The Minimal Autoinhibited Unit of the Guanine Nucleotide Exchange Factor Intersectin

Intersectin-1L is a member of the Dbl homology (DH) domain guanine nucleotide exchange factors (GEF) which control Rho-family GTPase signaling. Intersectin-1L is a GEF that is specific for Cdc42. It plays an important role in endocytosis, and is regulated by several partners including the actin regulator N-WASP. Intact intersectin-1L shows low Cdc42 exchange activity, although the isolated catalytic DH domain shows high activity. This finding suggests that the molecule is autoinhibited. To investigate the mechanism of autoinhibition we have constructed a series of domain deletions. We find that the five SH3 domains of intersectin are important for autoinhibition, with the fifth domain (SH3(E)) being sufficient for the bulk of the autoinhibitory effect. This SH3 domain appears to primarily interact with the DH domain. We have determined the crystal structure of the SH3(E)-DH domain construct, which shows a domain swapped arrangement in which the SH3 from one monomer interacts with the DH domain of the other monomer. Analytical ultracentrifugation and gel filtration, however, show that under biochemical concentrations, the construct is fully monomeric. Thus we propose that the actual autoinhibited structure contains the related intramolecular SH3(E)-DH interaction. We propose a model in which this intramolecular interaction may block or distort the GTPase binding region of the DH domain

Dose-response relationship between arsenic exposure and the serum enzymes for liver function tests in the individuals exposed to arsenic: a cross sectional study in Bangladesh

<p>Abstract</p> <p>Background</p> <p>Chronic arsenic exposure has been shown to cause liver damage. However, serum hepatic enzyme activity as recognized on liver function tests (LFTs) showing a dose-response relationship with arsenic exposure has not yet been clearly documented. The aim of our study was to investigate the dose-response relationship between arsenic exposure and major serum enzyme marker activity associated with LFTs in the population living in arsenic-endemic areas in Bangladesh.</p> <p>Methods</p> <p>A total of 200 residents living in arsenic-endemic areas in Bangladesh were selected as study subjects. Arsenic concentrations in the drinking water, hair and nails were measured by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The study subjects were stratified into quartile groups as follows, based on concentrations of arsenic in the drinking water, as well as in subjects' hair and nails: lowest, low, medium and high. The serum hepatic enzyme activities of alkaline phosphatase (ALP), aspartate transaminase (AST) and alanine transaminase (ALT) were then assayed.</p> <p>Results</p> <p>Arsenic concentrations in the subjects' hair and nails were positively correlated with arsenic levels in the drinking water. As regards the exposure-response relationship with arsenic in the drinking water, the respective activities of ALP, AST and ALT were found to be significantly increased in the high-exposure groups compared to the lowest-exposure groups before and after adjustments were made for different covariates. With internal exposure markers (arsenic in hair and nails), the ALP, AST and ALT activity profiles assumed a similar shape of dose-response relationship, with very few differences seen in the higher groups compared to the lowest group, most likely due to the temporalities of exposure metrics.</p> <p>Conclusions</p> <p>The present study demonstrated that arsenic concentrations in the drinking water were strongly correlated with arsenic concentrations in the subjects' hair and nails. Further, this study revealed a novel exposure- and dose- response relationship between arsenic exposure metrics and serum hepatic enzyme activity. Elevated serum hepatic enzyme activities in the higher exposure gradients provided new insights into arsenic-induced liver toxicity that might be helpful for the early prognosis of arsenic-induced liver diseases.</p

Development of a novel motivational interviewing (MI) informed peer-support intervention to support mothers to breastfeed for longer

Background: Many women in the UK stop breastfeeding before they would like to, and earlier than is recommended by the World Health Organization (WHO). Given the potential health benefits for mother and baby, new ways of supporting women to breastfeed for longer are required. The purpose of this study was to develop and characterise a novel Motivational Interviewing (MI) informed breastfeeding peer-support intervention. Methods: Qualitative interviews with health professionals and service providers (n=14), and focus groups with mothers (n=14), fathers (n=3), and breastfeeding peer-supporters (n=15) were carried out to understand experiences of breastfeeding peer-support and identify intervention options. Data were audio-recorded, transcribed, and analysed thematically. Consultation took place with a combined professional and lay Stakeholder Group (n=23). The Behaviour Change Wheel (BCW) guided intervention development process used the findings of the qualitative research and stakeholder consultation, alongside evidence from existing literature, to identify: the target behaviour to be changed; sources of this behaviour based on the Capability, Opportunity and Motivation (COM-B) model; intervention functions that could alter this behaviour; and; mode of delivery for the intervention. Behaviour change techniques included in the intervention were categorised using the Behaviour Change Technique Taxonomy Version 1 (BCTTv1). Results: Building knowledge, skills, confidence, and providing social support were perceived to be key functions of breastfeeding peer-support interventions that aim to decrease early discontinuation of breastfeeding. These features of breastfeeding peer-support mapped onto the BCW education, training, modelling and environmental restructuring intervention functions. Behaviour change techniques (BCTTv1) included social support, problem solving, and goal setting. The intervention included important inter-personal relational features (e.g. trust, honesty, kindness), and the BCTTv1 needed adaptation to incorporate this. Conclusions: The MI-informed breastfeeding peer-support intervention developed using this systematic and user-informed approach has a clear theoretical basis and well-described behaviour 3 change techniques. The process described could be useful in developing other complex interventions that incorporate peer-support and/or MI

Genetic variants in mannose receptor gene (MRC1) confer susceptibility to increased risk of sarcoidosis

<p>Abstract</p> <p>Background</p> <p>Mannose receptor (MR) is a member of the C-type lectin receptor family involved in pathogen molecular-pattern recognition and thought to be critical in shaping host immune response. The aim of this study was to investigate potential associations of genetic variants in the <it>MRC1 </it>gene with sarcoidosis.</p> <p>Methods</p> <p>Nine single nucleotide polymorphisms (SNPs), encompassing the <it>MRC1 </it>gene, were genotyped in a total of 605 Japanese consisting of 181 sarcoidosis patients and 424 healthy controls.</p> <p>Results</p> <p>Suggestive evidence of association between rs691005 SNP and risk of sarcoidosis was observed independent of sex and age in a recessive model (<it>P </it>= 0.001).</p> <p>Conclusions</p> <p>These results suggest that <it>MRC1 </it>is an important candidate gene for sarcoidosis. This is the first study to imply that genetic variants in <it>MRC1</it>, a major member of the C-type lectin, contribute to the development of sarcoidosis.</p

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Eccentric Exercise Activates Novel Transcriptional Regulation of Hypertrophic Signaling Pathways Not Affected by Hormone Changes

Unaccustomed eccentric exercise damages skeletal muscle tissue, activating mechanisms of recovery and remodeling that may be influenced by the female sex hormone 17β-estradiol (E2). Using high density oligonucleotide based microarrays, we screened for differences in mRNA expression caused by E2 and eccentric exercise. After random assignment to 8 days of either placebo (CON) or E2 (EXP), eighteen men performed 150 single-leg eccentric contractions. Muscle biopsies were collected at baseline (BL), following supplementation (PS), +3 hours (3H) and +48 hours (48H) after exercise. Serum E2 concentrations increased significantly with supplementation (P<0.001) but did not affect microarray results. Exercise led to early transcriptional changes in striated muscle activator of Rho signaling (STARS), Rho family GTPase 3 (RND3), mitogen activated protein kinase (MAPK) regulation and the downstream transcription factor FOS. Targeted RT-PCR analysis identified concurrent induction of negative regulators of calcineurin signaling RCAN (P<0.001) and HMOX1 (P = 0.009). Protein contents were elevated for RND3 at 3H (P = 0.02) and FOS at 48H (P<0.05). These findings indicate that early RhoA and NFAT signaling and regulation are altered following exercise for muscle remodeling and repair, but are not affected by E2

Bayesian Dynamical Systems Modelling in the Social Sciences

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach