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The GDMC AI settlement generation challenge is a procedural content generation (PCG) competition about producing an algorithm that can create a settlement in the game Minecraft. In contrast to the majority of AI competitions, the GDMC entries are evaluated by human experts on several criteria such as adaptability, functionality, evocative narrative, and visual aesthetics - all of which represent challenges to state-of-the-art PCG systems. This paper contains a collection of written experiences with this competition, by participants, judges, organizers and advisors. We asked people to reflect both on the artifacts themselves, and on the competition in general. The aim of this paper is to offer a shareable and edited collection of experiences and qualitative feedback which have the potential to push forward PCG and computational creativity, but would be lost once the individual assessments are compressed to scalar ratings. We reflect upon organizational issues for AI competitions, and discuss the future of the GDMC competition.
Abstract Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
Abstract Probiotics are linked to positive regulatory effects on the immune system. The aim of the study was to examine the association between the exposure of probiotics via dietary supplements or via infant formula by the age of 1 year and the development of celiac disease autoimmunity (CDA) and celiac disease among a cohort of 6520 genetically susceptible children. Use of probiotics during the first year of life was reported by 1460 children. Time-to-event analysis was used to examine the associations. Overall exposure of probiotics during the first year of life was not associated with either CDA (n = 1212) (HR 1.15; 95%CI 0.99, 1.35; p = 0.07) or celiac disease (n = 455) (HR 1.11; 95%CI 0.86, 1.43; p = 0.43) when adjusting for known risk factors. Intake of probiotic dietary supplements, however, was associated with a slightly increased risk of CDA (HR 1.18; 95%CI 1.00, 1.40; p = 0.043) compared to children who did not get probiotics. It was concluded that the overall exposure of probiotics during the first year of life was not associated with CDA or celiac disease in children at genetic risk.
Abstract Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Kieli: | eng |
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Julkaisija: | Hayward, Calif. : Institute of Mathematical Statistics 1982- |
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2328-3874 |
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Abstract The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.