeys of 65 million years, too old to be consistent with the fossil record; reconciling them now requires not only a slowdown of the mutation rate per generation in humans but also in baboons., Competing Interests: The authors have declared that no competing interests exist.

Recent advances in understanding of biological mechanisms and adverse outcome pathways for many exposure-related diseases show that certain common mechanisms involve thresholds and nonlinearities in biological exposure concentration-response (C-R) functions. These range from ultrasensitive molecular switches in signaling pathways, to assembly and activation of inflammasomes, to rupture of lysosomes and pyroptosis of cells. Realistic dose-response modeling and risk analysis must confront the reality of nonlinear C-R functions. This paper reviews several challenges for traditional statistical regression modeling of C-R functions with thresholds and nonlinearities, together with methods for overcoming them. Statistically significantly positive exposure-response regression coefficients can arise from many non-causal sources such as model specification errors, incompletely controlled confounding, exposure estimation errors, attribution of interactions to factors, associations among explanatory variables, or coincident historical trends. If so, the unadjusted regression coefficients do not necessarily predict how or whether reducing exposure would reduce risk. We discuss statistical options for controlling for such threats, and advocate causal Bayesian networks and dynamic simulation models as potentially valuable complements to nonparametric regression modeling for assessing causally interpretable nonlinear C-R functions and understanding how time patterns of exposures affect risk. We conclude that these approaches are promising for extending the great advances made in statistical C-R modeling methods in recent decades to clarify how to design regulations that are more causally effective in protecting human health., Competing Interests: Declaration of competing interests The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the author's employer, Cox Associates LLC, which received funding from the National Stone, Sand, and Gravel Association (NSSGA) to support research on nonlinear dose-response modeling and preparation of this paper. All questions asked, selection of research methods used, and conclusions reached are solely those of the author. No one else had rights to review or comment on this work before it was submitted for publication., (Copyright © 2020 Elsevier Inc. All rights reserved.)

We examine how Bayesian network (BN) learning and analysis methods can help to meet several methodological challenges that arise in interpreting significant regression coefficients in exposure-response regression modeling. As a motivating example, we consider the challenge of interpreting positive regression coefficients for blood lead level (BLL) as a predictor of mortality risk for nonsmoking men. We first note that practices such as dichotomizing or categorizing continuous confounders (e.g. income), omitting potentially important socioeconomic confounders (e.g. education), and assuming specific parametric regression model forms leave unclear to what extent a positive regression coefficient reflects these modeling choices, rather than a direct dependence of mortality risk on exposure. Therefore, significant exposure-response coefficients in parametric regression models do not necessarily reveal the extent to which reducing exposure-related variables (e.g. BLL) alone, while leaving fixed other correlates of exposure and mortality risks (e.g. education, income, etc.) would reduce adverse outcome risks (e.g. mortality risks). We then consider how BN structure-learning and inference algorithms and nonparametric estimation methods (partial dependence plots) can be used to clarify dependencies between variables, variable selection, confounding, and quantification of joint effects of multiple factors on risk, including possible high-order interactions and nonlinearities. We conclude that these details must be carefully modeled to determine whether a data set provides evidence that exposure itself directly affects risks; and that BN and nonparametric effect estimation and uncertainty quantification methods can complement regression modeling and help to improve the scientific basis for risk management decisions and policy-making by addressing these issues.

Inflammasomes are a family of pro-inflammatory signaling complexes that orchestrate inflammatory responses in many tissues. The NLRP3 inflammasome has been implicated in several diseases associated with chronic inflammation. In this paper, we present an Adverse Outcome Pathway (AOP) for NLRP3-induced chronic inflammatory diseases that demonstrates how NLRP3 can cause a transition from acute to chronic inflammation, and ultimately the onset of disease. We present a simple graphical description of the main features of internal dose time courses that are important when pharmacodynamics are governed by an activation threshold. Similar considerations hold for other AOPs that are rate-limited by processes with activation thresholds. The risk analysis implications of AOPs with threshold or threshold-like pharmacodynamic responses include the need to consider how cumulative dose per unit time is distributed over time and the possibility that safe, or virtually safe, exposure concentrations can be defined for such processes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The authors had complete control over the design, conduct, interpretation, and composition of this manuscript. The contents of this manuscript are solely the responsibility of the authors and do not necessarily reflect the views or policies of their employers. J. Goodman and A. Engel received support from the George Washington University (GWU) for developing this manuscript. Dr. Goodman has served as an expert in multiple litigation matters involving asbestos-containing products. None of the underlying research or analysis for this paper was performed during the context of those engagements or was sponsored by any of the defendants. Dr. Cox's work on the risk modeling approach reported here was supported by his employer, Cox Associates LLC, which has received research funding in 2018–2020 from the following sources: (1) a research contract from the National Stone, Sand, and Gravel Association to develop and apply risk models and machine learning methods and causal analytics to risk assessment for mineral dusts and fibers; (2) a research project with the GWU Regulatory Studies Center to investigate and explain the role of the NLRP3 inflammasome in risk analysis., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Virginiamycin (VM), a streptogramin antibiotic, has been used to promote healthy growth and treat illnesses in farm animals in the United States and other countries. The combination streptogramin Quinupristin-Dalfopristin (QD) was approved in the United States in 1999 for treating patients with vancomycin-resistant Enterococcus faecium (VREF) infections. Many chickens and swine test positive for QD-resistant E. faecium, raising concerns that using VM in food animals might select for streptogramin-resistant strains of E. faecium that could compromise QD effectiveness in treating human VREF infections. Such concerns have prompted bans and phase-outs of VM as growth promoters in the United States and Europe. This study quantitatively estimates potential human health risks from QD-resistant VREF infections due to VM use in food animals in China. Plausible conservative (risk-maximizing) quantitative risk estimates are derived for future uses, assuming 100% resistance to linezolid and daptomycin and 100% prescription rate of QD to high-level (VanA) VREF-infected patients. Up to one shortened life every few decades to every few thousand years might occur in China from VM use in animals, although the most likely risk is zero (e.g., if resistance is not transferred from bacteria in food animals to bacteria infecting human patients). Sensitivity and probabilistic uncertainty analyses suggest that this conclusion is robust to several data gaps and uncertainties. Potential future human health risks from VM use in animals in China appear to be small or zero, even if QD is eventually approved for use in human patients., (© 2020 Society for Risk Analysis.)

