Proton-Antiproton Annihilation into a Lambda_c-Antilambda_c Pair

The process p-pbar -> Lambda_c-Antilambda_c is investigated within the handbag approach. It is shown that the dominant dynamical mechanism, characterized by the partonic subprocess u-ubar -> c-cbar factorizes in the sense that only the subprocess contains highly virtual partons, a gluon to lowest order of perturbative QCD, while the hadronic matrix elements embody only soft scales and can be parameterized in terms of helicity flip and non-flip generalized parton distributions. Modelling these parton distributions by overlaps of light-cone wave functions for the involved baryons we are able to predict cross sections and spin correlation parameters for the process of interest.Comment: 39 pages, 7 figures, problems with printout of figures resolved, Ref. 33 and referring sentences in section 4 change

Airborne Signals from a Wounded Leaf Facilitate Viral Spreading and Induce Antibacterial Resistance in Neighboring Plants

Many plants release airborne volatile compounds in response to wounding due to pathogenic assault. These compounds serve as plant defenses and are involved in plant signaling. Here, we study the effects of pectin methylesterase (PME)-generated methanol release from wounded plants (“emitters”) on the defensive reactions of neighboring “receiver” plants. Plant leaf wounding resulted in the synthesis of PME and a spike in methanol released into the air. Gaseous methanol or vapors from wounded PME-transgenic plants induced resistance to the bacterial pathogen Ralstonia solanacearum in the leaves of non-wounded neighboring “receiver” plants. In experiments with different volatile organic compounds, gaseous methanol was the only airborne factor that could induce antibacterial resistance in neighboring plants. In an effort to understand the mechanisms by which methanol stimulates the antibacterial resistance of “receiver” plants, we constructed forward and reverse suppression subtractive hybridization cDNA libraries from Nicotiana benthamiana plants exposed to methanol. We identified multiple methanol-inducible genes (MIGs), most of which are involved in defense or cell-to-cell trafficking. We then isolated the most affected genes for further analysis: β-1,3-glucanase (BG), a previously unidentified gene (MIG-21), and non-cell-autonomous pathway protein (NCAPP). Experiments with Tobacco mosaic virus (TMV) and a vector encoding two tandem copies of green fluorescent protein as a tracer of cell-to-cell movement showed the increased gating capacity of plasmodesmata in the presence of BG, MIG-21, and NCAPP. The increased gating capacity is accompanied by enhanced TMV reproduction in the “receivers”. Overall, our data indicate that methanol emitted by a wounded plant acts as a signal that enhances antibacterial resistance and facilitates viral spread in neighboring plants

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Influence of Snowmelt Timing on the Diet Quality of Pyrenean Rock Ptarmigan (Lagopus muta pyrenaica): Implications for Reproductive Success

The Pyrenean rock ptarmigan (Lagopus muta pyrenaica) is the southernmost subspecies of the species in Europe and is considered threatened as a consequence of changes in landscape, human pressure, climate change, and low genetic diversity. Previous studies have shown a relationship between the date of snowmelt and reproductive success in the Pyrenean ptarmigan. It is well established that birds laying early in the breeding season have higher reproductive success, but the specific mechanism for this relationship is debated. We present an explicative model of the relationship between snowmelt date and breeding success mediated by food quality for grouse in alpine environments. From microhistological analyses of 121 faecal samples collected during three years in the Canigou Massif (Eastern Pyrenees), and the assessment of the chemical composition of the main dietary components, we estimated the potential quality of individual diets. Potential dietary quality was correlated with free-urate faecal N, a proxy of the digestible protein content ingested by ptarmigan, and both were correlated with phenological stage of consumed plants, which in turn depends on snowmelt date. Our findings suggest that the average snowmelt date is subject to a strong interannual variability influencing laying date. In years of early snowmelt, hens benefit from a longer period of high quality food resources potentially leading to a higher breeding success. On the contrary, in years of late snowmelt, hens begin their breeding period in poorer nutrient condition because the peaks of protein content of their main food items are delayed with respect to laying date, hence reducing breeding performance. We discuss the possible mismatch between breeding and snowmelt timing

Computational Homogenization of Architectured Materials

Architectured materials involve geometrically engineered distributions of microstructural phases at a scale comparable to the scale of the component, thus calling for new models in order to determine the effective properties of materials. The present chapter aims at providing such models, in the case of mechanical properties. As a matter of fact, one engineering challenge is to predict the effective properties of such materials; computational homogenization using finite element analysis is a powerful tool to do so. Homogenized behavior of architectured materials can thus be used in large structural computations, hence enabling the dissemination of architectured materials in the industry. Furthermore, computational homogenization is the basis for computational topology optimization which will give rise to the next generation of architectured materials. This chapter covers the computational homogenization of periodic architectured materials in elasticity and plasticity, as well as the homogenization and representativity of random architectured materials