Improving stress coping ability: comparison between the CYP17 genotype Of Ovis Aries and Capra Hircus

The ability of animals to adapt to stress is not only an animal health and welfare concern, but also influences reproduction potential and robustness. An important pathway involved in the stress response is the hypothalamic-pituitary-adrenal axis (HPAA) that results in the release of cortisol from the adrenal gland. In this study the cortisol responses of South African Merinos were measured to assess HPAA responsiveness to stress and relate it to behavioural stress responses to flock-isolation. The experiment was structured according to a 2×2 statistical design, with CYP17 genotype (WT1/WT1 vs. WT1/WT2) and selection line (H-line vs. L-line) as factors. Selection line criteria was based on divergent selection for (H-line) or against (L-line) maternal multiple rearing ability, where the H-line generally outperformed the L-line in terms of reproduction, animal welfare and resistance to certain pathogens. The CYP17 genotype is involved in the biosynthesis pathway of cortisol. In the present study the CYP17 genotype showed a significant influence on behavioural stress responses, where three parameters of the flock-isolation test were affected (P<0.05), namely the number of bleats uttered, the urinating frequency and the average distance from a human operator. It is suggested that the CYP17 genotype affects behavioural responses via its effects on cortisol production, and that the SNPs located within the CYP17 genotype may have application in marker-assisted selection of sheep

On-Line Portfolio Selection with Moving Average Reversion

On-line portfolio selection has attracted increasing interests in machine learning and AI communities recently. Empirical evidences show that stock's high and low prices are temporary and stock price relatives are likely to follow the mean reversion phenomenon. While the existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied in some real datasets, leading to poor performance when the assumption does not hold. To overcome the limitation, this article proposes a multiple-period mean reversion, or so-called Moving Average Reversion (MAR), and a new on-line portfolio selection strategy named "On-Line Moving Average Reversion" (OLMAR), which exploits MAR by applying powerful online learning techniques. From our empirical results, we found that OLMAR can overcome the drawback of existing mean reversion algorithms and achieve significantly better results, especially on the datasets where the existing mean reversion algorithms failed. In addition to superior trading performance, OLMAR also runs extremely fast, further supporting its practical applicability to a wide range of applications.Comment: ICML201

Differential Effects of Neonatal Testosterone Treatment on Aggression in Two Selection Lines of Mice

Selection lines of mice, artificially selected for aggression based upon the attack latency score (ALS), were used. In order to determine the relative contribution of neonatal testosterone (T) in the development of aggression, we vary the plasma-T level in males of both selection lines on the day of birth. At 14 weeks the ALS was measured. Neonatal T treatment results in a reduction of aggression in the long attack latency (LAL) line, whereas aggressive behaviour of the short attack latency (SAL) line is not affected. Both selection lines show reduction in testicular weight, although the total amount of T-producing Leydig cells was not affected. Neonatal T may cause a permanent reduction in aggressive behaviour in the LAL line only, probably due to differential appearance of critical periods. It is suggested that the difference in aggressive behaviour between SAL and LAL selection lines is due to a prenatally determined difference in neonatal T sensitivity of the brain.

Comparison of Selection Methods in On-line Distributed Evolutionary Robotics

In this paper, we study the impact of selection methods in the context of on-line on-board distributed evolutionary algorithms. We propose a variant of the mEDEA algorithm in which we add a selection operator, and we apply it in a taskdriven scenario. We evaluate four selection methods that induce different intensity of selection pressure in a multi-robot navigation with obstacle avoidance task and a collective foraging task. Experiments show that a small intensity of selection pressure is sufficient to rapidly obtain good performances on the tasks at hand. We introduce different measures to compare the selection methods, and show that the higher the selection pressure, the better the performances obtained, especially for the more challenging food foraging task

Response to somatic cell count-based selection for mastitis resistance in a divergent selection experiment in sheep

A divergent selection experiment in sheep was implemented to study the consequences of log-transformed somatic cell score (SCS)-based selection on resistance to natural intramammary infections. Using dams and progeny-tested rams selected for extreme breeding values for SCS, we created 2 groups of ewes with a strong divergence in SCS of approximately 3 genetic standard deviations. A survey of 84 first-lactation ewes of both the High and Low SCS lines indicated favorable responses to SCS-based selection on resistance to both clinical and subclinical mastitis. All clinical cases (n = 5) occurred in the High SCS line. Additionally, the frequency of chronic clinical mastitis,as detected by the presence of parenchymal abscesses, was much greater in the High SCS line (n = 21) than in the Low SCS line (n = 1). According to monthly milk bacterio-logical examinations of udder halves, the prevalence of infection was significantly greater (odds ratio = 3.1) in the High SCS line than in the Low SCS line, with predicted probabilities of 37 and 16%, respectively. The most frequently isolated bacteria responsible for mastitis were staphylococci: Staphylococcus auricularis(42.6% of positive samples), Staphylococcus simulans, Staphylococcus haemoliticus, Staphylococcus xylosus, Staphylococcus chromogenes, Staphylococcus lentus, Staphylococcus warneri, and Staphylococcus aureus. The incidence of positive bacteriology was greater in the High SCS line (39%) than in the Low SCS line (12%)at lambing, indicating that High SCS line ewes were especially susceptible to postpartum subclinical mastitis. Negativation of bacteriological results from one sampling time point to the next was markedly different between lines after weaning (e.g., 41 and 84% in the High and Low SCS lines, respectively). This result was consistent with differences in the duration of infection, which was much greater in the High SCS line compared with the Low SCS line. Finally, ewes from the High SCS line consistently had greater SCS in positive milk samples than did ewes from the Low SCS line (+2.04 SCS, on average), with an especially large difference between lines during the suckling period (+3.42 SCS). Altogether, the preliminary results suggest that the better resistance of Low SCS line ewes, compared with High SCS line ewes, was principally characterized by a better ability to limit infections during the peripartum period, to eliminate infections during lactation, and quantitatively to limit the inflammation process and its clinical consequences

Contact Line Instability and Pattern Selection in Thermally Driven Liquid Films

Liquids spreading over a solid substrate under the action of various forces are known to exhibit a long wavelength contact line instability. We use an example of thermally driven spreading on a horizontal surface to study how the stability of the flow can be altered, or patterns selected, using feedback control. We show that thermal perturbations of certain spatial structure imposed behind the contact line and proportional to the deviation of the contact line from its mean position can completely suppress the instability. Due to the presence of mean flow and a spatially nonuniform nature of spreading liquid films the dynamics of disturbances is governed by a nonnormal evolution operator, opening up a possibility of transient amplification and nonlinear instabilities. We show that in the case of thermal driving the nonnormality can be significant, especially for small wavenumber disturbances, and trace the origin of transient amplification to a close alignment of a large group of eigenfunctions of the evolution operator. However, for values of noise likely to occur in experiments we find that the transient amplification is not sufficiently strong to either change the predictions of the linear stability analysis or invalidate the proposed control approach.Comment: 13 pages, 14 figure

Multiple-line inference of selection on quantitative traits

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population-genetic test for selection acting on a quantitative trait which is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inference. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test allows to distinguish different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signatures of lineage-specific selection not seen in a two-line test.Comment: 21 pages, 11 figures; to appear in Genetic