Exercise-induced improvements in liver fat and endothelial function are not sustained 12 months following cessation of exercise supervision in non-alcoholic fatty liver disease (NAFLD).

AIMS: Supervised exercise reduces liver fat and improves endothelial function, a surrogate of cardiovascular disease risk, in non-alcoholic fatty liver disease (NAFLD). We hypothesised that after a 16-week supervised exercise program, patients would maintain longer-term improvements in cardiorespiratory fitness, liver fat and endothelial function. MATHERIALS AND METHODS: Ten NAFLD patients [5/5 males/females, age 51±13years, BMI 31±3 kg.m(2) (mean±s.d.)] underwent a 16-week supervised moderate-intensity exercise intervention. Biochemical markers, cardiorespiratory fitness (VO2peak), subcutaneous, visceral and liver fat (measured by magnetic resonance imaging and spectroscopy respectively) and brachial artery flow-mediated dilation (FMD) were assessed at baseline, after 16 weeks supervised training and 12-months after ending supervision. RESULTS: Despite no significant change in body weight, there were significant improvements in VO2peak [6.5 ml.kg(-1).min(-1) (95% CI 2.8, 10.1); P=0.003], FMD [2.9% (1.5, 4.2); P=0.001], liver transaminases (P0.05) and liver fat [1.4% (-13.0, 15.9); P=0.83] were not significantly different from baseline. CONCLUSIONS: Twelve months following cessation of supervision, exercise-mediated improvements in liver fat and other cardiometabolic variables had reversed with cardiorespiratory fitness at baseline levels. Maintenance of high cardiorespiratory fitness and stability of body weight are critical public health considerations for the treatment of NAFLD.International Journal of Obesity accepted article preview online, 21 July 2016. doi:10.1038/ijo.2016.123

Sideband Cooling Micromechanical Motion to the Quantum Ground State

The advent of laser cooling techniques revolutionized the study of many atomic-scale systems. This has fueled progress towards quantum computers by preparing trapped ions in their motional ground state, and generating new states of matter by achieving Bose-Einstein condensation of atomic vapors. Analogous cooling techniques provide a general and flexible method for preparing macroscopic objects in their motional ground state, bringing the powerful technology of micromechanics into the quantum regime. Cavity opto- or electro-mechanical systems achieve sideband cooling through the strong interaction between light and motion. However, entering the quantum regime, less than a single quantum of motion, has been elusive because sideband cooling has not sufficiently overwhelmed the coupling of mechanical systems to their hot environments. Here, we demonstrate sideband cooling of the motion of a micromechanical oscillator to the quantum ground state. Entering the quantum regime requires a large electromechanical interaction, which is achieved by embedding a micromechanical membrane into a superconducting microwave resonant circuit. In order to verify the cooling of the membrane motion into the quantum regime, we perform a near quantum-limited measurement of the microwave field, resolving this motion a factor of 5.1 from the Heisenberg limit. Furthermore, our device exhibits strong-coupling allowing coherent exchange of microwave photons and mechanical phonons. Simultaneously achieving strong coupling, ground state preparation and efficient measurement sets the stage for rapid advances in the control and detection of non-classical states of motion, possibly even testing quantum theory itself in the unexplored region of larger size and mass.Comment: 13 pages, 7 figure

Prediction of photoperiodic regulators from quantitative gene circuit models

Photoperiod sensors allow physiological adaptation to the changing seasons. The external coincidence hypothesis postulates that a light-responsive regulator is modulated by a circadian rhythm. Sufficient data are available to test this quantitatively in plants, though not yet in animals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their lightsensitive proteins are thought to form an external coincidence sensor. We use 40 timeseries of molecular data to model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, the models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modelling makes this complexity explicit and may thus contribute to crop improvement

Study protocol: The Intensive Care Outcome Network ('ICON') study

<p>Abstract</p> <p>Background</p> <p>Extended follow-up of survivors of ICU treatment has shown many patients suffer long-term physical and psychological consequences that affect their health-related quality of life. The current lack of rigorous longitudinal studies means that the true prevalence of these physical and psychological problems remains undetermined.</p> <p>Methods/Design</p> <p>The ICON (Intensive Care Outcome Network) study is a multi-centre, longitudinal study of survivors of critical illness. Patients will be recruited prior to hospital discharge from 20–30 ICUs in the UK and will be assessed at 3, 6, and 12 months following ICU discharge for health-related quality of life as measured by the Short Form-36 (SF-36) and the EuroQoL (EQ-5D); anxiety and depression as measured by the Hospital Anxiety and Depression Scale (HADS); and post traumatic stress disorder (PTSD) symptoms as measured by the PTSD Civilian Checklist (PCL-C). Postal questionnaires will be used.</p> <p>Discussion</p> <p>The ICON study will create a valuable UK database detailing the prevalence of physical and psychological morbidity experienced by patients as they recover from critical illness. Knowledge of the prevalence of physical and psychological morbidity in ICU survivors is important because research to generate models of causality, prognosis and treatment effects is dependent on accurate determination of prevalence. The results will also inform economic modelling of the long-term burden of critical illness.</p> <p>Trial Registration</p> <p>ISRCTN69112866</p

Growth characteristics in individuals with osteogenesis imperfecta in North America: results from a multicenter study.

PurposeOsteogenesis imperfecta (OI) predisposes people to recurrent fractures, bone deformities, and short stature. There is a lack of large-scale systematic studies that have investigated growth parameters in OI.MethodsUsing data from the Linked Clinical Research Centers, we compared height, growth velocity, weight, and body mass index (BMI) in 552 individuals with OI. Height, weight, and BMI were plotted on Centers for Disease Control and Prevention normative curves.ResultsIn children, the median z-scores for height in OI types I, III, and IV were -0.66, -6.91, and -2.79, respectively. Growth velocity was diminished in OI types III and IV. The median z-score for weight in children with OI type III was -4.55. The median z-scores for BMI in children with OI types I, III, and IV were 0.10, 0.91, and 0.67, respectively. Generalized linear model analyses demonstrated that the height z-score was positively correlated with the severity of the OI subtype (P &lt; 0.001), age, bisphosphonate use, and rodding (P &lt; 0.05).ConclusionFrom the largest cohort of individuals with OI, we provide median values for height, weight, and BMI z-scores that can aid the evaluation of overall growth in the clinic setting. This study is an important first step in the generation of OI-specific growth curves

MemBrain: Improving the Accuracy of Predicting Transmembrane Helices

Prediction of transmembrane helices (TMH) in α helical membrane proteins provides valuable information about the protein topology when the high resolution structures are not available. Many predictors have been developed based on either amino acid hydrophobicity scale or pure statistical approaches. While these predictors perform reasonably well in identifying the number of TMHs in a protein, they are generally inaccurate in predicting the ends of TMHs, or TMHs of unusual length. To improve the accuracy of TMH detection, we developed a machine-learning based predictor, MemBrain, which integrates a number of modern bioinformatics approaches including sequence representation by multiple sequence alignment matrix, the optimized evidence-theoretic K-nearest neighbor prediction algorithm, fusion of multiple prediction window sizes, and classification by dynamic threshold. MemBrain demonstrates an overall improvement of about 20% in prediction accuracy, particularly, in predicting the ends of TMHs and TMHs that are shorter than 15 residues. It also has the capability to detect N-terminal signal peptides. The MemBrain predictor is a useful sequence-based analysis tool for functional and structural characterization of helical membrane proteins; it is freely available at http://chou.med.harvard.edu/bioinf/MemBrain/

Improving appropriate polypharmacy for older people in primary care: selecting components of an evidence-based intervention to target prescribing and dispensing

