Melanin-specific life-history strategies.

Abstract The maintenance of genetic variation is a long-standing issue because the adaptive value of life-history strategies associated with each genetic variant is usually unknown. However, evidence for the coexistence of alternative evolutionary fixed strategies at the population level remains scarce. Because in the tawny owl (Strix aluco) heritable melanin-based coloration shows different physiological and behavioral norms of reaction, we investigated whether coloration is associated with investment in maintenance and reproduction. Light melanic owls had lower adult survival compared to dark melanic conspecifics, and color variation was related to the trade-off between offspring number and quality. When we experimentally enlarged brood size, light melanic males produced more fledglings but in poorer condition, and they were less often recruited in the local breeding population than those of darker melanic conspecifics. Our results also suggest that dark melanic males allocate a constant effort to raise their brood independently of environmental conditions, whereas lighter melanic males finely adjust reproductive effort in relation to changes in environmental conditions. Color traits can therefore be associated with life-history strategies, and stochastic environmental perturbation can temporarily favor one phenotype over others. The existence of fixed strategies implies that some phenotypes can sometimes display a "maladapted" strategy. Long-term population monitoring is therefore vital for a full understanding of how different genotypes deal with trade-offs.

Integrating life cycle costs and environmental impacts of composite rail car-bodies for a Korean train

Background, aim, and scope A coupled Life Cycle Costing and life cycle assessment has been performed for car-bodies of the Korean Tilting Train eXpress (TTX) project using European and Korean databases, with the objective of assessing environmental and cost performance to aid materials and process selection. More specifically, the potential of polymer composite car-body structures for the Korean Tilting Train eXpress (TTX) has been investigated. Materials and methods This assessment includes the cost of both carriage manufacturing and use phases, coupled with the life cycle environmental impacts of all stages from raw material production, through carriage manufacture and use, to end-of-life scenarios. Metallic carriages were compared with two composite options: hybrid steel-composite and full-composite carriages. The total planned production for this regional Korean train was 440 cars, with an annual production volume of 80 cars. Results and discussion The coupled analyses were used to generate plots of cost versus energy consumption and environmental impacts. The results show that the raw material and manufacturing phase costs are approximately half of the total life cycle costs, whilst their environmental impact is relatively insignificant (3-8%). The use phase of the car-body has the largest environmental impact for all scenarios, with near negligible contributions from the other phases. Since steel rail carriages weigh more (27-51%), the use phase cost is correspondingly higher, resulting in both the greatest environmental impact and the highest life cycle cost. Compared to the steel scenario, the hybrid composite variant has a lower life cycle cost (16%) and a lower environmental impact (26%). Though the full composite rail carriage may have the highest manufacturing cost, it results in the lowest total life cycle costs and lowest environmental impacts. Conclusions and recommendations This coupled cost and life cycle assessment showed that the full composite variant was the optimum solution. This case study showed that coupling of technical cost models with life cycle assessment offers an efficient route to accurately evaluate economic and environmental performance in a consistent way.

Geochemical compositions of Neogene phosphatic brachiopods: Implications for ancient environmental and marine conditions

Isotopic and trace element compositions of Miocene and Pliocene phosphatic brachiopods (Lingulidae and Discinidae) from southern North Sea, the Central Paratethys and the Atlantic coast of Europe were investigated in order to trace past environmental conditions and marine connections between the northern boreal and the southern subtropical-tropical marine basins. The North Sea genus Glottidia yielded low epsilon(Nd) and high delta O-18(PO4) values through the Mio-Pliocene indicating cold habitat temperature where the local seawater was dominated by the Atlantic Ocean. In contrast, the Middle Miocene Lingulidae and Discinidae of the Paratethys inhabited warm subtropical seawater with the possible influence of the Indian Ocean via the Mediterranean, as supported by their average epsilon(Nd) value of -8.3. The combined geochemical data support a thermal and marine separation of the Paratethys from the North Sea with no direct connection or major exchange of water from the Miocene onwards. The temperature in the Paratethys was very similar to that inferred from brachiopods from the Middle Miocene of western France, but the seawater epsilon(Nd) value here is identical to that of contemporaneous Atlantic Ocean. A Late Miocene lingulid brachiopod from southern Portugal has a high delta O-18(PO4), similar to the specimens investigated from the North Sea, reflecting either a deep water habitat or formation after the onset of major global cooling that resulted in an increased delta O-18 value of seawater. The epsilon(Nd) value of -8.4 for this site is compatible with an influence of Mediterranean outflow. (C) 2012 Elsevier B.V. All rights reserved.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Environmental and T cell-intrinsic factors limit the expansion of neonatal follicular T helper cells but may be circumvented by specific adjuvants.

Follicular Th (T(FH)) cells have emerged as a new Th subset providing help to B cells and supporting their differentiation into long-lived plasma cells or memory B cells. Their differentiation had not yet been investigated following neonatal immunization, which elicits delayed and limited germinal center (GC) responses. We demonstrate that neonatal immunization induces CXCR5(high)PD-1(high) CD4(+) T(FH) cells that exhibit T(FH) features (including Batf, Bcl6, c-Maf, ICOS, and IL-21 expression) and are able to migrate into the GCs. However, neonatal T(FH) cells fail to expand and to acquire a full-blown GC T(FH) phenotype, as reflected by a higher ratio of GC T(FH)/non-GC CD4(+) T cells in immunized adults than neonates (3.8 × 10(-3) versus 2.2 × 10(-3), p = 0.01). Following the adoptive transfer of naive adult OT-II CD4(+) T cells, OT-II T(FH) cells expand in the vaccine-draining lymph nodes of immunized adult but not infant recipients, whereas naive 2-wk-old CD4(+) OT-II cells failed to expand in adult hosts, reflecting the influence of both environmental and T cell-intrinsic factors. Postponing immunization to later in life increases the number of T(FH) cells in a stepwise manner, in direct correlation with the numbers of GC B cells and plasma cells elicited. Remarkably, adjuvantation with CpG oligonucleotides markedly increased GC T(FH) and GC B cell neonatal responses, up to adult levels. To our knowledge, this is the first demonstration that the T(FH) cell development limits early life GC responses and that adjuvants/delivery systems supporting T(FH) differentiation may restore adultlike early life GC B cell responses.