Why have occupational safety regulations in the United States not been more successful in protecting worker health from mesothelioma risks, while apparently succeeding relatively well in reducing silicosis risks? This paper briefly discusses biological bases for thresholds and nonlinearities in exposure-response functions for respirable crystalline silica (RCS) and asbestos, based on modeling a chronic inflammation mode of action (mediated by activation of the NLRP3 inflammasome, for both RCS and asbestos). It applies previously published physiologically based pharmacokinetic (PBPK) models to perform computational experiments illuminating how different time courses of exposure with the same time-weighted average (TWA) concentration affect internal doses in target tissues (lung for RCS and mesothelium for asbestos). Key conclusions are that (i) For RCS, but not asbestos, limiting average (TWA) exposure concentrations also tightly constrains internal doses and ability to trigger chronic inflammation and resulting increases in disease risks (ii) For asbestos, excursions (i.e., spikes in concentrations); and especially the times between them are crucial drivers of internal doses and time until chronic inflammation; and hence (iii) These dynamic aspects of exposure, which are not addressed by current occupational safety regulations, should be constrained to better protect worker health. Adjusting permissible average exposure concentration limits (PELs) and daily excursion limits (ELs) is predicted to have little impact on reducing mesothelioma risks, but increasing the number of days between successive excursions is predicted to be relatively effective in reducing worker risks, even if it has little or no impact on TWA average concentrations., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Introduction: The baboon is a well-characterized model of human early stage atherosclerosis. However, histological and morphological changes involved in atherogenesis in baboons are not known. Previously, we challenged baboons with a high-cholesterol, high-fat diet for two years and observed fatty streak and plaque lesions in iliac arteries (RCIA)., Methods: We evaluated histological and morphological changes of baboon arterial lesions and control arteries. In addition, we evaluated the vascular expression of CD68 and SMαA markers with progression of atherosclerosis., Results: We observed changes that correlated with extent of atherosclerosis, including increased maximum intimal thickness. We demonstrated at molecular level the infiltration of smooth muscle cells and macrophages into the intimal layer. Further, we observed histological and morphological discordancy between the affected and adjacent areas of the same RCIA., Conclusion: Atherogenesis in baboons is accompanied by histological, morphological, and molecular changes, as in humans, providing insights to evaluate the mechanisms underlying early stage atherosclerosis in target tissues., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses-which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas-have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.

Can a single fiber of amphibole asbestos increase the risk of lung cancer or malignant mesothelioma (MM)? Traditional linear no-threshold (LNT) risk assessment assumptions imply that the answer is yes: there is no safe exposure level. This paper draws on recent scientific progress in inflammation biology, especially elucidation of the activation thresholds for NLRP3 inflammasomes and resulting chronic inflammation, to model dose-response relationships for malignant mesothelioma and lung cancer risks caused by asbestos exposures. The modeling integrates a physiologically based pharmacokinetics (PBPK) front end with inflammation-driven two-stage clonal expansion (I-TSCE) models of carcinogenesis to describe how exposure leads to chronic inflammation, which in turn promotes carcinogenesis. Together, the combined PBPK and I-TSCE modeling predict that there are practical thresholds for exposure concentration below which asbestos exposure does not cause chronic inflammation in less than a lifetime, and therefore does not increase chronic inflammation-dependent cancer risks. Quantitative examples using model parameter estimates drawn from the literature suggest that practical thresholds may be within about a factor of 2 of some past exposure levels for some workers. The I-TSCE modeling framework explains previous puzzling aspects of asbestos epidemiology, such as why age at first exposure is a better predictor of lifetime MM risk than exposure duration. It may be a valuable tool for risk analysts when LNT assumptions are not justified due to inflammation response thresholds mediating dose-response relationships.

Baboons (genus Papio ) are broadly studied in the wild and in captivity. They are widely used as a nonhuman primate model for biomedical studies, and the Southwest National Primate Research Center (SNPRC) at Texas Biomedical Research Institute has maintained a large captive baboon colony for more than 50 yr. Unlike other model organisms, however, the genomic resources for baboons are severely lacking. This has hindered the progress of studies using baboons as a model for basic biology or human disease. Here, we describe a data set of 100 high-coverage whole-genome sequences obtained from the mixed colony of olive ( P. anubis ) and yellow ( P. cynocephalus ) baboons housed at the SNPRC. These data provide a comprehensive catalog of common genetic variation in baboons, as well as a fine-scale genetic map. We show how the data can be used to learn about ancestry and admixture and to correct errors in the colony records. Finally, we investigated the consequences of inbreeding within the SNPRC colony and found clear evidence for increased rates of infant mortality and increased homozygosity of putatively deleterious alleles in inbred individuals., (© 2019 Robinson et al.; Published by Cold Spring Harbor Laboratory Press.)