Background The use of multiple medicines (polypharmacy) is increasingly common in older people. Ensuring that patients receive the most appropriate combinations of medications (appropriate polypharmacy) is a significant challenge. The quality of evidence to support the effectiveness of interventions to improve appropriate polypharmacy is low. Systematic identification of mediators of behaviour change, using the Theoretical Domains Framework (TDF), provides a theoretically robust evidence base to inform intervention design. This study aimed to (1) identify key theoretical domains that were perceived to influence the prescribing and dispensing of appropriate polypharmacy to older patients by general practitioners (GPs) and community pharmacists, and (2) map domains to associated behaviour change techniques (BCTs) to include as components of an intervention to improve appropriate polypharmacy in older people in primary care. Methods Semi-structured interviews were conducted with members of each healthcare professional (HCP) group using tailored topic guides based on TDF version 1 (12 domains). Questions covering each domain explored HCPs’ perceptions of barriers and facilitators to ensuring the prescribing and dispensing of appropriate polypharmacy to older people. Interviews were audio-recorded and transcribed verbatim. Data analysis involved the framework method and content analysis. Key domains were identified and mapped to BCTs based on established methods and discussion within the research team. Results Thirty HCPs were interviewed (15 GPs, 15 pharmacists). Eight key domains were identified, perceived to influence prescribing and dispensing of appropriate polypharmacy: ‘Skills’, ‘Beliefs about capabilities’, ‘Beliefs about consequences’, ‘Environmental context and resources’, ‘Memory, attention and decision processes’, ‘Social/professional role and identity’, ‘Social influences’ and ‘Behavioural regulation’. Following mapping, four BCTs were selected for inclusion in an intervention for GPs or pharmacists: ‘Action planning’, ‘Prompts/cues’, ‘Modelling or demonstrating of behaviour’ and ‘Salience of consequences’. An additional BCT (‘Social support or encouragement’) was selected for inclusion in a community pharmacy-based intervention in order to address barriers relating to interprofessional working that were encountered by pharmacists. Conclusions Selected BCTs will be operationalised in a theory-based intervention to improve appropriate polypharmacy for older people, to be delivered in GP practice and community pharmacy settings. Future research will involve development and feasibility testing of this intervention

A Combination of Compositional Index and Genetic Algorithm for Predicting Transmembrane Helical Segments

Transmembrane helix (TMH) topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method. Availability: The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm

Investor heterogeneity and the cross-section of U.K. investment trust performance

We use the upper and lower bounds derived by Ferson and Lin (2010) to examine the impact of investor heterogeneity on the performance of U.K. investment trusts relative to alternative linear factor models. We find using the upper bounds that investor heterogeneity has an important impact for nearly all investment trusts. The upper bounds are large in economic terms and significantly different from zero. We find no evidence of any trusts where all investors agree on the sign of performance beyond what we expect by chance. Using the lower bound, we find that trusts with a larger disagreement about trust performance have a weaker relation between the trust premium and past Net Asset Value (NAV) performance

A survey of integral α-helical membrane proteins

Membrane proteins serve as cellular gatekeepers, regulators, and sensors. Prior studies have explored the functional breadth and evolution of proteins and families of particular interest, such as the diversity of transport-associated membrane protein families in prokaryotes and eukaryotes, the composition of integral membrane proteins, and family classification of all human G-protein coupled receptors. However, a comprehensive analysis of the content and evolutionary associations between membrane proteins and families in a diverse set of genomes is lacking. Here, a membrane protein annotation pipeline was developed to define the integral membrane genome and associations between 21,379 proteins from 34 genomes; most, but not all of these proteins belong to 598 defined families. The pipeline was used to provide target input for a structural genomics project that successfully cloned, expressed, and purified 61 of our first 96 selected targets in yeast. Furthermore, the methodology was applied (1) to explore the evolutionary history of the substrate-binding transmembrane domains of the human ABC transporter superfamily, (2) to identify the multidrug resistance-associated membrane proteins in whole genomes, and (3) to identify putative new membrane protein families