General Design Bayesian Generalized Linear Mixed Models

Linear mixed models are able to handle an extraordinary range of complications in regression-type analyses. Their most common use is to account for within-subject correlation in longitudinal data analysis. They are also the standard vehicle for smoothing spatial count data. However, when treated in full generality, mixed models can also handle spline-type smoothing and closely approximate kriging. This allows for nonparametric regression models (e.g., additive models and varying coefficient models) to be handled within the mixed model framework. The key is to allow the random effects design matrix to have general structure; hence our label general design. For continuous response data, particularly when Gaussianity of the response is reasonably assumed, computation is now quite mature and supported by the R, SAS and S-PLUS packages. Such is not the case for binary and count responses, where generalized linear mixed models (GLMMs) are required, but are hindered by the presence of intractable multivariate integrals. Software known to us supports special cases of the GLMM (e.g., PROC NLMIXED in SAS or glmmML in R) or relies on the sometimes crude Laplace-type approximation of integrals (e.g., the SAS macro glimmix or glmmPQL in R). This paper describes the fitting of general design generalized linear mixed models. A Bayesian approach is taken and Markov chain Monte Carlo (MCMC) is used for estimation and inference. In this generalized setting, MCMC requires sampling from nonstandard distributions. In this article, we demonstrate that the MCMC package WinBUGS facilitates sound fitting of general design Bayesian generalized linear mixed models in practice.Comment: Published at http://dx.doi.org/10.1214/088342306000000015 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Targeted Derepression of the Human Immunodeficiency Virus Type 1 Long Terminal Repeat by Pyrrole-Imidazole Polyamides

The host factor LSF represses the human immunodeficiency virus type 1 long terminal repeat (LTR) by mediating recruitment of histone deacetylase. We show that pyrrole-imidazole polyamides targeted to the LTR can specifically block LSF binding both in vitro and within cells via direct access to chromatin, resulting in increased LTR expression

Measurement error caused by spatial misalignment in environmental epidemiology

Copyright @ 2009 Gryparis et al - Published by Oxford University Press.In many environmental epidemiology studies, the locations and/or times of exposure measurements and health assessments do not match. In such settings, health effects analyses often use the predictions from an exposure model as a covariate in a regression model. Such exposure predictions contain some measurement error as the predicted values do not equal the true exposures. We provide a framework for spatial measurement error modeling, showing that smoothing induces a Berkson-type measurement error with nondiagonal error structure. From this viewpoint, we review the existing approaches to estimation in a linear regression health model, including direct use of the spatial predictions and exposure simulation, and explore some modified approaches, including Bayesian models and out-of-sample regression calibration, motivated by measurement error principles. We then extend this work to the generalized linear model framework for health outcomes. Based on analytical considerations and simulation results, we compare the performance of all these approaches under several spatial models for exposure. Our comparisons underscore several important points. First, exposure simulation can perform very poorly under certain realistic scenarios. Second, the relative performance of the different methods depends on the nature of the underlying exposure surface. Third, traditional measurement error concepts can help to explain the relative practical performance of the different methods. We apply the methods to data on the association between levels of particulate matter and birth weight in the greater Boston area.This research was supported by NIEHS grants ES012044 (AG, BAC), ES009825 (JS, BAC), ES007142 (CJP), and ES000002 (CJP), and EPA grant R-832416 (JS, BAC)

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in sub-Saharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM2.5) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39–62% of total PM2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10–45 μg/m3. Road dust and vehicle emissions comprised 12–33% of PM2.5 mass. Solid waste burning was also a significant contributor to household PM2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM2.5, accounting for 74–87% of its total mass; the relative and absolute contributions of biomass smoke to PM2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa

Effects of the noradrenergic agonist clonidine on temporal and spatial attention

Rationale: Recent theories posit an important role for the noradrenergic system in attentional selection in the temporal domain. In contrast, the spatially diffuse topographical projections of the noradrenergic system are inconsistent with a direct role in spatial selection. Objectives: To test the hypotheses that pharmacological attenuation of central noradrenergic activity should (1) impair performance on the attentional blink task, a task requiring the selection of targets in a rapid serial visual stream of stimuli; and (2) leave intact the efficiency of the search for a target in a two-dimensional visuospatial stimulus array. Materials and methods: Thirty-two healthy adult human subjects performed an attentional blink task and a visual search task in a double-blind, placebo-controlled, between-subject study investigating the effects of the α2 adrenoceptor agonist clonidine (150 μg, oral dose). Results: No differential effects of clonidine vs placebo were found on the attentional blink performance. Clonidine slowed overall reaction times in the visual search task but did not impair the efficiency of the visual search. Conclusions: The attentional blink results are inconsistent with recent theories about the role of the noradrenergic system in temporal filtering and in mediating the attentional blink. This discrepancy between theory and data is discussed in detail. The visual search results, in combination with previous findings, suggest that the noradrenergic system is not directly involved in spatial attention processes but instead can modulate these processes in an indirect fashion. © 2007 Springer-Verlag

Integrated measures of lead and manganese exposure improve estimation of their joint effects on cognition in Italian school-age children

Every day humans are exposed to mixtures of chemicals, such as lead (Pb) and manganese (Mn). An underappreciated aspect of studying the health effects of mixtures is the role that the exposure biomarker media (blood, hair, etc.) may play in estimating the effects of the mixture. Different biomarker media represent different aspects of each chemical's toxicokinetics, thus no single medium can fully capture the toxicokinetic profile for all the chemicals in a mixture. A potential solution to this problem is to combine exposure data across different media to derive integrated estimates of each chemical's internal concentration. This concept, formalized as a multi-media biomarker (MMB) has proven effective for estimating the health impacts of Pb exposure, but may also be useful to estimate mixture effects, such as the joint effects of metals like Pb and Mn, while factoring in how the association changes based upon the biomarker media. Levels of Pb and Mn were quantified in five media: blood, hair, nails, urine, and saliva in the Public Health Impact of Metals Exposure (PHIME) project, a study of Italian adolescents aged 10–14 years. MMBs were derived for both metals using weighted quantile sum (WQS) regression across the five media. Age-adjusted Wechsler Intelligence Scale for Children (WISC) IQ scores, measured at the same time as the exposure measures, were the primary outcome and models were adjusted for sex and socioeconomic status. The levels Pb and Mn were relatively low, with median blood Pb of 1.27 (IQR: 0.84) μg/dL and median blood Mn of 1.09 (IQR: 0.45) μg/dL. Quartile increases in a Pb-Mn combination predicted decreased Full Scale IQ of 1.9 points (95% CI: 0.3, 3.5) when Pb and Mn exposure levels were estimated using MMBs, while individual regressions for each metal were not associated with Full Scale IQ. Additionally, a quartile increase in the WQS index of Pb and Mn, measured using MMBs, were associated with reductions in Verbal IQ by 2.8 points (1.0, 4.5). Weights that determine the contributions of the metals to the joint effect highlighted that the contribution of the Pb-Mn was 72–28% for Full Scale IQ and 42–58% for Verbal IQ. We found that the joint effects of Pb and Mn are strongly affected by the medium used to measure exposure and that the joint effects of the Pb and Mn MMBs on cognition were the stronger than any individual biomarker. Thus, increase power and accuracy for measuring mixture effects compared to individual biomarkers. As the number of chemicals in mixtures increases, appropriate biomarker selection will become increasingly important and MMBs are a natural way to reduce bias in such analyses

Medium-Term Exposure to Traffic-Related Air Pollution and Markers of Inflammation and Endothelial Function

Bac k g r o u n d: Exposure to traffic-related air pollution (TRAP) contributes to increased cardiovascular risk. Land-use regression models can improve exposure assessment for TRAP. Objectives: We examined the association between medium-term concentrations of black carbon (BC) estimated by land-use regression and levels of soluble intercellular adhesion molecule-1 (sICAM-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1), both markers of inflammatory and endothelial response. Me t h o d s: We studied 642 elderly men participating in the Veterans Administration (VA) Normative Aging Study with repeated measurements of sICAM‑1 and sVCAM‑1 during 1999–2008. Daily estimates of BC exposure at each geocoded participant address were derived using a validated spatiotemporal model and averaged to form 4-, 8-, and 12-week exposures. We used linear mixed models to estimate associations, controlling for confounders. We examined effect modification by statin use, obesity, and diabetes. Re s u l t s: We found statistically significant positive associations between BC and sICAM‑1 for averages of 4, 8, and 12 weeks. An interquartile-range increase in 8-week BC exposure (0.30 μg/m3) was associated with a 1.58 % increase in sICAM‑1 (95 % confidence interval, 0.18–3.00%). Overall association

Impact of biomass fuels on pregnancy outcomes in central East India

Background: Smoke from biomass burning has been linked to reduced birth weight; association with other birth outcomes is poorly understood. Our objective was to evaluate effects of exposure to biomass smoke on birth weight, preterm birth and stillbirth. Methods: Information on household cooking fuel was available for secondary analysis from two cohorts of pregnant women enrolled at delivery in India (n = 1744). Birth weight was measured and the modified Ballard performed to assess gestational age. Linear and logistic regression models were used to explore associations between fuel and birth outcomes. Effect sizes were adjusted in multivariate models for socio-demographic characteristics using propensity score techniques and for medical/obstetric covariates. Results: Compared to women who use gas (n = 265), women cooking with wood (n = 1306) delivered infants that were on average 112 grams lighter (95% CI -170.1, -54.6) and more likely to be preterm (OR 3.11, 95% CI 2.12, 4.59). Stillbirths were also more common in the wood group (4% versus 0%, p < 0.001). In adjusted models, the association between wood use and birth weight was no longer significant (14 g reduction; 95% CI -93, 66); however, the increased odds for preterm birth persisted (aOR 2.29; 95% CI 1.24, 4.21). Wood fuel use did not increase the risk of delivering either a low birth weight or small for gestational age infant. Conclusions: The association between wood fuel use and reduced birth weight was insignificant in multivariate models using propensity score techniques to account for socio-demographic differences. In contrast, we demonstrated a persistent adverse impact of wood fuel use on preterm delivery. If prematurity is confirmed as a consequence of antenatal exposure to household air pollution, perinatal morbidity and mortality from household air pollution may be higher than previously appreciated

Modeling User Search Behavior for Masquerade Detection

Masquerade attacks are a common security problem that is a consequence of identity theft. This paper extends prior work by modeling user search behavior to detect deviations indicating a masquerade attack. We hypothesize that each individual user knows their own file system well enough to search in a limited, targeted and unique fashion in order to find information germane to their current task. Masqueraders, on the other hand, will likely not know the file system and layout of another user's desktop, and would likely search more extensively and broadly in a manner that is different than the victim user being impersonated. We identify actions linked to search and information access activities, and use them to build user models. The experimental results show that modeling search behavior reliably detects all masqueraders with a very low false positive rate of 1.1%, far better than prior published results. The limited set of features used for search behavior modeling also results in large performance gains over the same modeling techniques that use larger sets of features

Salinity drives meiofaunal community structure dynamics across the Baltic ecosystem

Coastal benthic biodiversity is under increased pressure from climate change, eutrophication, hypoxia, and changes in salinity due to increase in river runoff. The Baltic Sea is a large brackish system characterized by steep environmental gradients that experiences all of the mentioned stressors. As such it provides an ideal model system for studying the impact of on‐going and future climate change on biodiversity and function of benthic ecosystems. Meiofauna (animals &lt; 1 mm) are abundant in sediment and are still largely unexplored even though they are known to regulate organic matter degradation and nutrient cycling. In this study, benthic meiofaunal community structure was analysed along a salinity gradient in the Baltic Sea proper using high‐throughput sequencing. Our results demonstrate that areas with higher salinity have a higher biodiversity, and salinity is probably the main driver influencing meiofauna diversity and community composition. Furthermore, in the more diverse and saline environments a larger amount of nematode genera classified as predators prevailed, and meiofauna‐macrofauna associations were more prominent. These findings show that in the Baltic Sea, a decrease in salinity resulting from accelerated climate change will probably lead to decreased benthic biodiversity, and cause profound changes in benthic communities, with potential consequences for ecosystem stability, functions and services