EFFECT OF MC4R POLYMORPHISM ON PHYSIOLOGICAL STRESS RESPONSE IN PIGS

Melanocortin-4 receptor (MC4R) is a G-protein coupled receptor predominantly expressed in hypothalamic regions which are known for their roles in feeding behavior, energy homeostasis and HPA axis regulation. In this study, we analyzed the effect of a missense mutation (Asp298Asn) in the porcine MC4R gene on physiological stress response and carcass composition in pigs of two crosses: A (♀Duroc x ♂Swedish Landrace) x ♂Pietrain (n=25) and B (♀Swedish Landrace x ♂Large White) x ♂Pietrain (n=21). All pigs included in this study were heterozygous (Nn) for the stress syndrome gen. Blood samples were collected before loading and at exsanguinations to measure cortisol, lactate, glucose, serum enzymes activity and some haematological parameters. Because only one pig with AA genotype was observed, there was no indicated effect of this genotype on investigated parameters. The heterozygous (AG) pigs showed a lower increase (P<0.05) in CK and AST activity after exsanguinations as well as trend towards lower increase (P<0.10) in cortisol and lactate levels and higher increase (P<0.10) in RBC and haemoglobin content. Higher increase (P<0.05) in LDH activity was observed in GG homozygous pigs from group B, but not in pigs from group A. In addition, the heterozygous (AG) pigs had a higher backfat thickness and lower estimated lean (P<0.05) than homozygous (GG) pigs. These results may support a possible role of the MC4R Asp298Asn polymorphism in the genetic basis of stress response and economically important traits in pigs

Rapid Independent Trait Evolution despite a Strong Pleiotropic Genetic Correlation

This is the publisher's version. It can also be found here:http://dx.doi.org/10.1086/661907Genetic correlations are the most commonly studied of all potential constraints on adaptive evolution. We present a comprehensive test of constraints caused by genetic correlation, comparing empirical results to predictions from theory. The additive genetic correlation between the filament and the corolla tube in wild radish flowers is very high in magnitude, is estimated with good precision, and is caused by pleiotropy. Thus, evolutionary changes in the relative lengths of these two traits should be constrained. Still, artificial selection produced rapid evolution of these traits in opposite directions, so that in one replicate relative to controls, the difference between them increased by six standard deviations in only nine generations. This would result in a 54% increase in relative fitness on the basis of a previous estimate of natural selection in this population, and it would produce the phenotypes found in the most extreme species in the family Brassicaceae in less than 100 generations. These responses were within theoretical expectations and were much slower than if the genetic correlation was zero; thus, there was evidence for constraint. These results, coupled with comparable results from other species, show that evolution can be rapid despite the constraints caused by genetic correlations

Commentary: Differential associations between obesity and behavioral measures of impulsivity.

Growing evidence supports the concept of a “cognitive profile” (Jansen et al., 2015) of obesity, a set of interrelated cognitive patterns, largely influenced by executive functioning, that may underlie obesogenic behaviors, especially in contemporary environments, which are saturated with food cues. These cognitive deficits include attentional biases toward food (Castellanos et al., 2009; Yokum et al., 2011) and discounting of future rewards (Weller et al., 2008). A greater understanding of these cognitive patterns may aid the development of more effective behavioral interventions for obesity, whether through training to minimize cognitive biases, designing interventions to sidestep the effect that these cognitive patterns may have on behavior, or even harnessing biases to drive more adaptive behaviors

Fast Methods for Jackknifing Inequality Indices

The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper outlines a procedure to obtain jackknife estimates for several inequality indices with only a few passes through the data. The number of passes is independent of the number of observations. Hence, the method provides an efficient way to obtain standard errors of the estimators even if sample size is large. We apply our method using micro data on individual incomes for Germany and the US

Ubiquitous Aberration in Cholesterol Metabolism Across Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is characterized by metabolic deregulations that often manifest as deviations in metabolite levels and aberrations in their corresponding metabolic genes across the clinical specimens and preclinical PC models. Cholesterol is one of the critical metabolites supporting PC, synthesized or acquired by PC cells. Nevertheless, the significance of the de novo cholesterol synthesis pathway has been controversial in PC, indicating the need to reassess this pathway in PC. We utilized preclinical models and clinical specimens of PC patients and cell lines and utilized mass spectrometry-based sterol analysis. Further, we also performed in silico analysis to corroborate the significance of de novo cholesterol synthesis pathway in PC. Our results demonstrated alteration in free sterol levels, including free cholesterol, across in vitro, in vivo, and clinical specimens of PC. Especially, our sterol analyses established consistent alterations in free cholesterol across the different PC models. Overall, this study demonstrates the significance and consistency in deviation of cholesterol synthesis pathway in PC while showing the aberrations in sterol metabolite intermediates and the related genes using preclinical models, in silico platforms, and the clinical specimens

