Environmental stress alters genetic regulation of novelty seeking in vervet monkeys.

Considerable attention has been paid to identifying genetic influences and gene-environment interactions that increase vulnerability to environmental stressors, with promising but inconsistent results. A nonhuman primate model is presented here that allows assessment of genetic influences in response to a stressful life event for a behavioural trait with relevance for psychopathology. Genetic and environmental influences on free-choice novelty seeking behaviour were assessed in a pedigreed colony of vervet monkeys before and after relocation from a low stress to a higher stress environment. Heritability of novelty seeking scores, and genetic correlations within and between environments were conducted using variance components analysis. The results showed that novelty seeking was markedly inhibited in the higher stress environment, with effects persisting across a 2-year period for adults but not for juveniles. There were significant genetic contributions to novelty seeking scores in each year (h(2) = 0.35-0.43), with high genetic correlations within each environment (rhoG > 0.80) and a lower genetic correlation (rhoG = 0.35, non-significant) between environments. There were also significant genetic contributions to individual change scores from before to after the move (h(2) = 0.48). These results indicate that genetic regulation of novelty seeking was modified by the level of environmental stress, and they support a role for gene-environment interactions in a behavioural trait with relevance for mental health

Intracellular pathways involved in bone regeneration triggered by recombinant silk-silica chimeras

Biomineralization at the organic-inorganic interface is critical to many biology material functions in vitro and in vivo. Recombinant silk-silica fusion peptides are organic-inorganic hybrid material systems that can be effectively used to study and control biologically-mediated mineralization due to the genetic basis of sequence control. However, to date, the mechanisms by which these functionalized silk-silica proteins trigger the differentiation of human mesenchymal stem cells (hMSCs) to osteoblasts remain unknown. To address this challenge, we analyzed silk-silica surfaces for silica-hMSC receptor binding and activation, and the intracellular pathways involved in the induction of osteogenesis on these bioengineered biomaterials. The induction of gene expression of αVβ3 integrin, all three Mitogen-activated Protein Kinsases (MAPKs) as well as c-Jun, Runt-related Transcription Factor 2 (Runx2) and osteoblast marker genes was demonstrated upon growth of the hMSCs on the silk-silica materials. This induction of key markers of osteogenesis correlated with the content of silica on the materials. Moreover, computational simulations were performed for silk/silica-integrin binding which showed activation of αVβ3 integrin in contact with silica. This integrated computational and experimental approach provides insight into interactions that regulate osteogenesis towards more efficient biomaterial designs

A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

Axion-Higgs Unification

In theories with no fundamental scalars, one gauge group can become strong at a large scale Lambda and spontaneously break a global symmetry, producing the Higgs and the axion as composite pseudo-Nambu-Goldstone bosons. We show how KSVZ and DFSZ axion models can be naturally realised. The assumption Lambda around 10^{11} GeV is phenomenologically favoured because: a) The axion solves the QCD theta problem and provides the observed DM abundance; b) The observed Higgs mass is generated via RGE effects from a small Higgs quartic coupling at the compositeness scale, provided that the Higgs mass term is fine-tuned to be of electroweak size; c) Lepton, quark as well as neutrino masses can be obtained from four-fermion operators at the compositeness scale. d) The extra fermions can unify the gauge couplings.Comment: 19 pages. Refs. added and eq. 3.6 fixe

Proposed New Antiproton Experiments at Fermilab

Fermilab operates the world's most intense source of antiprotons. Recently various experiments have been proposed that can use those antiprotons either parasitically during Tevatron Collider running or after the Tevatron Collider finishes in about 2010. We discuss the physics goals and prospects of the proposed experiments.Comment: 6 pages, 2 figures, to appear in Proceedings of IXth International Conference on Low Energy Antiproton Physics (LEAP'08), Vienna, Austria, September 16 to 19, 200

Intraspecfic variation in cold-temperature metabolic phenotypes of Arabidopsis lyrata ssp petraea

Atmospheric temperature is a key factor in determining the distribution of a plant species. Alongside this, plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. We investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes associated with exposure to cold temperatures. Seeds of A. petraea were obtained from populations along a latitudinal gradient, namely Wales, Sweden and Iceland and grown in a controlled cabinet environment. Mannose, glucose, fructose, sucrose and raffinose concentrations were different between cold treatments and populations, especially in the Welsh population, but polyhydric alcohol concentrations were not. The free amino acid compositions were population specific, with fold differences in most amino acids, especially in the Icelandic populations, with gross changes in amino acids, particularly those associated with glutamine metabolism. Metabolic fingerprints and profiles were obtained. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic characteristic phenotypes for each population and temperature. It is suggested that amino acids and carbohydrates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations at different atmospheric temperatures. These findings show that there is significant natural variation in cold metabolism among populations of A. l. petraea which may signify plant adaptation to local climates

Collective Quartics from Simple Groups

This article classifies Little Higgs models that have collective quartic couplings. There are two classes of collective quartics: Special Cosets and Special Quartics. After taking into account dangerous singlets, the smallest Special Coset models are SU(5)/SO(5) and SU(6)/Sp(6). The smallest Special Quartic model is SU(5)/SU(3) x SU(2) x U(1) and has not previously been considered as a candidate Little Higgs model.Comment: 22 pages, 2 figure

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Model-Independent Bounds on a Light Higgs

We present up-to-date constraints on a generic Higgs parameter space. An accurate assessment of these exclusions must take into account statistical, and potentially signal, fluctuations in the data currently taken at the LHC. For this, we have constructed a straightforward statistical method for making full use of the data that is publicly available. We show that, using the expected and observed exclusions which are quoted for each search channel, we can fully reconstruct likelihood profiles under very reasonable and simple assumptions. Even working with this somewhat limited information, we show that our method is sufficiently accurate to warrant its study and advocate its use over more naive prescriptions. Using this method, we can begin to narrow in on the remaining viable parameter space for a Higgs-like scalar state, and to ascertain the nature of any hints of new physics---Higgs or otherwise---appearing in the data.Comment: 32 pages, 10 figures; v3: correction made to basis of four-derivative operators in the effective Lagrangian, references adde

Supersymmetric AdS_4 black holes and attractors

Using the general recipe given in arXiv:0804.0009, where all timelike supersymmetric solutions of N=2, D=4 gauged supergravity coupled to abelian vector multiplets were classified, we construct the first examples of genuine supersymmetric black holes in AdS_4 with nonconstant scalar fields. This is done for various choices of the prepotential, amongst others for the STU model. These solutions permit to study the BPS attractor flow in AdS. We also determine the most general supersymmetric static near-horizon geometry and obtain the attractor equations in gauged supergravity. As a general feature we find the presence of flat directions in the black hole potential, i.e., generically the values of the moduli on the horizon are not completely specified by the charges. For one of the considered prepotentials, the resulting moduli space is determined explicitely. Still, in all cases, we find that the black hole entropy depends only on the charges, in agreement with the attractor mechanism.Comment: 25 pages, uses JHEP3.cl