Atherosclerotic plaques are characterized by an accumulation of macrophages, lipids, smooth muscle cells, and fibroblasts, and, in advanced stages, necrotic debris within the arterial walls. Dietary habits such as high fat and high cholesterol (HFHC) consumption are known risk factors for atherosclerosis. However, the key metabolic contributors to diet-induced atherosclerosis are far from established. Herein, we investigate the role of a 2-year HFHC diet challenge in the metabolic changes of development and progression of atherosclerosis. We used a non-human primate (NHP) model (baboons, n = 60) fed a HFHC diet for two years and compared metabolomic profiles in serum from animals on baseline chow with serum collected after the challenge diet using two-dimensional gas chromatography time-of-flight mass-spectrometry (2D GC-ToF-MS) for untargeted metabolomic analysis, to quantify metabolites that contribute to atherosclerotic lesion formation. Further, clinical biomarkers associated with atherosclerosis, lipoprotein measures, fat indices, and arterial plaque formation (lesions) were quantified. Using two chemical derivatization (i.e., silylation) approaches, we quantified 321 metabolites belonging to 66 different metabolic pathways, which revealed significantly different metabolic profiles of HFHC diet and chow diet fed baboon sera. We found heritability of two important metabolites, lactic acid and asparagine, in the context of diet-induced metabolic changes. In addition, abundance of cholesterol, lactic acid, and asparagine were sex-dependent. Finally, 35 metabolites correlated (R2, 0.068-0.271, P < 0.05) with total lesion burden assessed in three arteries (aortic arch, common iliac artery, and descending aorta) which could serve as potential biomarkers pending further validation. This study demonstrates the feasibility of detecting sex-specific and heritable metabolites in NHPs with diet-induced atherosclerosis using untargeted metabolomics allowing understanding of atherosclerotic disease progression in humans., Competing Interests: The authors have declared that no competing interests exist.

Background: Non-human primate models of developmental programming by maternal obesity (MO) are needed for translation to human programming outcomes. We present baboon offspring (F1) morphometry, blood cortisol, and adrenocorticotropic hormone (ACTH) from 0.9 gestation to 0-2 years., Methods: Control mothers ate chow; MO mothers ate high-fat high-energy diet pre-pregnancy through lactation., Results: Maternal obesity mothers weighed more than controls pre-pregnancy. Maternal obesity gestational weight gain was lower with no correlation with fetal or placenta weights. At 0.9 gestation, MO and control F1 morphometry and ACTH were similar. MO-F1 0.9 gestation male cortisol was lower, rising slower from 0-2 years vs control-F1. At birth, male MO-F1 and control-F1 weights were similar, but growth from 0-2 years was steeper in MO-F1; newborn female MO-F1 weighed more than control-F1 but growth from 0-2 years was similar. ACTH did not change in either sex., Conclusions: Maternal obesity produced sexually dimorphic fetal and postnatal growth and hormonal phenotypes., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Rationale: Plasma low-density lipoprotein cholesterol (plasma LDL-C), vascular endothelial cells and peripheral blood mononuclear cells (PBMCs), particularly monocytes, play key roles in initiating atherosclerosis, the primary cause of cardiovascular disease (CVD). Although the mechanisms underlying development of atherosclerosis are not well understood, LDL-C is known to influence expression of endothelial microRNAs (miRNAs) and gene-targets of miRNAs to promote cell senescence. However, the impact of LDL-C on expression of PBMC miRNAs and miRNA targeted genes in response to an atherogenic diet is not known. In this study, we used unbiased methods to identify coordinately responsive PBMC miRNA- gene networks that differ between low and high LDL-C baboons when fed a high-cholesterol, high-fat (HCHF) diet., Methods and Results: Using RNA Seq, we quantified PBMC mRNAs and miRNAs from half-sib baboons discordant for LDL-C plasma concentrations (low LDL-C, n = 3; high LDL-C, n = 3) before and after a 7-week HCHF diet challenge. For low LDL-C baboons, 626 genes exhibited significant change in expression (255 down-regulated, 371 up-regulated) in response to the HCHF diet, and for high LDL-C baboons 379 genes exhibited significant change in expression (162 down-regulated, 217 up-regulated) in response to the HCHF diet. We identified 494 miRNAs identical to human miRNAs and 47 novel miRNAs. Fifty miRNAs were differentially expressed in low LDL-C baboons (21 up- and 29 down-regulated) and 20 in high LDL-C baboons (11 up- and 9 down-regulated) in response to the HCHF diet. Among the differentially expressed miRNAs were miR-221/222 and miR-34a-3p, which were down-regulated, and miR-148a/b-5p, which was up-regulated. In addition, gene-targets of these miRNAs, VEGFA, MAML3, SPARC, and DMGDH, were inversely expressed and are central hub genes in networks and signaling pathways that differ between low and high LDL-C baboon HCHF diet response., Conclusions: We have identified coordinately regulated HCHF diet-responsive PBMC miRNA-gene networks that differ between baboons discordant for LDL-C concentrations. Our findings provide potential insights into molecular mechanisms underlying initiation of atherosclerosis where LDL-C concentrations influence expression of specific miRNAs, which in turn regulate expression of genes that play roles in initiation of lesions., Competing Interests: The authors have declared that no competing interests exist.

Key Points: Maternal obesity (MO) and exposure to a high-fat, high-simple-carbohydrate diet during pregnancy predisposes offspring to obesity, metabolic and cardiovascular disorders in later life. Underlying molecular pathways and potential epigenetic factors that are dysregulated in MO were identified using unbiased transcriptomic methods. There was increased lipid accumulation and severe steatosis in the MO baboon fetal liver suggesting that these offspring are on an early trajectory of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis., Abstract: Maternal obesity (MO) increases offspring cardiometabolic disease risk. Altered fetal liver development in response to the challenge of MO has metabolic consequences underlying adverse offspring life-course health outcomes. Little is known about the molecular pathways and potential epigenetic changes regulating primate fetal liver responses to MO. We hypothesized that MO would induce fetal baboon liver epigenetic changes resulting in dysregulation of key metabolic pathways that impact lipid metabolism. MO was induced prior to pregnancy by a high-fat, high-fructose diet. Unbiased gene and microRNA (small RNA Seq) abundance analyses were performed on fetal baboon livers at 0.9 gestation and subjected to pathway analyses to identify fetal liver molecular responses to MO. Fetal baboon liver lipid and glycogen content were quantified by the Computer Assisted Stereology Toolbox. In response to MO, fetal livers revealed dysregulation of TCA cycle, proteasome, oxidative phosphorylation, glycolysis and Wnt/β-catenin signalling pathways together with marked lipid accumulation supporting our hypothesis that multiple pathway dysregulation detrimentally impacts lipid management. This is the first study of MO programming of the non-human primate fetal liver using unbiased transcriptome analysis to detect changes in hepatic gene expression levels and identify potential microRNA epigenetic regulators of metabolic disruption., (© 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.)

