Momentarily Excessive Construction As The Basis For Protoadaptation

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137522/1/evo04677.pd

Mechanistic Hierarchical Gaussian Processes

The statistics literature on functional data analysis focuses primarily on flexible black-box approaches, which are designed to allow individual curves to have essentially any shape while characterizing variability. Such methods typically cannot incorporate mechanistic information, which is commonly expressed in terms of differential equations. Motivated by studies of muscle activation, we propose a nonparametric Bayesian approach that takes into account mechanistic understanding of muscle physiology. A novel class of hierarchical Gaussian processes is defined that favors curves consistent with differential equations defined on motor, damper, spring systems. A Gibbs sampler is proposed to sample from the posterior distribution and applied to a study of rats exposed to non-injurious muscle activation protocols. Although motivated by muscle force data, a parallel approach can be used to include mechanistic information in broad functional data analysis applications

Evidence accumulation models with R: A practical guide to hierarchical Bayesian methods

Evidence accumulation models are a useful tool to allow researchers to investigate the latent cognitive variables that underlie response time and response accuracy. However, applying evidence accumulation models can be difficult because they lack easily computable forms. Numerical methods are required to determine the parameters of evidence accumulation that best correspond to the fitted data. When applied to complex cognitive models, such numerical methods can require substantial computational power which can lead to infeasibly long compute times. In this paper, we provide efficient, practical software and a step-by-step guide to fit evidence accumulation models with Bayesian methods. The software, written in C++, is provided in an R package: 'ggdmc'. The software incorporates three important ingredients of Bayesian computation, (1) the likelihood functions of two common response time models, (2) the Markov chain Monte Carlo (MCMC) algorithm (3) a population-based MCMC sampling method. The software has gone through stringent checks to be hosted on the Comprehensive R Archive Network (CRAN) and is free to download. We illustrate its basic use and an example of fitting complex hierarchical Wiener diffusion models to four shooting-decision data sets

Prevention of Neural-Tube Defects with Periconceptional Folic Acid, Methylfolate, or Multivitamins?

Background/Aims: To review the main results of intervention trials which showed the efficacy of periconceptional folic acid-containing multivitamin and folic acid supplementation in the prevention of neural-tube defects (NTD). Methods and Results: The main findings of 5 intervention trials are known: (i) the efficacy of a multivitamin containing 0.36 mg folic acid in a UK nonrandomized controlled trial resulted in an 83-91% reduction in NTD recurrence, while the results of the Hungarian (ii) randomized controlled trial and (iii) cohort-controlled trial using a multivitamin containing 0.8 mg folic acid showed 93 and 89% reductions in the first occurrence of NTD, respectively. On the other hand, (iv) another multicenter randomized controlled trial proved a 71% efficacy of 4 mg folic acid in the reduction of recurrent NTD, while (v) a public health-oriented Chinese-US trial showed a 41-79% reduction in the first occurrence of NTD depending on the incidence of NTD. Conclusions: Translational application of these findings could result in a breakthrough in the primary prevention of NTD, but so far this is not widely applied in practice. The benefits and drawbacks of 4 main possible uses of periconceptional folic acid/multivitamin supplementation, i.e. (i) dietary intake, (ii) periconceptional supplementation, (iii) flour fortification, and (iv) the recent attempt for the use of combination of oral contraceptives with 6S-5-methytetrahydrofolate (methylfolate), are discussed. Obviously, prevention of NTD is much better than the frequent elective termination of pregnancies after prenatal diagnosis of NTD fetuses

Hierarchical Generalized Linear Models for Multiple Groups of Rare and Common Variants: Jointly Estimating Group and Individual-Variant Effects

Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors. Detecting disease susceptibility variants is a challenging task, especially when their frequencies are low and/or their effects are small or moderate. We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates. The proposed hierarchical generalized linear models introduce a group effect and a genetic score (i.e., a linear combination of main-effect predictors for genetic variants) for each group of variants, and jointly they estimate the group effects and the weights of the genetic scores. This framework includes various previous methods as special cases, and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance. Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models, leading to the development of stable and flexible tools. The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/)

Effectiveness and acceptability of progestogens in combined oral contraceptives – a systematic review

BACKGROUND: The progestogen component of oral contraceptives (OCs) has undergone changes since it was recognized that their chemical structure can influence the spectrum of minor adverse and beneficial effects. METHODS: The objective of this review was to evaluate currently available low-dose OCs containing ethinylestradiol and different progestogens in terms of contraceptive effectiveness, cycle control, side effects and continuation rates. The Cochrane Controlled Trials Register, MEDLINE and EMBASE databases were searched. Randomized trials reporting clinical outcomes were considered for inclusion and were assessed for methodological quality and validity. RESULTS: Twenty–two trials were included in the review. Eighteen were sponsored by pharmaceutical companies and in only 5 there was an attempt for blinding. Most comparisons between different interventions included one to three trials, involving usually less than 500 women. Discontinuation was less with second-generation progestogens compared to first–generation (RR 0.79; 95% CI 0.69–0.91). Cycle control appeared to be better with second-compared to first-generation progestogens for both, mono-and triphasic preparations (RR 0.69; 95% CI 0.52–0.91) and (RR 0.61; 95% CI 0.43–0.85), respectively. Intermenstrual bleeding was less with third- compared to second-generation pills (RR 0.71; 95% CI 0.55–0.91). Contraceptive effectiveness of gestodene (GSD) was comparable to that of levonorgestrel (LNG), and had similar pattern of spotting, breakthrough bleeding and absence of withdrawal bleeding). Drospirenone (DRSP) was similar compared to desogestrel (DSG) regarding contraceptive effectiveness, cycle control and side effects. CONCLUSION: The third- and second-generation progestogens are preferred over first generation in all indices of acceptability. Current evidence suggests that GSD is comparable to LNG in terms of contraceptive effectiveness and for most cycle control indices. GSD is also comparable to DSG. DRSP is comparable to DSG. Future research should focus on independently conducted well designed randomized trials comparing particularly the third- with second-generation progestogens

Deletion of Genes Implicated in Protecting the Integrity of Male Germ Cells Has Differential Effects on the Incidence of DNA Breaks and Germ Cell Loss

Infertility affects approximately 20% of couples in Europe and in 50% of cases the problem lies with the male partner. The impact of damaged DNA originating in the male germ line on infertility is poorly understood but may increase miscarriage. Mouse models allow us to investigate how deficiencies in DNA repair/damage response pathways impact on formation and function of male germ cells. We have investigated mice with deletions of ERCC1 (excision repair cross-complementing gene 1), MSH2 (MutS homolog 2, involved in mismatch repair pathway), and p53 (tumour suppressor gene implicated in elimination of germ cells with DNA damage).We demonstrate for the first time that depletion of ERCC1 or p53 from germ cells results in an increased incidence of unrepaired DNA breaks in pachytene spermatocytes and increased numbers of caspase-3 positive (apoptotic) germ cells. Sertoli cell-only tubules were detected in testes from mice lacking expression of ERCC1 or MSH2 but not p53. The number of sperm recovered from epididymes was significantly reduced in mice lacking testicular ERCC1 and 40% of sperm contained DNA breaks whereas the numbers of sperm were not different to controls in adult Msh2 -/- or p53 -/- mice nor did they have significantly compromised DNA.These data have demonstrated that deletion of Ercc1, Msh2 and p53 can have differential but overlapping affects on germ cell function and sperm production. These findings increase our understanding of the ways in which gene mutations can have an impact on male fertility

Spectral Density Regression for Bivariate Extremes

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods