Recognition and Alleviation of Pain in Animals

The pain and distress which animals experience as a consequence of their use by man figures prominently in discussions of animal welfare. Some improvements have been made in animal housing and husbandry practices and it is likely that further progress will be made in this field. In comparison, relatively little attention has been given to the problem of minimizing the pain and distress caused to animals by the various procedures to which they are subjected. The most publicized of these are the wide range of experimental techniques which are undertaken using laboratory animals, but also includes procedures such as castration of farm animals and neutering operations carried out on pet animals. The prevention or alleviation of the pain associated with such procedures is a complex problem with no single, simple solution. Consideration must be given to the use of analgesic drugs, the provision of high standards of general care, and the use of special nursing techniques. When dealing with post-operative care, the pre-operative management ofthe animal, the operative procedures and the anesthetic regime must all be evaluated and, when necessary, modified to minimize pain or discomfort

I Know My Neighbour: Individual Recognition in Octopus vulgaris

Background: Little is known about individual recognition (IR) in octopuses, although they have been abundantly studied for their sophisticated behaviour and learning capacities. Indeed, the ability of octopuses to recognise conspecifics is suggested by a number of clues emerging from both laboratory studies (where they appear to form and maintain dominance hierarchies) and field observations (octopuses of neighbouring dens display little agonism between each other). To fill this gap in knowledge, we investigated the behaviour of 24 size-matched pairs of Octopus vulgaris in laboratory conditions. Methodology/Principal Findings: The experimental design was composed of 3 phases: Phase 1 (acclimatization): 12 ‘‘sightallowed’’ (and 12 ‘‘isolated’’) pairs were maintained for 3 days in contiguous tanks separated by a transparent (and opaque) partition to allow (and block) the vision of the conspecific; Phase 2 (cohabitation): members of each pair (both sight-allowed and isolated) were transferred into an experimental tank and were allowed to interact for 15 min every day for 3 consecutive days; Phase 3 (test): each pair (both sight-allowed and isolated) was subject to a switch of an octopus to form pairs composed of either familiar (‘‘sham switches’’) or unfamiliar conspecifics (‘‘real switches’’). Longer latencies (i.e. the time elapsed from the first interaction) and fewer physical contacts in the familiar pairs as opposed to the unfamiliar pairs were used as proxies for recognition. Conclusions: Octopuses appear able to recognise conspecifics and to remember the individual previously met for at leas

Contribution of genetic effects to genetic variance components with epistasis and linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Cockerham genetic models are commonly used in quantitative trait loci (QTL) analysis with a special feature of partitioning genotypic variances into various genetic variance components, while the F_∞genetic models are widely used in genetic association studies. Over years, there have been some confusion about the relationship between these two type of models. A link between the additive, dominance and epistatic effects in an F_∞model and the additive, dominance and epistatic variance components in a Cockerham model has not been well established, especially when there are multiple QTL in presence of epistasis and linkage disequilibrium (LD).</p> <p>Results</p> <p>In this paper, we further explore the differences and links between the F_∞and Cockerham models. First, we show that the Cockerham type models are allelic based models with a special modification to correct a confounding problem. Several important moment functions, which are useful for partition of variance components in Cockerham models, are also derived. Next, we discuss properties of the F_∞models in partition of genotypic variances. Its difference from that of the Cockerham models is addressed. Finally, for a two-locus biallelic QTL model with epistasis and LD between the loci, we present detailed formulas for calculation of the genetic variance components in terms of the additive, dominant and epistatic effects in an F_∞model. A new way of linking the Cockerham and F_∞model parameters through their coding variables of genotypes is also proposed, which is especially useful when reduced F_∞models are applied.</p> <p>Conclusion</p> <p>The Cockerham type models are allele-based models with a focus on partition of genotypic variances into various genetic variance components, which are contributed by allelic effects and their interactions. By contrast, the F_∞regression models are genotype-based models focusing on modeling and testing of within-locus genotypic effects and locus-by-locus genotypic interactions. When there is no need to distinguish the paternal and maternal allelic effects, these two types of models are transferable. Transformation between an F_∞model's parameters and its corresponding Cockerham model's parameters can be established through a relationship between their coding variables of genotypes. Genetic variance components in terms of the additive, dominance and epistatic genetic effects in an F_∞model can then be calculated by translating formulas derived for the Cockerham models.</p

Matched Ascertainment of Informative Families for Complex Genetic Modelling

Family data are used extensively in quantitative genetic studies to disentangle the genetic and environmental contributions to various diseases. Many family studies based their analysis on population-based registers containing a large number of individuals composed of small family units. For binary trait analyses, exact marginal likelihood is a common approach, but, due to the computational demand of the enormous data sets, it allows only a limited number of effects in the model. This makes it particularly difficult to perform joint estimation of variance components for a binary trait and the potential confounders. We have developed a data-reduction method of ascertaining informative families from population-based family registers. We propose a scheme where the ascertained families match the full cohort with respect to some relevant statistics, such as the risk to relatives of an affected individual. The ascertainment-adjusted analysis, which we implement using a pseudo-likelihood approach, is shown to be efficient relative to the analysis of the whole cohort and robust to mis-specification of the random effect distribution

Modelling fast forms of visual neural plasticity using a modified second-order motion energy model

The Adelson-Bergen motion energy sensor is well established as the leading model of low-level visual motion sensing in human vision. However, the standard model cannot predict adaptation effects in motion perception. A previous paper Pavan et al.(Journal of Vision 10:1-17, 2013) presented an extension to the model which uses a first-order RC gain-control circuit (leaky integrator) to implement adaptation effects which can span many seconds, and showed that the extended model's output is consistent with psychophysical data on the classic motion after-effect. Recent psychophysical research has reported adaptation over much shorter time periods, spanning just a few hundred milliseconds. The present paper further extends the sensor model to implement rapid adaptation, by adding a second-order RC circuit which causes the sensor to require a finite amount of time to react to a sudden change in stimulation. The output of the new sensor accounts accurately for psychophysical data on rapid forms of facilitation (rapid visual motion priming, rVMP) and suppression (rapid motion after-effect, rMAE). Changes in natural scene content occur over multiple time scales, and multi-stage leaky integrators of the kind proposed here offer a computational scheme for modelling adaptation over multiple time scales. © 2014 Springer Science+Business Media New York

The association of APOE genotype and cognitive decline in interaction with risk factors in a 65–69 year old community sample

<p>Abstract</p> <p>Background</p> <p>While the evidence of an association between the apolipoprotein E (<it>APOE</it>) <it>*E4 </it>allele and Alzheimer's disease is very strong, the effect of the <it>*E4 </it>allele on cognitive decline in the general population is more equivocal. A cross-sectional study on the lifespan effects of the <it>*E4 </it>allele <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> failed to find any effect of the <it>*E4 </it>allele on cognitive performance at ages 20–24, 40–44 or 60–64 years.</p> <p>Methods</p> <p>In this four year follow-up study, we reexamine the effect of <it>*E4 </it>in the sample of 2,021 individuals, now aged 65–69 years.</p> <p>Results</p> <p>Performance on the Mini-Mental State Examination (MMSE) was significantly poorer for <it>*E4 </it>homozygotes than heterozygotes or non-carriers. The effects of the <it>*E4 </it>genotype on cognitive decline over four years were found on the MMSE and Symbol-Digit Modalities test but only when controlling for risk factors such as head injury and education. Analyses were repeated with the exclusion of participants diagnosed with a mild cognitive disorder, with little change.</p> <p>Conclusion</p> <p>It is possible that <it>*E4 </it>carriers become vulnerable to greater cognitive decline in the presence of other risk factors at 65–69 years of age.</p