When and why do third parties punish outside of the lab? A cross-cultural recall study

Punishment can reform uncooperative behavior and hence could have contributed to humans&rsquo; ability to live in large-scale societies. Punishment by unaffected third parties has received extensive scientific scrutiny because third parties punish transgressors in laboratory experiments on behalf of strangers that they will never interact with again. Often overlooked in this research are interactions involving people who are not strangers, which constitute many interactions beyond the laboratory. Across three samples in two countries (United States and Japan; N = 1,294), we found that third parties&rsquo; anger at transgressors, and their intervention and punishment on behalf of victims, varied in real-life conflicts as a function of how much third parties valued the welfare of the disputants. Punishment was rare (1&ndash;2%) when third parties did not value the welfare of the victim, suggesting that previous economic game results have overestimated third parties&rsquo; willingness to punish transgressors on behalf of strangers.</p

Influences on the triple alpha process beyond the Hoyle state

7 pags., 3 figs. -- International Symposium on Nuclear Astrophysics - Nuclei in the Cosmos - IX, 25-30 June 2006, CERNThe triple alpha process is studied using indirect methods. The beta decays of 12N and 12B are used to probe the triple alpha continuum of 12C. Different independent breakup channels are identified, consistently showing that the 10 MeV strength is dominated by a 0+ state interfering with the Hoyle state ghost. The 13–14 MeV region on the other hand is dominated by a 2 + state

The gut microbiota in multiple sclerosis varies with disease activity

BACKGROUND: Multiple sclerosis is a chronic immune-mediated disease of the brain and spinal cord resulting in physical and cognitive impairment in young adults. It is hypothesized that a disrupted bacterial and viral gut microbiota is a part of the pathogenesis mediating disease impact through an altered gut microbiota-brain axis. The aim of this study is to explore the characteristics of gut microbiota in multiple sclerosis and to associate it with disease variables, as the etiology of the disease remains only partially known. METHODS: Here, in a case-control setting involving 148 Danish cases with multiple sclerosis and 148 matched healthy control subjects, we performed shotgun sequencing of fecal microbial DNA and associated bacterial and viral microbiota findings with plasma cytokines, blood cell gene expression profiles, and disease activity. RESULTS: We found 61 bacterial species that were differentially abundant when comparing all multiple sclerosis cases with healthy controls, among which 31 species were enriched in cases. A cluster of inflammation markers composed of blood leukocytes, CRP, and blood cell gene expression of IL17A and IL6 was positively associated with a cluster of multiple sclerosis-related species. Bacterial species that were more abundant in cases with disease-active treatment-naïve multiple sclerosis were positively linked to a group of plasma cytokines including IL-22, IL-17A, IFN-β, IL-33, and TNF-α. The bacterial species richness of treatment-naïve multiple sclerosis cases was associated with number of relapses over a follow-up period of 2 years. However, in non-disease-active cases, we identified two bacterial species, Faecalibacterium prausnitzii and Gordonibacter urolithinfaciens, whose absolute abundance was enriched. These bacteria are known to produce anti-inflammatory metabolites including butyrate and urolithin. In addition, cases with multiple sclerosis had a higher viral species diversity and a higher abundance of Caudovirales bacteriophages. CONCLUSIONS: Considerable aberrations are present in the gut microbiota of patients with multiple sclerosis that are directly associated with blood biomarkers of inflammation, and in treatment-naïve cases bacterial richness is positively associated with disease activity. Yet, the finding of two symbiotic bacterial species in non-disease-active cases that produce favorable immune-modulating compounds provides a rationale for testing these bacteria as adjunct therapeutics in future clinical trials

Maternal depression during pregnancy and cord blood DNA methylation: findings from the Avon Longitudinal Study of Parents and Children

Up to 13% of women may experience symptoms of depression during pregnancy or in the postpartum period. Depression during pregnancy has been associated with an increased risk of adverse neurodevelopmental outcomes in the child and epigenetic mechanisms could be one of the biological pathways to explain this association. In 844 mother–child pairs from the Avon Longitudinal Study of Parents and Children, we carried out an epigenome-wide association study (EWAS) to investigate associations between prospectively collected data on maternal depression ascertained by the Edinburgh Postnatal Depression Scale in pregnancy and DNA methylation in the cord blood of newborn offspring. In individual site analysis, we identified two CpG sites associated with maternal depression in the middle part of pregnancy. In our regional analysis, we identified 39 differentially methylated regions (DMRs). Seven DMRs were associated with depression at any time point during pregnancy, 7 associated with depression in mid-pregnancy, 23 were associated with depression in late pregnancy, and 2 DMRs were associated with depression throughout pregnancy. Several of these map to genes associated with psychiatric disease and brain development. We attempted replication in The Generation R Study and could not replicate our results. Although our findings in ALSPAC suggest that maternal depression could be associated with cord blood DNA methylation the results should be viewed as preliminary and hypothesis generating until further replicated in a larger sample

Detecting the Dependent Evolution of Biosequences

A probabilistic graphical model is developed in order to detect the dependent evolution between different sites in biological sequences. Given a multiple sequence alignment for each molecule of interest and a phylogenetic tree, the model can predict potential interactions within or between nucleic acids and proteins. Initial validation of the model is carried out using tRNA sequence data. The model is able to accurately identify the secondary structure of tRNA as well as several known tertiary interactions