Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

We express the mean and variance terms in a double exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the model, and whether they enter linearly or flexibly. When the variance term is null we obtain a generalized additive model, which becomes a generalized linear model if the predictors enter the mean linearly. The model is estimated using Markov chain Monte Carlo simulation and the methodology is illustrated using real and simulated data sets.Comment: 8 graphs 35 page

Transport of Cytoplasmically Synthesized Proteins into the Mitochondria in a Cell Free System from Neurospora crassa

Synthesis and transport of mitochondrial proteins were followed in a cell-free homogenate of Neurospora crassa in which mitochondrial translation was inhibited. Proteins synthesized on cytoplasmic ribosomes are transferred into the mitochondrial fraction. The relative amounts of proteins which are transferred in vitro are comparable to those transferred in whole cells. Cycloheximide and puromycin inhibit the synthesis of mitochondrial proteins but not their transfer into mitochondria. The transfer of immunoprecipitable mitochondrial proteins was demonstrated for matrix proteins, carboxyatractyloside-binding protein and cytochrome c. Import of proteins into mitochondria exhibits a degree of specificity. The transport mechanism differentiates between newly synthesized proteins and preexistent mitochondrial proteins, at least in the case of matrix proteins. In the cell-free homogenate membrane-bound ribosomes are more active in the synthesis of mitochondrial proteins than are free ribosomes. The finished translation products appear to be released from the membrane-bound ribosomes into the cytosol rather than into the membrane vesicles. The results suggest that the transport of cytoplasmically synthesized mitochondrial proteins is essentially independent of cytoplasmic translation; that cytoplasmically synthesized mitochondrial proteins exist in an extramitochondrial pool prior to import; that the site of this pool is the cytosol for at least some of the mitochondrial proteins; and that the precursors in the extramitochondrial pool differ in structure or conformation from the functional proteins in the mitochondria

A nonlinear mixed-effects modeling approach for ecological data: Using temporal dynamics of vegetation moisture as an example

Increasingly, often ecologist collects data with nonlinear trends, heterogeneous variances, temporal correlation, and hierarchical structure. Nonlinear mixed-effects models offer a flexible approach to such data, but the estimation and interpretation of these models present challenges, partly associated with the lack of worked examples in the ecological literature. We illustrate the nonlinear mixed-effects modeling approach using temporal dynamics of vegetation moisture with field data from northwestern Patagonia. This is a Mediterranean-type climate region where modeling temporal changes in live fuel moisture content are conceptually relevant (ecological theory) and have practical implications (fire management). We used this approach to answer whether moisture dynamics varies among functional groups and aridity conditions, and compared it with other simpler statistical models. The modeling process is set out “step-by-step”: We start translating the ideas about the system dynamics to a statistical model, which is made increasingly complex in order to include different sources of variability and correlation structures. We provide guidelines and R scripts (including a new self-starting function) that make data analyses reproducible. We also explain how to extract the parameter estimates from the R output. Our modeling approach suggests moisture dynamic to vary between grasses and shrubs, and between grasses facing different aridity conditions. Compared to more classical models, the nonlinear mixed-effects model showed greater goodness of fit and met statistical assumptions. While the mixed-effects approach accounts for spatial nesting, temporal dependence, and variance heterogeneity; the nonlinear function allowed to model the seasonal pattern. Parameters of the nonlinear mixed-effects model reflected relevant ecological processes. From an applied perspective, the model could forecast the time when fuel moisture becomes critical to fire occurrence. Due to the lack of worked examples for nonlinear mixed-effects models in the literature, our modeling approach could be useful to diverse ecologists dealing with complex data.Fil: Oddi, Facundo José. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Miguez, Fernando E.. University of Iowa; Estados UnidosFil: Ghermandi, Luciana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Bianchi, Lucas Osvaldo. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garibaldi, Lucas Alejandro. Universidad Nacional de Río Negro. Sede Andina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Analysing trajectories of a longitudinal exposure: A causal perspective on common methods in lifecourse research

Longitudinal data is commonly analysed to inform prevention policies for diseases that may develop throughout life. Commonly methods interpret the longitudinal data as a series of discrete measurements or as continuous patterns. Some of the latter methods condition on the outcome, aiming to capture ‘average’ patterns within outcome groups, while others capture individual-level pattern features before relating these to the outcome. Conditioning on the outcome may prevent meaningful interpretation. Repeated measurements of a longitudinal exposure (weight) and later outcome (glycated haemoglobin levels) were simulated to match three scenarios: one with no causal relationship between growth rate and glycated haemoglobin; two with a positive causal effect of growth rate on glycated haemoglobin. Two methods that condition on the outcome and one that did not were applied to the data in 1000 simulations. The interpretation of the two-step method matched the simulation in all causal scenarios, but that of the methods conditioning on the outcome did not. Methods that condition on the outcome do not accurately represent a causal relationship between a longitudinal pattern and outcome. Researchers considering longitudinal data should carefully determine if they wish to analyse longitudinal data as a series of discrete time points or by extracting pattern features