Key Points: Maternal high-fat diet consumption predisposes to metabolic dysfunction in male and female offspring at young adulthood. Maternal obesity programs non-alcoholic fatty liver disease (NAFLD) in a sex-dependent manner. We demonstrate sex-dependent liver transcriptome profiles in rat offspring of obese mothers. In this study, we focused on pathways related to insulin, glucose and lipid signalling. These results improve understanding of the mechanisms by which a maternal high-fat diet affects the offspring., Abstract: Maternal obesity (MO) predisposes offspring (F1) to obesity, insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD). MO's effects on the F1 liver transcriptome are poorly understood. We used RNA-seq to determine the liver transcriptome of male and female F1 of MO and control-fed mothers. We hypothesized that MO-F1 are predisposed to sex-dependent adult liver dysfunction. Female Wistar rat mothers ate a control (C) or obesogenic (MO) diet from the time they were weaned through breeding at postnatal day (PND) 120, delivery and lactation. After weaning, all male and female F1 ate a control diet. At PND 110, F1 serum, liver and fat were collected to analyse metabolites, histology and liver differentially expressed genes. Male and female MO-F1 showed increased adiposity index, triglycerides, insulin and homeostatic model assessment vs. C-F1 with similar body weight and glucose serum concentrations. MO-F1 males presented greater physiological and histological NAFLD characteristics than MO-F1 females. RNA-seq revealed 1365 genes significantly changed in male MO-F1 liver and only 70 genes in female MO-F1 compared with controls. GO and KEGG analysis identified differentially expressed genes related to metabolic processes. Male MO-F1 liver showed the following altered pathways: insulin signalling (22 genes), phospholipase D signalling (14 genes), NAFLD (13 genes) and glycolysis/gluconeogenesis (7 genes). In contrast, few genes were altered in these pathways in MO-F1 females. In summary, MO programs sex-dependent F1 changes in insulin, glucose and lipid signalling pathways, leading to liver dysfunction and insulin resistance., (© 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.)

Rationale: Metabolomics analyses using gas chromatography/mass spectrometry (GC/MS)-based metabolomics are heavily impeded by the lack of high-resolution mass spectrometers and limited spectral libraries to complement the excellent chromatography that GC platforms offer, a challenge that is being addressed with the implementation of high-resolution (HR) platforms such as 1D-GC/Orbitrap-MS., Methods: We used serum samples from a non-human primate (NHP), a baboon (Papio hamadryas), with suitable quality controls to quantify the chemical space using an advanced HRMS platform for confident metabolite identification and robust quantification to assess the suitability of the platform for routine clinical metabolomics research. In a complementary approach, we also analyzed the same serum samples using two-dimensional gas chromatography/time-of-flight mass spectrometry (2D-GC/TOF-MS) for metabolite identification and quantification following established standard protocols., Results: Overall, the 2D-GC/TOF-MS (~5000 peaks per sample) and 1D-GC/Orbitrap-MS (~500 peaks per sample) analyses enabled identification and quantification of a total of 555 annotated metabolites from the NHP serum with a spectral similarity score R sim  ≥ 900 and signal-to-noise (S/N) ratio of >25. A common set of 30 metabolites with HMDB and KEGG IDs was quantified in the serum samples by both platforms where 2D-GC/TOF-MS enabled quantification of a total 384 metabolites (118 HMDB IDs) and 1D-GC/Orbitrap-MS analysis quantification of a total 200 metabolites (47 HMDB IDs). Thus, roughly 30-70% of the peaks remain unidentified or un-annotated across both platforms., Conclusions: Our study provides insights into the benefits and limitations of the use of a higher mass resolution and mass accuracy instrument for untargeted GC/MS-based metabolomics with multi-dimensional chromatography in future studies addressing clinical conditions or exposome studies., (© 2018 John Wiley & Sons, Ltd.)

Perhaps no other topic in risk analysis is more difficult, more controversial, or more important to risk management policy analysts and decision-makers than how to draw valid, correctly qualified causal conclusions from observational data. Statistical methods can readily quantify associations between observed variables using measures such as relative risk (RR) ratios, odds ratios (OR), slope coefficients for exposure or treatment variables in regression models, and quantities derived from these measures. Textbooks of epidemiology explain how to calculate population attributable fractions, attributable risks, burden-of-disease estimates, and probabilities of causation from relative risk (RR) ratios. Despite their suggestive names, these association-based measures have no necessary connection to causation if the associations on which they are based arise from bias, confounding, p-hacking, coincident historical trends, or other noncausal sources. But policy analysts and decision makers need something more: trustworthy predictions - and, later, evaluations - of the changes in outcomes caused by changes in policy variables. This concept of manipulative causation differs from the more familiar concepts of associational and attributive causation most widely used in epidemiology. Drawing on modern literature on causal discovery and inference principles and algorithms for drawing limited but useful causal conclusions from observational data, we propose seven criteria for assessing consistency of data with a manipulative causal exposure-response relationship - mutual information, directed dependence, internal and external consistency, coherent causal explanation of biological plausibility, causal mediation confirmation, and refutation of non-causal explanations - and discuss to what extent it is now possible to automate discovery of manipulative causal dependencies and quantification of causal effects from observational data. We compare our proposed principles for causal discovery and inference to the traditional Bradford Hill considerations from 1965. Understanding how old and new principles are related can clarify and enrich both.

