The effect of mixing entire male pigs prior to transport to slaughter on behaviour, welfare and carcass lesions

peer-reviewedData set for article is also provided.Research is needed to validate lesions recorded at meat inspection as indicators of pig welfare on farm. The aims were to determine the influence of mixing pigs on carcass lesions and to establish whether such lesions correlate with pig behaviour and lesions scored on farm. Aggressive and mounting behaviour of pigs in three single sex pens was recorded on Day −5, −2, and −1 relative to slaughter (Day 0). On Day 0 pigs were randomly allocated to 3 treatments (n = 20/group) over 5 replicates: males mixed with females (MF), males mixed with males (MM), and males unmixed (MUM). Aggressive and mounting behaviours were recorded on Day 0 at holding on farm and lairage. Skin/tail lesions were scored according to severity at the farm (Day −1), lairage, and on the carcass (Day 0). Effect of treatment and time on behaviour and lesions were analysed by mixed models. Spearman rank correlations between behaviour and lesion scores and between scores recorded at different stages were determined. In general, MM performed more aggressive behaviour (50.4 ± 10.72) than MUM (20.3 ± 9.55, P < 0.05) and more mounting (30.9 ± 9.99) than MF (11.4 ± 3.76) and MUM (9.8 ± 3.74, P < 0.05). Skin lesion scores increased between farm (Day −1) and lairage (P < 0.001), but this tended to be significant only for MF and MM (P = 0.08). There was no effect of treatment on carcass lesions and no associations were found with fighting/mounting. Mixing entire males prior to slaughter stimulated mounting and aggressive behaviour but did not influence carcass lesion scores. Carcass skin/tail lesions scores were correlated with scores recorded on farm (rskin = 0.21 and rtail = 0.18, P < 0.01) suggesting that information recorded at meat inspection could be used as indicators of pig welfare on farm.This study was part of the PIGWELFIND project funded by the Department of Agriculture, Food and the Marine (DAFM), Ireland

Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies.

Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown subtle environmental perturbations. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the effect of prominent genetic regulators. As a result, this new model can more accurately distinguish true genetic association signals from confounding variation. We applied our model and compared it to existing methods on different datasets and biological systems. PANAMA consistently performs better than alternative methods, and finds in particular substantially more trans regulators. Importantly, our approach not only identifies a greater number of associations, but also yields hits that are biologically more plausible and can be better reproduced between independent studies. A software implementation of PANAMA is freely available online at http://ml.sheffield.ac.uk/qtl/

Selective Decrease of Components of the Creatine Kinase System and ATP Synthase Complex in Chronic Chagas Disease Cardiomyopathy

Chronic Chagas disease cardiomyopathy (CCC) affects millions in endemic areas and is presenting in growing numbers in the USA and European countries due to migration currents. Clinical progression, length of survival and overall prognosis are significantly worse in CCC patients when compared to patients with dilated cardiomyopathy of non-inflammatory etiology. Impairment of energy metabolism seems to play a role in heart failure due to cardiomyopathies. Herein, we have analyzed energy metabolism enzymes in myocardium samples of CCC patients comparing to other non-inflammatory cardiomyopathies. We found that myocardial tissue from CCC patients displays a significant reduction of both myocardial protein levels of ATP synthase alpha and creatine kinase enzyme activity, in comparison to control heart samples, as well as idiopathic dilated cardiomyopathy and ischemic cardiomyopathy. Our results suggest that CCC myocardium displays a selective energetic deficit, which may play a role in the reduced heart function observed in such patients