Direct genetic demonstration of Gα13 coupling to the orphan G protein-coupled receptor G2A leading to RhoA-dependent actin rearrangement

G2A is an orphan G protein-coupled receptor (GPCR), expressed predominantly in T and B cells and homologous to a small group of GPCRs of unknown function expressed in lymphoid tissues. G2A is transcriptionally induced in response to diverse stimuli, and its ectopic expression suppresses transformation of B lymphoid precursors by BCR-ABL. G2A induces morphological transformation of NIH 3T3 fibroblasts. Microinjection of constructs encoding G2A into Swiss 3T3 fibroblasts induces actin reorganization into stress fibers that depends on RhoA, but not CDC42 or RAC. G2A elicits RhoA-dependent transcriptional activation of serum response factor. Direct evaluation of RhoA activity demonstrates elevated levels of RhoA-GTP in G2A-expressing cells. Microinjection of embryonic fibroblasts derived from various Galpha knockout mice establishes a requirement for Galpha 13 but not Galpha 12 or Galpha q/11 in G2A-induced actin rearrangement. In conclusion, G2A represents a family of GPCRs expressed in lymphocytes that may link diverse stimuli to cytoskeletal reorganization and transcriptional activation through a pathway involving Galpha 13 and RhoA

Happy to help? Exploring the factors associated with variations in rates of volunteering across Europe

The frequency of formal volunteering varies widely across European countries, and rates of formal volunteering are especially low among Eastern European countries. Why are there such large differences in volunteering rates when it is known that volunteering is beneficial for well-being? Using data from the latest round of the European Social Survey, we test three hypotheses to explain these cross-national differences in volunteering. We ask whether people in countries with low frequencies of volunteering spend more of their time on informal volunteering activities; whether they differ on socio-demographic variables which are known to be linked to volunteering rates; or whether they show less well-being benefit from formal volunteering. Contrary to the first hypothesis, we find a positive correlation between formal and informal volunteering. We further conclude that national differences in rates of volunteering cannot be fully explained by differences in the social, psychological or cultural factors associated with volunteering nor the outcome of volunteering. It is likely that contextual factors, such as a country’s historical background or institutions, determine levels of volunteering to a large extent

Time spent on work-related activities, social activities and time pressure as intermediary determinants of health disparities among elderly women and men in 5 European countries: a structural equation model

Background Psychosocial factors shape the health of older adults through complex inter-relating pathways. Besides socioeconomic factors, time use activities may explain gender inequality in self-reported health. This study investigated the role of work-related and social time use activities as determinants of health in old age. Specifically, we analysed whether the impact of stress in terms of time pressure on health mediated the relationship between work-related time use activities (i.e. housework and paid work) on self-reported health. Methods We applied structural equation models and a maximum-likelihood function to estimate the direct and indirect effects of psychosocial factors on health using pooled data from the Multinational Time Use Study on 11,168 men and 14,295 women aged 65+ from Italy, Spain, UK, France and the Netherlands. Results The fit indices for the conceptual model indicated an acceptable fit for both men and women. The results showed that socioeconomic status (SES), demographic factors, stress and work-related time use activities after retirement had a significant direct influence on self-reported health among the elderly, but the magnitude of the effects varied by gender. Social activities had a positive impact on self-reported health but had no significant impact on stress among older men and women. The indirect standardized effects of work-related activities on self-reported health was statistically significant for housework (β = − 0.006; P  0.05 among women), which implied that the paths from paid work and housework on self-reported health via stress (mediator) was very weak because their indirect effects were close to zero. Conclusions Our findings suggest that although stress in terms of time pressure has a direct negative effect on health, it does not indirectly influence the positive effects of work-related time use activities on self-reported health among elderly men and women. The results support the time availability hypothesis that the elderly may not have the same time pressure as younger adults after retirement

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

Genetical genomics of growth in a chicken model

Background: The genetics underlying body mass and growth are key to understanding a wide range of topics in biology, both evolutionary and developmental. Body mass and growth traits are affected by many genetic variants of small effect. This complicates genetic mapping of growth and body mass. Experimental intercrosses between individuals from divergent populations allows us to map naturally occurring genetic variants for selected traits, such as body mass by linkage mapping. By simultaneously measuring traits and intermediary molecular phenotypes, such as gene expression, one can use integrative genomics to search for potential causative genes. Results: In this study, we use linkage mapping approach to map growth traits (N = 471) and liver gene expression (N = 130) in an advanced intercross of wild Red Junglefowl and domestic White Leghorn layer chickens. We find 16 loci for growth traits, and 1463 loci for liver gene expression, as measured by microarrays. Of these, the genes TRAK1, OSBPL8, YEATS4, CEP55, and PIP4K2B are identified as strong candidates for growth loci in the chicken. We also show a high degree of sex-specific gene-regulation, with almost every gene expression locus exhibiting sex-interactions. Finally, several trans-regulatory hotspots were found, one of which coincides with a major growth locus. Conclusions: These findings not only serve to identify several strong candidates affecting growth, but also show how sex-specificity and local gene-regulation affect growth regulation in the chicken.Funding Agencies|Carl Tryggers Stiftelse; Swedish Research Council (VR); Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS); Linkoping University Neuro-network; European Research Council [GENEWELL 322206]</p