Moral reasoning and homosexuality: the acceptability of arguments about lesbian and gay issues

In the political arena, lesbian and gay issues have typically been contested on grounds of human rights, but with variable success. Using a moral developmental framework, the purpose of this study was to explore preferences for different types of moral arguments when thinking about moral dilemmas around lesbian and gay issues. The analysis presented here comprised data collected from 545 students at UK universities, who completed a questionnaire, part of which comprised a moral dilemma task. Findings of the study showed that respondents do not apply moral reasoning consistently, and do not (clearly) favour human rights reasoning when thinking about lesbian and gay issues. Respondents tended to favour reasoning supporting existing social structures and frameworks, therefore this study highlights the importance of structural change in effecting widespread attitude change in relation to lesbian and gay rights issues. The implications of the findings for moral education are also discussed.</p

Towards evolutionary predictions:Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions

Effects of environmental pollutants on the reproduction and welfare of ruminants

Anthropogenic pollutants comprise a wide range of synthetic organic compounds and heavy metals, which are dispersed throughout the environment, usually at low concentrations. Exposure of ruminants, as for all other animals, is unavoidable and while the levels of exposure to most chemicals are usually too low to induce any physiological effects, combinations of pollutants can act additively or synergistically to perturb multiple physiological systems at all ages but particularly in the developing foetus. In sheep, organs affected by pollutant exposure include the ovary, testis, hypothalamus and pituitary gland and bone. Reported effects of exposure include changes in organ weight and gross structure, histology and gene and protein expression but these changes are not reflected in changes in reproductive performance under the conditions tested. These results illustrate the complexity of the effects of endocrine disrupting compounds on the reproductive axis, which make it difficult to extrapolate between, or even within, species. Effects of pollutant exposure on the thyroid gland, immune, cardiovascular and obesogenic systems have not been shown explicitly, in ruminants, but work on other species suggests that these systems can also be perturbed. It is concluded that exposure to a mixture of anthropogenic pollutants has significant effects on a wide variety of physiological systems, including the reproductive system. Although this physiological insult has not yet been shown to lead to a reduction in ruminant gross performance, there are already reports indicating that anthropogenic pollutant exposure can compromise several physiological systems and may pose a significant threat to both reproductive performance and welfare in the longer term. At present, many potential mechanisms of action for individual chemicals have been identified but knowledge of factors affecting the rate of tissue exposure and of the effects of combinations of chemicals on physiological systems is poor. Nevertheless, both are vital for the identification of risks to animal productivity and welfare

Optical properties of dust

http://arxiv.org/abs/0808.4123Except in a few cases cosmic dust can be studied in situ or in terrestrial laboratories, essentially all of our information concerning the nature of cosmic dust depends upon its interaction with electromagnetic radiation. This chapter presents the theoretical basis for describing the optical properties of dust -- how it absorbs and scatters starlight and reradiates the absorbed energy at longer wavelengths.Partial support by a Chandra Theory program and HST Theory Programs is gratefully acknowledged

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function