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Background: Little is known about the repertoire of non-human primate kidney genes expressed throughout development. The present work establishes an understanding of the primate renal transcriptome during fetal development in the context of renal maturation., Methods: The baboon kidney transcriptome was characterized at 60-day gestation (DG), 90 DG, 125 DG, 140 DG, 160 DG and adulthood (6-12 years) using gene arrays and validated by QRT-PCR. Pathway and cluster analyses were used to characterize gene expression in the context of biological pathways., Results: Pathway analysis indicated activation of pathways not previously reported as relevant to kidney development. Cluster analysis also revealed gene splice variants with discordant expression profiles during development., Conclusions: This study provides the first detailed genetic analysis of the developing primate kidney, and our findings of discordant expression of gene splice variants suggest that gene arrays likely provide a simplified view and demonstrate the need to study the fetal renal proteome., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Introduction: Metabolomics is a promising approach for discovery of relevant biomarkers in cells, tissues, organs, and biofluids for disease identification and prediction. The field has mostly relied on blood-based biofluids (serum, plasma, urine) as non-invasive sources of samples as surrogates of tissue or organ-specific conditions. However, the tissue specificity of metabolites pose challenges in translating blood metabolic profiles to organ-specific pathophysiological changes, and require further downstream analysis of the metabolites., Objectives: As part of this project, we aim to develop and optimize an efficient extraction protocol for the analysis of kidney tissue metabolites representative of key primate metabolic pathways., Methods: Kidney cortex and medulla tissues of a baboon were homogenized and extracted using eight different extraction protocols including methanol/water, dichloromethane/methanol, pure methanol, pure water, water/methanol/chloroform, methanol/chloroform, methanol/acetonitrile/water, and acetonitrile/isopropanol/water. The extracts were analyzed by a two-dimensional gas chromatography time-of-flight mass-spectrometer (2D GC-ToF-MS) platform after methoximation and silylation., Results: Our analysis quantified 110 shared metabolites in kidney cortex and medulla tissues from hundreds of metabolites found among the eight different solvent extractions spanning low to high polarities. The results revealed that medulla is metabolically richer compared to the cortex. Dichloromethane and methanol mixture (3:1) yielded highest number of metabolites across both the tissue types. Depending on the metabolites of interest, tissue type, and the biological question, different solvents can be used to extract specific groups of metabolites., Conclusion: This investigation provides insights into selection of extraction solvents for detection of classes of metabolites in renal cortex and medulla, which is fundamentally important for identification of prognostic and diagnostic metabolic kidney biomarkers for future therapeutic applications.

Rodent and nonhuman primate studies indicate that developmental programming by reduced perinatal nutrition negatively impacts life course cardio-metabolic health. We have developed a baboon model in which we feed control mothers (CON) ad libitum while nutrient restricted mothers are fed 70% of ad libitum global feed in pregnancy and lactation. Offspring of nutrient restricted mothers are intrauterine growth restricted (IUGR) at term. By 3.5 years IUGR baboons showed signs of insulin resistance, indicating a pre-diabetic phenotype, in contrast to healthy CON offspring. We hypothesized that a novel breath analysis approach would provide markers of the altered cardio-metabolic state in a non-invasive manner. Here we assess whether exhaled breath volatile organic compounds (VOCs) collected from this unique cohort of juvenile baboons with documented cardio-metabolic dysfunction resulting from in utero programming can be detected from their breath signatures. Breath was collected from male and female CON and IUGR baboons at 4.8 ± 0.2 years (human equivalent ∼13 years). Breath VOCs were quantified using a two-dimensional gas chromatography mass spectrometer. Two-way ANOVA, on 76 biologically relevant VOCs identified 27 VOCs (p < 0.05) with altered abundances between groups (sex, birthweight, and sex x birthweight). The 27 VOCs included 2-pentanone, 2-octanone, 2,2,7,7-tetramethyloctane and 3-methyl-1-heptene, which have not previously been associated with cardio-metabolic disease. Unsupervised principal component analysis of these VOCs could discriminate the four clusters defining males, females, CON and IUGR. This study, which is the first to assess quantifiable breath signatures associated with cardio-metabolic programing for any model of IUGR, demonstrates the translational value of this unique model to identify metabolites of programmed cardio-metabolic dysfunction in breath signatures. Future studies are required to validate the translatability of these findings to humans.

Background: The purpose of this study was to determine whether dietary manipulation can reliably induce early-stage atherosclerosis and clinically relevant changes in vascular function in an established, well-characterized non-human primate model., Methods: We fed 112 baboons a high-cholesterol, high-fat challenge diet for two years. We assayed circulating biomarkers of cardiovascular disease (CVD) risk, at 0, 7, and 104 weeks into the challenge; assessed arterial compliance noninvasively at 104 weeks; and measured atherosclerotic lesions in three major arteries at necropsy., Results: We observed evidence of atherosclerosis in all but one baboon fed the two-year challenge diet. CVD risk biomarkers, the prevalence, size, and complexity of arterial lesions, plus consequent arterial stiffness, were increased in comparison with dietary control animals., Conclusions: Feeding baboons a high-cholesterol, high-fat diet for two years reliably induces atherosclerosis, with risk factor profiles, arterial lesions, and changes in vascular function also seen in humans., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Two apparently contradictory findings in the literature on low-dose human metabolism of benzene are as follows. First, metabolism is approximately linear at low concentrations, e.g., below 10 ppm. This is consistent with decades of quantitative modeling of benzene pharmacokinetics and dose-dependent metabolism. Second, measured benzene exposure and metabolite concentrations for occupationally exposed benzene workers in Tianjin, China show that dose-specific metabolism (DSM) ratios of metabolite concentrations per ppm of benzene in air decrease steadily with benzene concentration, with the steepest decreases below 3 ppm. This has been interpreted as indicating that metabolism at low concentrations of benzene is highly nonlinear. We reexamine the data using non-parametric methods. Our main conclusion is that both findings are correct; they are not contradictory. Low-concentration metabolism can be linear, with metabolite concentrations proportional to benzene concentrations in air, and yet DSM ratios can still decrease with benzene concentrations. This is because a ratio of random variables can be negatively correlated with its own denominator even if the mean of the numerator is proportional to the denominator. Interpreting DSM ratios that decrease with air benzene concentrations as evidence of nonlinear metabolism is therefore unwarranted when plots of metabolite concentrations against benzene ppm in air show approximately straight-line relationships between them, as in the Tianjin data. Thus, an apparent contradiction that has fueled heated discussions in the recent literature can be resolved by recognizing that highly nonlinear, decreasing DSM ratios are consistent with linear metabolism., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Most developmental programming studies on maternal nutrient reduction (MNR) are in altricial rodents whose maternal nutritional burden and offspring developmental trajectory differ from precocial non-human primates and humans., Methods: Control (CTR) baboon mothers ate ad libitum; MNR mothers ate 70% global control diet in pregnancy and lactation., Results: We present offspring morphometry, blood cortisol, and adrenocorticotropin (ACTH) during second half of gestation (G) and first three postnatal years. Moderate MNR produced intrauterine growth restriction (IUGR). IUGR males (n=43) and females (n=28) were smaller than CTR males (n=50) and females (n=47) in many measurements at many ages. In CTR, fetal ACTH increased 228% and cortisol 48% between 0.65G and 0.9G. IUGR ACTH was elevated at 0.65G and cortisol at 0.9G. 0.9G maternal gestational weight gain, fetal weight, and placenta weight were correlated., Conclusions: Moderate IUGR decreased body weight and morphometric measurements at key time points and altered hypothalamo-pituitary-adrenal function., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States. Human epidemiological studies provide challenges for understanding mechanisms that regulate initiation and progression of CVD due to variation in lifestyle, diet, and other environmental factors. Studies describing metabolic and physiologic aspects of CVD, and those investigating genetic and epigenetic mechanisms influencing CVD initiation and progression, have been conducted in multiple Old World nonhuman primate (NHP) species. Major advantages of NHPs as models for understanding CVD are their genetic, metabolic, and physiologic similarities with humans, and the ability to control diet, environment, and breeding. These NHP species are also genetically and phenotypically heterogeneous, providing opportunities to study gene by environment interactions that are not feasible in inbred animal models. Each Old World NHP species included in this review brings unique strengths as models to better understand human CVD. All develop CVD without genetic manipulation providing multiple models to discover genetic variants that influence CVD risk. In addition, as each of these NHP species age, their age-related comorbidities such as dyslipidemia and diabetes are accelerated proportionally 3 to 4 times faster than in humans.In this review, we discuss current CVD-related research in NHPs focusing on selected aspects of CVD for which nonprimate model organism studies have left gaps in our understanding of human disease. We include studies on current knowledge of genetics, epigenetics, calorie restriction, maternal calorie restriction and offspring health, maternal obesity and offspring health, nonalcoholic steatohepatitis and steatosis, Chagas disease, microbiome, stem cells, and prevention of CVD., (© The Author(s) 2017. Published by Oxford University Press on behalf of the National Academy of Sciences. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Shotgun proteomics utilizes a database search strategy to compare detected mass spectra to a library of theoretical spectra derived from reference genome information. As such, the robustness of proteomics results is contingent upon the completeness and accuracy of the gene annotation in the reference genome. For animal models of disease where genomic annotation is incomplete, such as non-human primates, proteogenomic methods can improve the detection of proteins by incorporating transcriptional data from RNA-Seq to improve proteomics search databases used for peptide spectral matching. Customized search databases derived from RNA-Seq data are capable of identifying unannotated genetic and splice variants while simultaneously reducing the number of comparisons to only those transcripts actively expressed in the tissue., Results: We collected RNA-Seq and proteomic data from 10 vervet monkey liver samples and used the RNA-Seq data to curate sample-specific search databases which were analyzed in the program Morpheus. We compared these results against those from a search database generated from the reference vervet genome. A total of 284 previously unannotated splice junctions were predicted by the RNA-Seq data, 92 of which were confirmed by peptide spectral matches. More than half (53/92) of these unannotated splice variants had orthologs in other non-human primates, suggesting that failure to match these peptides in the reference analyses likely arose from incomplete gene model information. The sample-specific databases also identified 101 unique peptides containing single amino acid substitutions which were missed by the reference database. Because the sample-specific searches were restricted to actively expressed transcripts, the search databases were smaller, more computationally efficient, and identified more peptides at the empirically derived 1 % false discovery rate., Conclusion: Proteogenomic approaches are ideally suited to facilitate the discovery and annotation of proteins in less widely studies animal models such as non-human primates. We expect that these approaches will help to improve existing genome annotations of non-human primate species such as vervet.

Monocytes and the recruitment of monocyte-derived macrophages into sites of inflammation play a key role in atherogenesis and other chronic inflammatory diseases linked to cardiometabolic syndrome and obesity. Previous studies from our group have shown that metabolic stress promotes monocyte priming, i.e., enhanced adhesion and accelerated chemotaxis of monocytes in response to chemokines, both in vitro and in dyslipidemic LDLR -/- mice. We also showed that metabolic stress-induced monocyte dysfunction is, at least to a large extent caused by the S -glutathionylation, inactivation, and subsequent degradation of mitogen-activated protein kinase phosphatase 1. Here, we analyzed the effects of a Western-style, dyslipidemic diet (DD), which was composed of high levels of saturated fat, cholesterol, and simple sugars, on monocyte (dys)function in non-human primates (NHPs). We found that similar to mice, a DD enhances monocyte chemotaxis in NHP within 4 weeks, occurring concordantly with the onset of hypercholesterolemia but prior to changes in triglycerides, blood glucose, monocytosis, or changes in monocyte subset composition. In addition, we identified transitory decreases in the acetylation of histone H3 at the lysine residues 18 and 23 in metabolically primed monocytes, and we found that monocyte priming was correlated with the acetylation of histone H3 at lysine 27 after an 8-week DD regimen. Our data show that metabolic stress promotes monocyte priming and hyper-chemotactic responses in NHP. The histone modifications accompanying monocyte priming in primates suggest a reprogramming of the epigenetic landscape, which may lead to dysregulated responses and functionalities in macrophages derived from primed monocytes that are recruited to sites of inflammation.

