英語母語話者と日本人学習者の英語動詞運用

博士（学術）神戸大

Model-based prediction of human hair color using DNA variants

Predicting complex human phenotypes from genotypes is the central concept of widely advocated personalized medicine, but so far has rarely led to high accuracies limiting practical applications. One notable exception, although less relevant for medical but important for forensic purposes, is human eye color, for which it has been recently demonstrated that highly accurate prediction is feasible from a small number of DNA variants. Here, we demonstrate that human hair color is predictable from DNA variants with similarly high accuracies. We analyzed in Polish Europeans with single-observer hair color grading 45 single nucleotide polymorphisms (SNPs) from 12 genes previously associated with human hair color variation. We found that a model based on a subset of 13 single or compound genetic markers from 11 genes predicted red hair color with over 0.9, black hair color with almost 0.9, as well as blond, and brown hair color with over 0.8 prevalence-adjusted accuracy expressed by the area under the receiver characteristic operating curves (AUC). The identified genetic predictors also differentiate reasonably well between similar hair colors, such as between red and blond-red, as well as between blond and dark-blond, highlighting the value of the identified DNA variants for accurate hair color prediction

On quantifying uncertainties for the linearized BGK kinetic equation

We consider the linearized BGK equation and want to quantify uncertainties in the case of modelling errors. More specifically, we want to quantify the error produced if the pre-determined equilibrium function is chosen inaccurately. In this paper we consider perturbations in the velocity and in the temperature of the equilibrium function and consider how much the error is amplified in the solution

Swarming in shallow waters

A swarm is a collection of separate objects that move autonomously in the same direction in a concerted fashion. This type of behavior is observed in ensembles of various organisms but has proven inherently difficult to realize in artificial chemical systems, where the components have to self-assemble dynamically and, at the same time, propel themselves. This paper describes a class of systems in which millimeter-sized components interact hydrodynamically and organize into dissipative structures that swarm in thin fluid layers. Depending on the geometry of the particles, various types of swarms can be engineered, including ensembles that rotate, follow a "leader", or are pushed in front of a larger particle

Global skin colour prediction from DNA

Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics

Widespread hybridization in the introduced hog deer population of Victoria, Australia, and its implications for conservation

In Australia, many species have been introduced that have since undergone drastic declines in their native range. One species of note is the hog deer (Axis porcinus) which was introduced in the 1860s to Victoria, Australia, and has since become endangered in its native range throughout South-East Asia. There is increased interest in using non-native populations as a source for genetic rescue; however, considerations need to be made of the genetic suitability of the non-native population. Three mitochondrial markers and two nuclear markers were sequenced to assess the genetic variation of the Victorian population of hog deer, which identified that the Victorian population has hybrid origins with the closely related chital (Axis axis), a species that is no longer present in the wild in Victoria. In addition, the mitochondrial D-loop region within the Victorian hog deer is monomorphic, demonstrating that mitochondrial genetic diversity is very low within this population. This study is the first to report of long-term persistence of hog deer and chital hybrids in a wild setting, and the continual survival of this population suggests that hybrids of these two species are fertile. Despite the newly discovered hybrid status in Victorian hog deer, this population may still be beneficial for future translocations within the native range. However, more in-depth analysis of genetic diversity within the Victorian hog deer population and investigation of hybridization rates within the native range are necessary before translocations are attempted

MC1R variants increased the risk of sporadic cutaneous melanoma in darker-pigmented Caucasians: A pooled-analysis from the M-SKIP project.

The MC1R gene is a key regulator of skin pigmentation. We aimed to evaluate the association between MC1R variants and the risk of sporadic cutaneous melanoma (CM) within the M-SKIP project, an international pooled-analysis on MC1R, skin cancer and phenotypic characteristics. Data included 5,160 cases and 12,119 controls from 17 studies. We calculated a summary odds ratio (SOR) for the association of each of the nine most studied MC1R variants and of variants combined with CM by using random-effects models. Stratified analysis by phenotypic characteristics were also performed. Melanoma risk increased with presence of any of the main MC1R variants: the SOR for each variant ranged from 1.47 (95%CI: 1.17\u20131.84) for V60L to 2.74 (1.53\u20134.89) for D84E. Carriers of any MC1R variant had a 66% higher risk of developing melanoma compared with wild-type subjects (SOR; 95%CI: 1.66; 1.41\u20131.96) and the risk attributable to MC1R variants was 28%. When taking into account phenotypic characteristics, we found that MC1R-associated melanoma risk increased only for darker-pigmented Caucasians: SOR (95%CI) was 3.14 (2.06\u20134.80) for subjects with no freckles, no red hair and skin Type III/IV. Our study documents the important role of all the main MC1R variants in sporadic CM and suggests that they have a direct effect on melanoma risk, independently on the phenotypic characteristics of carriers. This is of particular importance for assessing preventive strategies, which may be directed to darker-pigmented Caucasians with MC1R variants as well as to lightly pigmented, fair-skinned subjects

Managing Carbon Aspirations: The Influence of Corporate Climate Change Targets on Environmental Performance

Addressing climate change is among the most challenging ethical issues facing contemporary business and society. Unsustainable business activities are causing significant distributional and procedural injustices in areas such as public health and vulnerability to extreme weather events, primarily because of a distinction between primary emitters and those already experiencing the impacts of climate change. Business, as a significant contributor to climate change and beneficiary of externalizing environmental costs, has an obligation to address its environmental impacts. In this paper, we explore the role of firms’ climate change targets in shaping their emissions trends in the context of a large multi-country sample of companies. We contrast two intentions for setting emissions reductions targets: symbolic attempts to manage external stakeholder perceptions via “greenwashing” and substantive commitments to reducing environmental impacts. We argue that the attributes of firms’ climate change targets (their extent, form, and time horizon) are diagnostic of firms’ underlying intentions. Consistent with our hypotheses, while we find no overall effect of setting climate change targets on emissions, we show that targets characterized by a commitment to more ambitious emissions reductions, a longer target time frame, and absolute reductions in emissions are associated with significant reductions in firms’ emissions. Our evidence suggests the need for vigilance among policy-makers and environmental campaigners regarding the underlying intentions that accompany environmental management practices and shows that these can to some extent be diagnosed analytically

Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project

Background: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods. Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer dev