Heterosexual interactions of pairs of laboratory-housed stumptail macaques (Macaca arctoides) under continuous observation with closed-circuit video recording

Female-male interaction of heterosexual pairs of stumptail macaques, housed together continuously, was studied 24 hr per day using closed-circuit video recording. Two pairs were studied for approximately 2 months each. Although no generalizations can be made from such a small sample, no aspect of behavioral interaction varied significantly with the stage of the menstrual cycle of the female partner. Copulation occurred regularly but only during the daylight hours. Both pairs showed several peak ejaculation days (5-21 ejaculations/day), which were distributed throughout the entire menstrual cycle. In general, the highest number of ejaculations was observed to occur when the animals were put together either for the first time or following a separation of a few days. In one pair the female became pregnant, and from the fifth week of pregnancy onward there was a gradual increase in male aggression, coinciding with a decrease in male sexual and grooming behavior. In a second study eight different pairs were observed during the first day together and male copulatory behavior was studied. Two patterns of copulatory behavior could be discerned: pairs displaying a high number of ejaculations (19-38) and pairs displaying a low number of ejaculations (4-8). With regard to the interejaculatory interval (IEI), the male stumptail appeared to be unique. In contrast to what has been reported for other mammals, i.e., a steady increase in IEI with subsequent ejaculations, the stumptail showed increasing IEIs only during the first three to four, as well as between the last, ejaculations; in between, the IEI remained relatively constant. The maximum number of consecutive ejaculations observed was 38, displayed during a 10-hr time period (mean (± SEM)IEI, 12.9 ± 3.5 min)

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior.

Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce a computationally efficient approach for multivariate genomic-relatedness-based restricted maximum likelihood (MGREML) to estimate the genetic correlation between a large number of phenotypes simultaneously. Using individual-level data (N = 20,190) from the UK Biobank, we provide estimates of the heritability of gray-matter volume in 74 regions of interest (ROIs) in the brain and we map genetic correlations between these ROIs and health-relevant behavioral outcomes, including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs. These empirical results illustrate how MGREML can be used to estimate internally consistent and high-dimensional genetic correlation matrices in large datasets

Dispelling urban myths about default uncertainty factors in chemical risk assessment - Sufficient protection against mixture effects?

© 2013 Martin et al.; licensee BioMed Central LtdThis article has been made available through the Brunel Open Access Publishing Fund.Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment. © 2013 Martin et al.; licensee BioMed Central Ltd.Oak Foundatio

Commissioning of inline ECE system within waveguide based ECRH transmission systems on ASDEX upgrade

A CW capable inline electron cyclotron emission (ECE) separation system for feedback control, featuring oversized corrugated waveguides, is commissioned on ASDEX upgrade (AUG). The system is based on a combination of a polarization independent, non-resonant, Mach-Zehnder diplexer equipped with dielectric plate beam splitters [2, 3] employed as corrugated oversized waveguide filter, and a resonant Fast Directional Switch, FADIS [4, 5, 6, 7] as ECE/ECCD separation system. This paper presents an overview of the system, the low power characterisation tests and first high power commissioning on AUG

Childhood meat eating and inflammatory markers: The Guangzhou Biobank Cohort Study

<p>Abstract</p> <p>Background</p> <p>We hypothesized that socio-economic development could, via nutritionally driven levels of pubertal sex-steroids, promote a pro-inflammatory state among men but not women in developing countries. We tested this hypothesis, using recalled childhood meat eating as a proxy for childhood nutrition, in southern China.</p> <p>Methods</p> <p>We used multivariable linear regression in the Guangzhou Biobank Cohort Study phase 3 (2006-8) to examine the adjusted associations of recalled childhood meat eating, <1/week (n = 5,023), about once per week (n = 3,592) and almost daily (n = 1,252), with white blood cell count and its differentials among older (≥50 years) men (n = 2,498) and women (n = 7,369).</p> <p>Results</p> <p>Adjusted for age, childhood socio-economic position, education and smoking, childhood meat eating had sex-specific associations with white blood cell count and lymphocyte count, but not granulocyte count. Men with childhood meat eating almost daily compared to <1/week had higher white blood cell count (0.33 10⁹/L, 95% confidence interval (CI) 0.10 to 0.56) and higher lymphocyte count (0.16 10⁹/L, 95% CI 0.07 to 0.25). Adjustment for obesity slightly attenuated these associations.</p> <p>Conclusion</p> <p>If confirmed, this hypothesis implies that economic development and the associated improvements in nutrition at puberty may be less beneficial among men than women; consistent with the widening sex differentials in life expectancy with economic development.</p

Automatic Mapping of Discontinuity Persistence on Rock Masses Using 3D Point Clouds

Finding new ways to quantify discontinuity persistence values in rock masses in an automatic or semi-automatic manner is a considerable challenge, as an alternative to the use of traditional methods based on measuring patches or traces with tapes. Remote sensing techniques potentially provide new ways of analysing visible data from the rock mass. This work presents a methodology for the automatic mapping of discontinuity persistence on rock masses, using 3D point clouds. The method proposed herein starts by clustering points that belong to patches of a given discontinuity. Coplanar clusters are then merged into a single group of points. Persistence is measured in the directions of the dip and strike for each coplanar set of points, resulting in the extraction of the length of the maximum chord and the area of the convex hull. The proposed approach is implemented in a graphic interface with open source software. Three case studies are utilized to illustrate the methodology: (1) small-scale laboratory setup consisting of a regular distribution of cubes with similar dimensions, (2) more complex geometry consisting of a real rock mass surface in an excavated cavern and (3) slope with persistent sub-vertical discontinuities. Results presented good agreement with field measurements, validating the methodology. Complexities and difficulties related to the method (e.g. natural discontinuity waviness) are reported and discussed. An assessment on the applicability of the method to the 3D point cloud is also presented. Utilization of remote sensing data for a more objective characterization of the persistence of planar discontinuities affecting rock masses is highlighted herein

Towards a general framework for including noise impacts in LCA

Industrial Ecolog