The levels of 63 cytokines, chemokines, and growth factors were measured in the serum of four patients with idiopathic morphea and of one patient with vitamin K 1 -induced morphea employing a multiplex assay to identify the role of inflammatory/immunologic events in their pathogenesis. Full-thickness skin biopsies of affected skin were analyzed by histopathology. Luminex assays for 63 cytokines, chemokines, and growth factors were performed in the sera from four patients with idiopathic morphea and in two different samples of serum obtained in two separate occasions from one patient with vitamin K 1 -induced morphea. The serum values of numerous inflammatory cytokines and growth factors including IL-2, IL-4, IL-6, and IFNβ were markedly increased in the serum of patients with idiopathic morphea, whereas, these values were normal in the serum of the patient with vitamin K 1 -induced morphea. In contrast, serum eotaxin levels were greater than threefold higher in the patient with vitamin K 1 -induced morphea compared to patients with idiopathic morphea. The results demonstrated remarkable increases in the levels of numerous cytokines and chemokines in the serum samples of all patients with idiopathic morphea indicative of a prominent role of inflammatory/immunologic events in its pathogenesis. The results also showed statistically significant differences between idiopathic morphea and vitamin K 1 -induced morphea suggesting that their development involves different pathogenetic mechanisms.

An increased level of sodium-lithium countertransport (SLC) activity has been associated with salt-sensitive hypertension. Previous findings have suggested that dysregulation of the renin-angiotensin-aldosterone system (RAAS) may be involved in the mechanism linking elevated SLC activity and hypertension. Therefore, baboons with different levels of SLC activity were given two diets differing in sodium content, with and without an angiotensin II (ANG II) infusion, to investigate the relationship between SLC activity, the RAAS, and physiological regulation by sodium. Although we anticipated that high SLC activity would be associated with inappropriate function of the RAAS and greater arterial pressure sensitivity to dietary sodium and ANG II and that low SLC activity would be associated with the least BP sensitivity, we found that the low SLC phenotype correlated with BP sensitivity similar to the high SLC phenotype, and the normal SLC phenotype showed the least BP sensitivity to dietary sodium and ANG II., (Copyright © 2017 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.)

Glutamyl aminopeptidase (ENPEP) is a member of the M1 family of endopeptidases which are mammalian type II integral membrane zinc-containing endopeptidases. ENPEP is involved in the catabolic pathway of the renin-angiotensin system forming angiotensin III, which participates in blood pressure regulation and blood vessel formation. Comparative ENPEP amino acid sequences and structures and ENPEP gene locations were examined using data from several mammalian genome projects. Mammalian ENPEP sequences shared 71-98% identities. Five N-glycosylation sites were conserved for all mammalian ENPEP proteins examined although 9-18 sites were observed, in each case. Sequence alignments, key amino acid residues and predicted secondary and tertiary structures were also studied, including transmembrane and cytoplasmic sequences and active site residues. Highest levels of human ENPEP expression were observed in the terminal ileum of the small intestine and in the kidney cortex. Mammalian ENPEP genes contained 20 coding exons. The human ENPEP gene promoter and first coding exon contained a CpG island (CpG27) and at least 6 transcription factor binding sites, whereas the 3'-UTR region contained 7 miRNA target sites, which may contribute to the regulation of ENPEP gene expression in tissues of the body. Phylogenetic analyses examined the relationships of mammalian ENPEP genes and proteins, including primate, other eutherian, marsupial and monotreme sources, using chicken ENPEP as a primordial sequence for comparative purposes.

Permissible exposure limits (PELs) for respirable crystalline silica (RCS) have recently been reduced from 0.10 to 0.05 mg/m 3 . This raises an important question: do current laboratory practices and standards for assessing RCS concentrations permit reliable discrimination between workplaces that are in compliance and workplaces that are not? To find out, this paper examines recent laboratory performance in quantifying RCS amounts on filters sent to them to assess their proficiency. A key finding is that accredited laboratories do not reliably (e.g., with 95% confidence) estimate RCS quantities to within a factor of 2. Thus, laboratory findings indicating that RCS levels are above or below a PEL provide little confidence that this is true. The current accreditation standard only requires laboratories to achieve estimates within three standard deviations of the correct (reference) value at least two thirds of the time, rather than a more usual standard such as within 25% of the correct value at least 95% of the time. Laboratory practices may improve as the new PEL is implemented, but they are presently essentially powerless to discriminate among RCS levels over most of the range of values that have been tested, leaving employers and regulators without a reliable means to ascertain when workplace RCS levels are above or below the PEL., (Copyright © 2016 Elsevier Inc. All rights reserved.)

A prior report demonstrated an unacceptably low level of accuracy in silica analytical testing, with a general negative bias (i.e., underreporting) although other inaccuracies included false-positive results when analyzing blank filters. The possible bias may have been due to the loss of sample during shipping and or sample preparation. We report on a follow-up study that was designed to mimic the original study, but in which sources of variability were evaluated. We found no effect on silica recoveries due to shipping and confirmed the prior study results that the muffle furnace ashing process led to low overall recoveries (49-104%), depending on the adherence to the recommended preparation method. Plasma ashing recoveries ranged from 89 to 108%. Our results suggest that muffle-furnace ashing using a crucible should be restricted. More broadly, however, muffle-furnace ashing is only one source of analytical error that contributes to the relatively poor overall performance revealed by Cox et al. Whatever the case, OSHA should ensure that its proposed requirements to improve laboratory performance will actually lead to the discovery and correction of all major sources of error by participating laboratories. This is particularly important in light of OSHA's proposed reduction in the PEL and action level proposed by OSHA., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Four articles by Anenberg et al., Fann et al., Shin et al., and Smith contribute valuable perspectives and syntheses to a large and growing literature that estimates the burden of mortality risks attributed to fine particulate matter (PM2.5) based on estimated epidemiological associations, summarized as concentration-response (C-R) relations. This comment questions the use of C-R relations to predict or estimate how changing exposure concentrations would change responses in a population. C-R associations typically reflect modeling choices, and equally good choices can commonly lead to conflicting conclusions about the signs, significance, and magnitudes of C-R relations and regression coefficients. This indicates that C-R relations do not necessarily reflect underlying stable causal laws useful for making risk predictions, but only choices about how to describe past data, with no uniquely correct choice being determined by the data. Similarly, currently available C-R data typically do not suffice to make valid predictions about how future changes in concentrations will affect responses. These difficulties can be substantially overcome by model ensemble and causal graph modeling and time series methods, but these require different data and knowledge-for example, knowledge of how multiple variables depend on each other, rather than only of how one dependent variable is associated with multiple explanatory variables-than that captured by traditional C-R models or expressible by any single C-R coefficient or curve., (© 2016 Society for Risk Analysis.)

SLC9B genes and proteins are members of the sodium/lithium hydrogen antiporter family which function as solute exchangers within cellular membranes of mammalian tissues. SLC9B2 and SLC9B1 amino acid sequences and structures and SLC9B -like gene locations were examined using bioinformatic data from several vertebrate genome projects. Vertebrate SLC9B2 sequences shared 56-98% identity as compared with ∼50% identities with mammalian SLC9B1 sequences. Sequence alignments, key amino acid residues and conserved predicted transmembrane structures were also studied. Mammalian SLC9B2 and SLC9B1 genes usually contained 11 or 12 coding exons with differential tissue expression patterns: SLC9B2, broad tissue distribution; and SLC9B1 , being testis specific. Transcription factor binding sites and CpG islands within the human SLC9B2 and SLC9B1 gene promoters were identified. Phylogenetic analyses suggested that SLC9B1 originated in an ancestral marsupial genome from a SLC9B2 gene duplication event., Competing Interests: Disclosure: No conflicts of interest are reported.

Naturally occurring admixture has now been documented in every major primate lineage, suggesting its key role in primate evolutionary history. Active primate hybrid zones can provide valuable insight into this process. Here, we investigate the history of admixture in one of the best-studied natural primate hybrid zones, between yellow baboons (Papio cynocephalus) and anubis baboons (Papio anubis) in the Amboseli ecosystem of Kenya. We generated a new genome assembly for yellow baboon and low-coverage genomewide resequencing data from yellow baboons, anubis baboons and known hybrids (n = 44). Using a novel composite likelihood method for estimating local ancestry from low-coverage data, we found high levels of genetic diversity and genetic differentiation between the parent taxa, and excellent agreement between genome-scale ancestry estimates and a priori pedigree, life history and morphology-based estimates (r(2)  = 0.899). However, even putatively unadmixed Amboseli yellow individuals carried a substantial proportion of anubis ancestry, presumably due to historical admixture. Further, the distribution of shared vs. fixed differences between a putatively unadmixed Amboseli yellow baboon and an unadmixed anubis baboon, both sequenced at high coverage, is inconsistent with simple isolation-migration or equilibrium migration models. Our findings suggest a complex process of intermittent contact that has occurred multiple times in baboon evolutionary history, despite no obvious fitness costs to hybrids or major geographic or behavioural barriers. In combination with the extensive phenotypic data available for baboon hybrids, our results provide valuable context for understanding the history of admixture in primates, including in our own lineage., (© 2016 John Wiley & Sons Ltd.)

Purpose: To compare the ability of Cirrus retinal nerve fiber layer (RNFL) thickness and the Color Reflectivity Discretization Analysis (CORDA), a novel optical coherence tomography (OCT) analysis method, to differentiate between normal subjects, glaucoma suspects, and glaucoma patients., Patients and Methods: Analysis of peripapillary OCT images using Cirrus SD-OCT (optic nerve head cube 200 × 200 protocol) and postacquisition CORDA analysis of peripapillary RNFL B-scan images was performed. In total, 291 eyes of 148 subjects (94 normal eyes, 100 primary open-angle glaucoma suspect eyes, and 97 eyes with primary open-angle glaucoma) were included. Area under the receiver operating characteristic curve was estimated for each region and method (Cirrus vs. CORDA) for differentiating eyes with glaucoma, and those that are glaucoma suspect, from normal eyes., Results: CORDA HR1 parameter discriminated glaucoma patients from normal subjects more accurately than Cirrus RNFL thickness in nasal (P = 0.003) and temporal (P = 0.001) regions. HR1 showed greater area under the receiver operating characteristic curve than Cirrus RNFL thickness when discriminating glaucoma suspects from normal subjects in the superior (P = 0.02), nasal (P = 0.003), and temporal (P = 0.001) regions. Both were similar for mean and the inferior regions., Conclusions: In this study, the novel CORDA HR1 differentiated between normal subjects and glaucoma suspects more accurately than Cirrus RNFL, and in temporal and nasal regions when discriminating between normal and glaucomatous eyes. CORDA analysis may improve the diagnostic accuracy of Cirrus OCT for glaucoma and glaucoma suspects.