Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Predictors of Shoulder Pain and Disability Index (SPADI) and work status after 1 year in patients with subacromial shoulder pain

<p>Abstract</p> <p>Background</p> <p>Shoulder pain is a common complaint in primary health care and has an unfavourable outcome in many patients. The objectives were to identify predictors for pain and disability (SPADI) and work status in patients with subacromial shoulder pain.</p> <p>Methods</p> <p>Secondary analyses of data from a randomized clinical controlled trial were performed. Outcome measures were the absolute values of the combined Shoulder Pain and Disability Index (SPADI) and work status 1 year after treatment with supervised exercises (SE) or radial extracorporeal shockwave therapy (rESWT). Predictors of outcome were investigated using multiple linear regression (SPADI) and logistic regression (work status).</p> <p>Results</p> <p>104 patients were included. Low education (≤ 12 years), previous shoulder pain, and a high baseline SPADI score predicted poor results with these variables explaining 29.9% of the variance in SPADI score at 1 year. Low education and poor self-reported health status predicted a work status of "not working": Odds Ratio, OR = 4.3(95% CI (1.3 to 14.9)), p = 0.02 for education, and OR = 1.06 (95% CI (1.0 to 1.1)), p = 0.001 for self-reported health status, respectively. Adjustments for age, gender, and treatment group were performed, but did not change the results.</p> <p>Conclusion</p> <p>Education was the most consistent predictor of pain and disability, and work status at 1 year follow-up. Also, baseline SPADI score, previous shoulder pain and self-reported health status predicted outcome.</p> <p>Trial registration</p> <p>Clinical trials NCT00653081</p

Class dynamics of development: a methodological note

This article argues that class relations are constitutive of developmental processes and central to understanding inequality within and between countries. In doing so it illustrates and explains the diversity of the actually existing forms of class relations, and the ways in which they interplay with other social relations such as gender and ethnicity. This is part of a wider project to re- vitalise class analysis in the study of development problems and experiences

Predictors of stable return-to-work in non-acute, non-specific spinal pain: low total prior sick-listing, high self prediction and young age. A two-year prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Non-specific spinal pain (NSP), comprising back and/or neck pain, is one of the leading disorders in long-term sick-listing. During 2000-2004, 125 Swedish primary-care patients with non-acute NSP, full-time sick-listed 6 weeks-2 years, were included in a randomized controlled trial to compare a cognitive-behavioural programme with traditional primary care. This prospective cohort study is a re-assessment of the data from the randomized trial with the 2 treatment groups considered as a single cohort. The aim was to investigate which baseline variables predict a stable return-to-work during a 2-year period after baseline: objective variables from function tests, socioeconomic, subjective and/or treatment variables. Stable return-to-work was a return-to-work lasting for at least 1 month from the start of follow-up.</p> <p>Methods</p> <p><it>Stable return-to-work </it>was the outcome variable, the above-mentioned factors were the predictive variables in multiple-logistic regression models, one per follow-up at 6, 12, 18 and 24 months after baseline. The factors from univariate analyzes with a <it>p</it>-value of at most .10 were included. The non-significant variables were excluded stepwise to yield models comprising only significant factors (<it>p </it>< .05). As the comparatively few cases made it risky to associate certain predictors with certain time-points, we finally considered the predictors which were represented in at least 3 follow-ups. They are presented with odds ratios (OR) and 95% confidence intervals.</p> <p>Results</p> <p>Three variables qualified, all of them represented in 3 follow-ups: <it>Low total prior sick-listing </it>(including all diagnoses) was the strongest predictor in 2 follow-ups, 18 and 24 months, OR 4.8 [1.9-12.3] and 3.8 [1.6-8.7] respectively, <it>High self prediction </it>(the patients' own belief in return-to-work) was the strongest at 12 months, OR 5.2 [1.5-17.5] and <it>Young age </it>(max 44 years) the second strongest at 18 months, OR 3.5 [1.3-9.1].</p> <p>Conclusions</p> <p>In primary-care patients with non-acute NSP, the strong predictors of stable return-to-work were 2 socioeconomic variables, <it>Low total prior sick-listing </it>and <it>Young age</it>, and 1 subjective variable, <it>High self-prediction</it>. Objective variables from function tests and treatment variables were non-predictors. Except for <it>Young age</it>, the predictors have previously been insufficiently studied, and so our study should widen knowledge within clinical practice.</p> <p>Trial registration</p> <p>Trial registration number for the original trial NCT00488735.</p