Timing of HAART Initiation and Clinical Outcomes in Human Immunodeficiency Virus Type 1 Seroconverters

BACKGROUND To estimate the clinical benefit of highly active antiretroviral therapy (HAART) initiation vs deferral in a given month in patients with CD4 cell counts less than 800/μL. METHODS In this observational cohort study of human immunodeficiency virus type 1 seroconverters from CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe), we constructed monthly sequential nested subcohorts between January 1996 and May 2009, including all eligible HAART-naive, AIDS-free individuals with a CD4 cell count less than 800/μL. The primary outcome was time to AIDS or death in those who initiated HAART in the baseline month compared with those who did not, pooled across subcohorts and stratified by CD4 cell count. Using inverse probability-of-treatment weighted survival curves and Cox proportional hazards regression models, we estimated the absolute and relative effects of treatment with robust 95% confidence intervals (CIs). RESULTS Of 9455 patients with 52,268 person-years of follow-up, 812 (8.6%) developed AIDS and 544 (5.8%) died. In CD4 cell count strata of 200 to 349, 350 to 499, and 500 to 799/μL, HAART initiation was associated with adjusted hazard ratios (95% CIs) for AIDS/death of 0.59 (0.43-0.81), 0.75 (0.49-1.14), and 1.10 (0.67-1.79), respectively. In the analysis of all-cause mortality, HAART initiation was associated with adjusted hazard ratios (95% CIs) of 0.71 (0.44-1.15), 0.51 (0.33-0.80), and 1.02 (0.49-2.12), respectively. Numbers needed to treat (95% CIs) to prevent 1 AIDS event or death within 3 years were 21 (14-38) and 34 (20-115) in CD4 cell count strata of 200 to 349 and 350 to 499/μL, respectively. CONCLUSION Compared with deferring in a given month, HAART initiation at CD4 cell counts less than 500/μL (but not 500-799/μL) was associated with slower disease progression

Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

Advantages of the single delay model for the assessment of insulin sensitivity from the intravenous glucose tolerance test

The Minimal Model, (MM), used to assess insulin sensitivity (IS) from Intra-Venous Glucose-Tolerance Test (IVGTT) data, suffers from frequent lack of identifiability (parameter estimates with Coefficients of Variation (CV) less than 52%). The recently proposed Single Delay Model (SDM) is evaluated as a practical alternative

Comparing chromosomal and mitochondrial phylogenies of the Indriidae (Primates, Lemuriformes)

The Malagasy primate family Indriidae comprises three genera with up to 19 species. Cytogenetic and molecular phylogenies of the Indriidae have been performed with special attention to the genus Propithecus. Comparative R-banding and FISH with human paints were applied to karyotypes of representatives of all three genera and confirmed most of the earlier R-banding results. However, additional chromosomal rearrangements were detected. A reticulated and a cladistic phylogeny, the latter including hemiplasies, have been performed. Cladistic analysis of cytogenetic data resulted in a phylogenetic tree revealing (1) monophyly of the family Indriidae, (2) monophyly of the genus Avahi, (3) sister–group relationships between Propithecus diadema and Propithecus edwardsi, and (4) the grouping of the latter with Indri indri, Propithecus verreauxi, and Propithecus tattersalli, and thus suggesting paraphyly of the genus Propithecus. A molecular phylogeny based on complete mitochondrial cytochrome b sequences of 16 species indicated some identical relationships, such as the monophyly of Avahi and the sister–group relationships of the eastern (P. diadema and P. edwardsi) to the western Propithecus species (P. verreauxi, Propithecus coquereli, and P. tattersalli). However, the main difference between the molecular and cytogenetic phylogenies consists in an early divergence of Indri in the molecular phylogeny while in the chromosomal phylogeny it is nested within Propithecus. The similarities and differences between molecular and cytogenetic phylogenies in relation to data on the species’ geographic distributions and mating systems allow us to propose a scenario of the evolution of Indriidae. Chromosomal and molecular processes alone or in combination created a reproductive barrier that was then followed by further speciation processes

Genetic Association Studies of Copy-Number Variation: Should Assignment of Copy Number States Precede Testing?

Recently, structural variation in the genome has been implicated in many complex diseases. Using genomewide single nucleotide polymorphism (SNP) arrays, researchers are able to investigate the impact not only of SNP variation, but also of copy-number variants (CNVs) on the phenotype. The most common analytic approach involves estimating, at the level of the individual genome, the underlying number of copies present at each location. Once this is completed, tests are performed to determine the association between copy number state and phenotype. An alternative approach is to carry out association testing first, between phenotype and raw intensities from the SNP array at the level of the individual marker, and then aggregate neighboring test results to identify CNVs associated with the phenotype. Here, we explore the strengths and weaknesses of these two approaches using both simulations and real data from a pharmacogenomic study of the chemotherapeutic agent gemcitabine. Our results indicate that pooled marker-level testing is capable of offering a dramatic increase in power (-fold) over CNV-level testing, particularly for small CNVs. However, CNV-level testing is superior when CNVs are large and rare; understanding these tradeoffs is an important consideration in conducting association studies of structural variation