Membrane glucocorticoid receptors are localised in the extracellular matrix and signal through the MAPK pathway in mammalian skeletal muscle fibres

A number of studies have previously proposed the existence of glucocorticoid receptors on the plasma membrane of many cell types including skeletal muscle fibres. However, their exact localisation and the cellular signalling pathway(s) they utilise to communicate with the rest of the cell are still poorly understood. In this study, we investigated the localisation and the mechanism(s) underlying the non-genomic physiological functions of these receptors in mouse skeletal muscle cells. The results show that the receptors were localised in the cytoplasm in myoblasts, in the nucleus in myotubes and in the extracellular matrix, in satellite cells and in the proximity of mitochondria in adult muscle fibres. Also, they bound laminin in a glucocorticoid-dependent manner. Treating small skeletal muscle fibre bundles with the synthetic glucocorticoid, beclomethasone dipropionate, increased the phosphorylation (=activation) of extracellular-signal regulated kinase 1&2, c-Jun N-terminal kinase and p38 mitogen-activated protein kinase. This occurred within 5min and depended on the fibre-type and the duration of the treatment. It was also abolished by the glucocorticoid receptor inhibitor, mifepristone, and a monoclonal antibody against the receptor. From these results we conclude that the non-genomic/non-canonical physiological functions of glucocorticoids, in adult skeletal muscle fibres are mediated by a glucocorticoid receptor localised in the extracellular matrix, in satellite cells and close to mitochondria and involve activation of the MAPK pathway

Infering Air Quality from Traffic Data using Transferable Neural Network Models

This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy requirements. Measurement equipment tends to be expensive to purchase and maintain. Therefore, a model based approach capable of accurate determination of pollution levels is highly beneficial. The objective of this study was to develop a neural network model to accurately infer pollution levels from existing data sources in Leicester, UK. Neural Networks are models made of several highly interconnected processing elements. These elements process information by their dynamic state response to inputs. Problems which were not solvable by traditional algorithmic approaches frequently can be solved using neural networks. This paper shows that using a simple neural network with traffic and meteorological data as inputs, the air quality can be estimated with a good level of generalisation and in near real-time. By applying these models to links rather than nodes, this methodology can directly be used to inform traffic engineers and direct traffic management decisions towards enhancing local air quality and traffic management simultaneously.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

An optimized TOPS+ comparison method for enhanced TOPS models

This article has been made available through the Brunel Open Access Publishing Fund.Background Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. Results We have developed a TOPS+ string model as an improvement to the TOPS [1-3] graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset [4] demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. Conclusions Our advanced TOPS+ comparison shows better performance on the PDB40 dataset [4] compared to our basic TOPS+ method, giving 90 percent accuracy for SCOP alpha+beta; a 6 percent increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset [5], achieving 98 percent accuracy. Software Availability: The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.This article is available through the Brunel Open Access Publishing Fun

The effect of prior walking on coronary heart disease risk markers in South Asian and European men.

Purpose: Heart disease risk is elevated in South Asians possibly due to impaired postprandial metabolism. Running has been shown to induce greater reductions in postprandial lipaemia in South Asian than European men but the effect of walking in South Asians is unknown. Methods: Fifteen South Asian and 14 White European men aged 19-30 years completed two, 2-d trials in a randomised crossover design. On day 1, participants rested (control) or walked for 60 min at approximately 50% maximum oxygen uptake (exercise). On day 2, participants rested and consumed two high fat meals over a 9h period during which 14 venous blood samples were collected. Results: South Asians exhibited higher postprandial triacylglycerol (geometric mean (95% confidence interval) 2.29(1.82 to 2.89) vs. 1.54(1.21 to 1.96) mmol·L-1·hr-1), glucose (5.49(5.21 to 5.79) vs. 5.05(4.78 to 5.33) mmol·L-1·hr-1), insulin (32.9(25.7 to 42.1) vs. 18.3(14.2 to 23.7) µU·mL-1·hr-1) and interleukin-6 (2.44(1.61 to 3.67) vs. 1.04(0.68 to 1.59) pg·mL-1·hr-1) than Europeans (all ES ≥ 0.72, P≤0.03). Between-group differences in triacylglycerol, glucose and insulin were not significant after controlling for age and percentage body fat. Walking reduced postprandial triacylglycerol (1.79(1.52 to 2.12) vs. 1.97(1.67 to 2.33) mmol·L-1·hr-1) and insulin (21.0(17.0 to 26.0) vs. 28.7(23.2 to 35.4) µU·mL-1·hr-1) (all ES ≥ 0.23. P≤0.01), but group differences were not significant. Conclusions: Healthy South Asians exhibited impaired postprandial metabolism compared with White Europeans, but these differences were diminished after controlling for potential confounders. The small-moderate reduction in postprandial triacylglycerol and insulin after brisk walking was not different between the ethnicities

Timescales of transformational climate change adaptation in sub-Saharan African agriculture

Climate change is projected to constitute a significant threat to food security if no adaptation actions are taken. Transformation of agricultural systems, for example switching crop types or moving out of agriculture, is projected to be necessary in some cases. However, little attention has been paid to the timing of these transformations. Here, we develop a temporal uncertainty framework using the CMIP5 ensemble to assess when and where cultivation of key crops in sub-Saharan Africa becomes unviable. We report potential transformational changes for all major crops during the twenty-first century, as climates shift and areas become unsuitable. For most crops, however, transformation is limited to small pockets (<15% of area), and only for beans, maize and banana is transformation more widespread (â 1/430% area for maize and banana, 60% for beans). We envisage three overlapping adaptation phases to enable projected transformational changes: an incremental adaptation phase focused on improvements to crops and management, a preparatory phase that establishes appropriate policies and enabling environments, and a transformational adaptation phase in which farmers substitute crops, explore alternative livelihoods strategies, or relocate. To best align policies with production triggers for no-regret actions, monitoring capacities to track farming systems as well as climate are needed

C-reactive protein levels in patients at cardiovascular risk: EURIKA study

Background: Elevated C-reactive protein (CRP) levels are associated with high cardiovascular risk, and might identify patients who could benefit from more carefully adapted risk factor management. We have assessed the prevalence of elevated CRP levels in patients with one or more traditional cardiovascular risk factors. Methods: Data were analysed from the European Study on Cardiovascular Risk Prevention and Management in Usual Daily Practice (EURIKA, ClinicalTrials.gov Identifier: NCT00882336), which included patients (aged ≥50 years) from 12 European countries with at least one traditional cardiovascular risk factor but no history of cardiovascular disease. Analysis was also carried out on the subset of patients without diabetes mellitus who were not receiving statin therapy. Results: In the overall population, CRP levels were positively correlated with body mass index and glycated haemoglobin levels, and were negatively correlated with high-density lipoprotein cholesterol levels. CRP levels were also higher in women, those at higher traditionally estimated cardiovascular risk and those with greater numbers of metabolic syndrome markers. Among patients without diabetes mellitus who were not receiving statin therapy, approximately 30% had CRP levels ≥3 mg/L, and approximately 50% had CRP levels ≥2 mg/L, including those at intermediate levels of traditionally estimated cardiovascular risk. Conclusions: CRP levels are elevated in a large proportion of patients with at least one cardiovascular risk factor, without diabetes mellitus who are not receiving statin therapy, suggesting a higher level of cardiovascular risk than predicted according to conventional risk estimation systems

Mass-encoded synthetic biomarkers for multiplexed urinary monitoring of disease

Biomarkers are becoming increasingly important in the clinical management of complex diseases, yet our ability to discover new biomarkers remains limited by our dependence on endogenous molecules. Here we describe the development of exogenously administered 'synthetic biomarkers' composed of mass-encoded peptides conjugated to nanoparticles that leverage intrinsic features of human disease and physiology for noninvasive urinary monitoring. These protease-sensitive agents perform three functions in vivo: they target sites of disease, sample dysregulated protease activities and emit mass-encoded reporters into host urine for multiplexed detection by mass spectrometry. Using mouse models of liver fibrosis and cancer, we show that these agents can noninvasively monitor liver fibrosis and resolution without the need for invasive core biopsies and substantially improve early detection of cancer compared with current clinically used blood biomarkers. This approach of engineering synthetic biomarkers for multiplexed urinary monitoring should be broadly amenable to additional pathophysiological processes and point-of-care diagnostics.National Institutes of Health (U.S.) (Bioengineering Research Partnership R01 CA124427)Kathy and Curt Marble Cancer Research FundNational Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service Award (F32CA159496-01

Impact of the AHI1 Gene on the Vulnerability to Schizophrenia: A Case-Control Association Study

BackgroundThe Abelson helper integration-1 (AHI1) gene is required for both cerebellar and cortical development in humans. While the accelerated evolution of AHI1 in the human lineage indicates a role in cognitive (dys)function, a linkage scan in large pedigrees identified AHI1 as a positional candidate for schizophrenia. To further investigate the contribution of AHI1 to the susceptibility of schizophrenia, we evaluated the effect of AHI1 variation on the vulnerability to psychosis in two samples from Spain and Germany.Methodology/Principal Findings29 single-nucleotide polymorphisms (SNPs) located in a genomic region including the AHI1 gene were genotyped in two samples from Spain (280 patients with psychotic disorders; 348 controls) and Germany (247 patients with schizophrenic disorders; 360 controls). Allelic, genotypic and haplotype frequencies were compared between cases and controls in both samples separately, as well as in the combined sample. The effect of genotype on several psychopathological measures (BPRS, KGV, PANSS) assessed in a Spanish subsample was also evaluated. We found several significant associations in the Spanish sample. Particularly, rs7750586 and rs911507, both located upstream of the AHI1 coding region, were found to be associated with schizophrenia in the analysis of genotypic (p = 0.0033, and 0.031, respectively) and allelic frequencies (p = 0.001 in both cases). Moreover, several other risk and protective haplotypes were detected (0.006<p<0.036). Joint analysis also supported the association of rs7750586 and rs911507 with the risk for schizophrenia. The analysis of clinical measures also revealed an effect on symptom severity (minimum P value = 0.0037).Conclusions/SignificanceOur data support, in agreement with previous reports, an effect of AHI1 variation on the susceptibility to schizophrenia in central and southern European populations

Systematic review of methods used in meta-analyses where a primary outcome is an adverse or unintended event

addresses: Peninsula College of Medicine and Dentistry, St Luke's Campus, University of Exeter, Exeter, UK. [email protected]: PMCID: PMC3528446types: Journal Article; Research Support, Non-U.S. Gov't© 2012 Warren et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Adverse consequences of medical interventions are a source of concern, but clinical trials may lack power to detect elevated rates of such events, while observational studies have inherent limitations. Meta-analysis allows the combination of individual studies, which can increase power and provide stronger evidence relating to adverse events. However, meta-analysis of adverse events has associated methodological challenges. The aim of this study was to systematically identify and review the methodology used in meta-analyses where a primary outcome is an adverse or unintended event, following a therapeutic intervention

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types