The social dimension of globalization: A review of the literature

With globalization affecting so many inter-connected areas, it is difficult to grasp its full impact. This literature review of over 120 sources considers the impact of globalization on wages and taxes, poverty, inequality, insecurity, child labour, gender, and migration. Opening with some stylized facts concerning globalization in 1985-2002, the authors then highlight recent findings on these areas, reporting on controversies and on emerging consensus where it exists. There follows a review of national and international policy responses designed to make globalization more sustainable and equitable and to deliver decent jobs, security and a voice in decision-making

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

The role of livestock grazing in long-term vegetation changes in coastal dunes: a case study from the Netherlands

The vegetation of coastal sand dunes is characterized by high species diversity and comprises some of the rarest vegetation types in North-Western Europe. Among them are dune grassland communities whose species richness relies on grazing. Those communities are assessed as a priority habitat type under the Natura 2000 legislation. In autumn 1990, Galloway cows and Nordic Fjord horses were introduced in the coastal dunes of Meijendel near The Hague (52°7'N, 4°20'E), The Netherlands, to reduce encroachment of tall grasses and shrubs, to develop bare sand patches, and as such facilitating diverse vegetation structures in the dune grasslands. In the 1950s, decades before the introduction of livestock, 41 permanent plots were installed. On average, they were examined every four years. Our study hypothesised that the livestock grazing in the set densities would halt progressive succession and facilitate regressive succession. Up to 1990, we observed an equilibrium between progressive and regressive succession. After 1990, however, our data showed a pronounced progressive succession contradicting the hypothesized effect of the livestock grazing. We relate the main observed patterns with two factors linked to rabbit populations: (i) the myxomatosis outbreak in 1954 and (ii) the rabbit Viral Haemorrhagic Disease (rVHD-1) outbreak in 1989. In addition to livestock grazing, rabbits block progressive succession by feeding on seedlings of shrub and tree species and digging burrows, creating small-scale mosaics of bare sand and initiate blowout development when collapsing. We state that the substantial decrease in rabbit numbers due to the viral diseases likely caused the observed increase of shrubs and trees in the study area's permanent plots. Climate change might have contributed to the observed increase in autonomous blowout development since 2001, as well as a decrease in atmospheric nitrogen deposition since 1990, after a strong increase the decades before

Using artificial neural networks to accelerate flowsheet optimization for downstream process development

An optimal purification process for biopharmaceutical products is important to meet strict safety regulations, and for economic benefits. To find the global optimum, it is desirable to screen the overall design space. Advanced model-based approaches enable to screen a broad range of the design-space, in contrast to traditional statistical or heuristic-based approaches. Though, chromatographic mechanistic modeling (MM), one of the advanced model-based approaches, can be speed-limiting for flowsheet optimization, which evaluates every purification possibility (e.g., type and order of purification techniques, and their operating conditions). Therefore, we propose to use artificial neural networks (ANNs) during global optimization to select the most optimal flowsheets. So, the number of flowsheets for final local optimization is reduced and consequently the overall optimization time. Employing ANNs during global optimization proved to reduce the number of flowsheets from 15 to only 3. From these three, one flowsheet was optimized locally and similar final results were found when using the global outcome of either the ANN or MM as starting condition. Moreover, the overall flowsheet optimization time was reduced by 50% when using ANNs during global optimization. This approach accelerates the early purification process design; moreover, it is generic, flexible, and regardless of sample material's type.</p