Evaluation of the ACCESS - Chemistry-climate model for the Southern Hemisphere

Published: 29 February 2016Chemistry–climate models are important tools for addressing interactions of composition and climate in the Earth system. In particular, they are used to assess the combined roles of greenhouse gases and ozone in Southern Hemisphere climate and weather. Here we present an evaluation of the Australian Community Climate and Earth System Simulator – chemistry–climate model (ACCESS-CCM), focusing on the Southern Hemisphere and the Australian region. This model is used for the Australian contribution to the international Chemistry–Climate Model Initiative, which is soliciting hindcast, future projection and sensitivity simulations. The model simulates global total column ozone (TCO) distributions accurately, with a slight delay in the onset and recovery of springtime Antarctic ozone depletion, and consistently higher ozone values. However, October-averaged Antarctic TCO from 1960 to 2010 shows a similar amount of depletion compared to observations. Comparison with model precursors shows large improvements in the representation of the Southern Hemisphere stratosphere, especially in TCO concentrations. A significant innovation is seen in the evaluation of simulated vertical profiles of ozone and temperature with ozonesonde data from Australia, New Zealand and Antarctica from 38 to 90° S. Excess ozone concentrations (greater than 26 % at Davis and the South Pole during winter) and stratospheric cold biases (up to 10 K at the South Pole during summer and autumn) outside the period of perturbed springtime ozone depletion are seen during all seasons compared to ozonesondes. A disparity in the vertical location of ozone depletion is seen: centred around 100 hPa in ozonesonde data compared to above 50hPa in the model. Analysis of vertical chlorine monoxide profiles indicates that colder Antarctic stratospheric temperatures (possibly due to reduced mid-latitude heat flux) are artificially enhancing polar stratospheric cloud formation at high altitudes. The model's inability to explicitly simulate a supercooled ternary solution may also explain the lack of depletion at lower altitudes. Analysis of the simulated Southern Annular Mode (SAM) index compares well with ERA-Interim data, an important metric for correct representation of Australian climate. Accompanying these modulations of the SAM, 50 hPa zonal wind differences between 2001–2010 and 1979–1998 show increasing zonal wind strength southward of 60° S during December for both the model simulations and ERA-Interim data. These model diagnostics show that the model reasonably captures the stratospheric ozone-driven chemistry–climate interactions important for Australian climate and weather while highlighting areas for future model development.Kane A. Stone, Olaf Morgenstern, David J. Karoly, Andrew R. Klekociuk, W. John French, N. Luke Abraham, and Robyn Schofiel

Rossby wave dynamics of the North Pacific extra-tropical response to El Niño: importance of the basic state in coupled GCMs

The extra-tropical response to El Nino in a "low" horizontal resolution coupled climate model, typical of the Intergovernmental Panel on Climate Change fourth assessment report simulations, is shown to have serious systematic errors. A high resolution configuration of the same model has a much improved response that is similar to observations. The errors in the low resolution model are traced to an incorrect representation of the atmospheric teleconnection mechanism that controls the extra-tropical sea surface temperatures (SSTs) during El Nino. This is due to an unrealistic atmospheric mean state, which changes the propagation characteristics of Rossby waves. These erroneous upper tropospheric circulation anomalies then induce erroneous surface circulation features over the North Pacific. The associated surface wind speed and direction errors create erroneous surface flux and upwelling anomalies which finally lead to the incorrect extra-tropical SST response to El Nino in the low resolution model. This highlights the sensitivity of the climate response to a single link in a chain of complex climatic processes. The correct representation of these processes in the high resolution model indicates the importance of horizontal resolution in resolving such processes

Multiscale computational analysis of Xenopus laevis morphogenesis reveals key insights of systems-level behavior

<p>Abstract</p> <p>Background</p> <p>Tissue morphogenesis is a complex process whereby tissue structures self-assemble by the aggregate behaviors of independently acting cells responding to both intracellular and extracellular cues in their environment. During embryonic development, morphogenesis is particularly important for organizing cells into tissues, and although key regulatory events of this process are well studied in isolation, a number of important systems-level questions remain unanswered. This is due, in part, to a lack of integrative tools that enable the coupling of biological phenomena across spatial and temporal scales. Here, we present a new computational framework that integrates intracellular signaling information with multi-cell behaviors in the context of a spatially heterogeneous tissue environment.</p> <p>Results</p> <p>We have developed a computational simulation of mesendoderm migration in the <it>Xenopus laevis </it>explant model, which is a well studied biological model of tissue morphogenesis that recapitulates many features of this process during development in humans. The simulation couples, via a JAVA interface, an ordinary differential equation-based mass action kinetics model to compute intracellular Wnt/β-catenin signaling with an agent-based model of mesendoderm migration across a fibronectin extracellular matrix substrate. The emergent cell behaviors in the simulation suggest the following properties of the system: maintaining the integrity of cell-to-cell contact signals is necessary for preventing fractionation of cells as they move, contact with the Fn substrate and the existence of a Fn gradient provides an extracellular feedback loop that governs migration speed, the incorporation of polarity signals is required for cells to migrate in the same direction, and a delicate balance of integrin and cadherin interactions is needed to reproduce experimentally observed migratory behaviors.</p> <p>Conclusion</p> <p>Our computational framework couples two different spatial scales in biology: intracellular with multicellular. In our simulation, events at one scale have quantitative and dynamic impact on events at the other scale. This integration enables the testing and identification of key systems-level hypotheses regarding how signaling proteins affect overall tissue-level behavior during morphogenesis in an experimentally verifiable system. Applications of this approach extend to the study of tissue patterning processes that occur during adulthood and disease, such as tumorgenesis and atherogenesis.</p