Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

The ethics of digital well-being: a multidisciplinary perspective

This chapter serves as an introduction to the edited collection of the same name, which includes chapters that explore digital well-being from a range of disciplinary perspectives, including philosophy, psychology, economics, health care, and education. The purpose of this introductory chapter is to provide a short primer on the different disciplinary approaches to the study of well-being. To supplement this primer, we also invited key experts from several disciplines—philosophy, psychology, public policy, and health care—to share their thoughts on what they believe are the most important open questions and ethical issues for the multi-disciplinary study of digital well-being. We also introduce and discuss several themes that we believe will be fundamental to the ongoing study of digital well-being: digital gratitude, automated interventions, and sustainable co-well-being

Synthetic microparticles conjugated with VEGF165 improve the survival of endothelial progenitor cells via microRNA-17 inhibition

Several cell-based therapies are under pre-clinical and clinical evaluation for the treatment of ischemic diseases. Poor survival and vascular engraftment rates of transplanted cells force them to work mainly via time-limited paracrine actions. Although several approaches, including the use of soluble vascular endothelial growth factor (sVEGF)-VEGF165, have been developed in the last 10 years to enhance cell survival, they showed limited efficacy. Here, we report a pro-survival approach based on VEGF-immobilized microparticles (VEGF-MPs). VEGF-MPs prolong VEGFR-2 and Akt phosphorylation in cord blood-derived late outgrowth endothelial progenitor cells (OEPCs). In vivo, OEPC aggregates containing VEGF-MPs show higher survival than those treated with sVEGF. Additionally, VEGF-MPs decrease miR-17 expression in OEPCs, thus increasing the expression of its target genes CDKN1A and ZNF652. The therapeutic effect of OEPCs is improved in vivo by inhibiting miR-17. Overall, our data show an experimental approach to improve therapeutic efficacy of proangiogenic cells for the treatment of ischemic diseases.Soluble vascular endothelial growth factor (VEGF) enhances vascular engraftment of transplanted cells but the efficacy is low. Here, the authors show that VEGF-immobilized microparticles prolong survival of endothelial progenitors in vitro and in vivo by downregulating miR17 and upregulating CDKN1A and ZNF652

Rift Valley Fever Virus Seroprevalence in Human Rural Populations of Gabon

Rift Valley fever (RVF) is a disease transmitted by a mosquito bite (Aedes). Humans can also be infected through direct contact with blood (aerosols) or tissues (placenta, stillborn) of infected animals. Although severe clinical cases can be observed, infection with RVF virus (RVFV) in humans in most cases causes a febrile illness without serious symptoms. In small ruminants RVFV mainly causes abortion and neonatal death. RVFV distribution has been poorly investigated in Central Africa. We conducted a large scale serological survey of RVF antibodies in rural populations in Gabon, involving 4,323 individuals from 212 randomly selected villages. The results showed an overall RVFV prevalence of 3.3%, with values of 2.9% in the forested zones, 2.2% in savannas and 8.3% in the lakes region. These findings strongly suggest for the first time the wide circulation of Rift valley fever virus in Gabon and the possible existence of a sylvan cycle of RVF virus in this country. The serological higher prevalence in the lake region suggests that this region is likely to have particular ecological conditions, especially mosquito vector species, favoring the circulation of this virus. In Gabon, human cases of RVF may occur but are either misdiagnosed or not reported

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases