Benefits of short-term training with vibrotactile biofeedback of trunk sway on balance control in multiple sclerosis

Background and Aims: Patients with multiple sclerosis (MS) suffer from diminished balance control. We examined whether 4 sessions of training with vibrotactile biofeedback (VTfb) of trunk sway could improve their balance control and provide a carry-over effect. Methods: Baseline trunk sway was first measured for 15 MS patients. Then they received head mounted VTfb of trunk sway which was directionally active when trunk sway exceeded limits set using the baseline assessments. Stance and gait tasks were trained 2 times weekly for 2 weeks with VTfb. Assessments with VTfb were performed at the end of each week. Two weeks later balance was assessed without VTfb to determine if a carry-over effect was present. Results: Assessments with VTfb showed a significant decrease in trunk sway after 1 and 2 weeks of VTfb training (p<0.02). Carry-over improvements were also present (p<0.02). The greatest effects were found for tests of standing eyes closed stance on foam which resulted in a 59% decreased pitch sway angle (p=0.002) with VTfb and a 51% reduction (p=0.03) carry-over effect. Conclusions: This study indicates that balance control in MS patients improves rapidly after one week of training with VTfb and more slowly subsequently. The carry-over effect lasted at least 2 weeks. Future studies should determine, with more weeks of VTfb training, the time course of the slower balance and carry-over improvements following the first rapid improvement in balance control. We conclude that training with VTfb of trunk sway significantly improves balance control in MS patients, and could possibly reduce falls

Analysis of IL2/IL21 Gene Variants in Cholestatic Liver Diseases Reveals an Association with Primary Sclerosing Cholangitis

Background/Aims: The chromosome 4q27 region harboring IL2 and IL21 is an established risk locus for ulcerative colitis (UC) and various other autoimmune diseases. Considering the strong coincidence of primary sclerosing cholangitis (PSC) with UC and the increased frequency of other autoimmune disorders in patients with primary biliary cirrhosis (PBC), we investigated whether genetic variation in the IL2/IL21 region may also modulate the susceptibility to these two rare cholestatic liver diseases. Methods: Four strongly UC-associated single nucleotide polymorphisms (SNPs) within the KIAA1109/TENR/IL2/IL21 linkage disequilibrium block were genotyped in 124 PBC and 41 PSC patients. Control allele frequencies from 1,487 healthy, unrelated Caucasians were available from a previous UC association study. Results: The minor alleles of all four markers were associated with a decreased susceptibility to PSC (rs13151961: p = 0.013, odds ratio (OR) 0.34; rs13119723: p = 0.023, OR 0.40; rs6822844: p = 0.031, OR 0.41; rs6840978: p = 0.043, OR 0.46). Moreover, a haplotype consisting of the four minor alleles also had a protective effect on PSC susceptibility (p = 0.0084, OR 0.28). A haplotype of the four major alleles was independently associated with PSC when excluding the patients with concomitant inflammatory bowel disease (p = 0.033, OR 4.18). Conclusion: The IL2/IL21 region may be one of the highly suggestive but so far rarely identified shared susceptibility loci for PSC and UC. Copyright (C) 2011 S. Karger AG, Base

The human brain networks mediating the vestibular sensation of self-motion

Vestibular Agnosia - where peripheral vestibular activation triggers the usual reflex nystagmus response but with attenuated or no self-motion perception - is found in brain disease with disrupted cortical network functioning, e.g. traumatic brain injury (TBI) or neurodegeneration (Parkinson's Disease). Patients with acute focal hemispheric lesions (e.g. stroke) do not manifest vestibular agnosia. Thus, brain network mapping techniques, e.g. resting state functional MRI (rsfMRI), are needed to interrogate functional brain networks mediating vestibular agnosia. Hence, we prospectively recruited 39 acute TBI patients with preserved peripheral vestibular function and obtained self-motion perceptual thresholds during passive yaw rotations in the dark and additionally acquired whole-brain rsfMRI in the acute phase. Following quality-control checks, 26 patient scans were analyzed. Using self-motion perceptual thresholds from a matched healthy control group, 11 acute TBI patients were classified as having vestibular agnosia versus 15 with normal self-motion perception thresholds. Using independent component analysis on the rsfMRI data, we found altered functional connectivity in bilateral lingual gyrus and temporo-occipital fusiform cortex in the vestibular agnosia patients. Moreover, regions of interest analyses showed both inter-hemispheric and intra-hemispheric network disruption in vestibular agnosia. In conclusion, our results show that vestibular agnosia is mediated by bilateral anterior and posterior network dysfunction and reveal the distributed brain mechanisms mediating vestibular self-motion perception

Vestibular dysfunction in acute traumatic brain injury

Traumatic brain injury (TBI) is the commonest cause of disability in under-40-year-olds. Vestibular features of dizziness (illusory self-motion) or imbalance which affects 50% of TBI patients at 5 years, increases unemployment threefold in TBI survivors. Unfortunately, vestibular diagnoses are cryptogenic in 25% of chronic TBI cases, impeding therapy. We hypothesized that chronic adaptive brain mechanisms uncouple vestibular symptoms from signs. This predicts a masking of vestibular diagnoses chronically but not acutely. Hence, defining the spectrum of vestibular diagnoses in acute TBI should clarify vestibular diagnoses in chronic TBI. There are, however, no relevant acute TBI data. Of 111 Major Trauma Ward adult admissions screened (median 38-years-old), 96 patients (87%) had subjective dizziness (illusory self-motion) and/or objective imbalance were referred to the senior author (BMS). Symptoms included: feeling unbalanced (58%), headache (50%) and dizziness (40%). In the 47 cases assessed by BMS, gait ataxia was the commonest sign (62%) with half of these cases denying imbalance when asked. Diagnoses included BPPV (38%), acute peripheral unilateral vestibular loss (19%), and migraine phenotype headache (34%), another potential source of vestibular symptoms. In acute TBI, vestibular signs are common, with gait ataxia being the most frequent one. However, patients underreport symptoms. The uncoupling of symptoms from signs likely arises from TBI affecting perceptual mechanisms. Hence, the cryptogenic nature of vestibular symptoms in TBI (acute or chronic) relates to a complex interaction between injury (to peripheral and central vestibular structures and perceptual mechanisms) and brain-adaptation, emphasizing the need for acute prospective, mechanistic studies

The effectiveness, acceptability and cost-effectiveness of psychosocial interventions for maltreated children and adolescents: an evidence synthesis.

BACKGROUND: Child maltreatment is a substantial social problem that affects large numbers of children and young people in the UK, resulting in a range of significant short- and long-term psychosocial problems. OBJECTIVES: To synthesise evidence of the effectiveness, cost-effectiveness and acceptability of interventions addressing the adverse consequences of child maltreatment. STUDY DESIGN: For effectiveness, we included any controlled study. Other study designs were considered for economic decision modelling. For acceptability, we included any study that asked participants for their views. PARTICIPANTS: Children and young people up to 24 years 11 months, who had experienced maltreatment before the age of 17 years 11 months. INTERVENTIONS: Any psychosocial intervention provided in any setting aiming to address the consequences of maltreatment. MAIN OUTCOME MEASURES: Psychological distress [particularly post-traumatic stress disorder (PTSD), depression and anxiety, and self-harm], behaviour, social functioning, quality of life and acceptability. METHODS: Young Persons and Professional Advisory Groups guided the project, which was conducted in accordance with Cochrane Collaboration and NHS Centre for Reviews and Dissemination guidance. Departures from the published protocol were recorded and explained. Meta-analyses and cost-effectiveness analyses of available data were undertaken where possible. RESULTS: We identified 198 effectiveness studies (including 62 randomised trials); six economic evaluations (five using trial data and one decision-analytic model); and 73 studies investigating treatment acceptability. Pooled data on cognitive-behavioural therapy (CBT) for sexual abuse suggested post-treatment reductions in PTSD [standardised mean difference (SMD) -0.44 (95% CI -4.43 to -1.53)], depression [mean difference -2.83 (95% CI -4.53 to -1.13)] and anxiety [SMD -0.23 (95% CI -0.03 to -0.42)]. No differences were observed for post-treatment sexualised behaviour, externalising behaviour, behaviour management skills of parents, or parental support to the child. Findings from attachment-focused interventions suggested improvements in secure attachment [odds ratio 0.14 (95% CI 0.03 to 0.70)] and reductions in disorganised behaviour [SMD 0.23 (95% CI 0.13 to 0.42)], but no differences in avoidant attachment or externalising behaviour. Few studies addressed the role of caregivers, or the impact of the therapist-child relationship. Economic evaluations suffered methodological limitations and provided conflicting results. As a result, decision-analytic modelling was not possible, but cost-effectiveness analysis using effectiveness data from meta-analyses was undertaken for the most promising intervention: CBT for sexual abuse. Analyses of the cost-effectiveness of CBT were limited by the lack of cost data beyond the cost of CBT itself. CONCLUSIONS: It is not possible to draw firm conclusions about which interventions are effective for children with different maltreatment profiles, which are of no benefit or are harmful, and which factors encourage people to seek therapy, accept the offer of therapy and actively engage with therapy. Little is known about the cost-effectiveness of alternative interventions. LIMITATIONS: Studies were largely conducted outside the UK. The heterogeneity of outcomes and measures seriously impacted on the ability to conduct meta-analyses. FUTURE WORK: Studies are needed that assess the effectiveness of interventions within a UK context, which address the wider effects of maltreatment, as well as specific clinical outcomes. STUDY REGISTRATION: This study is registered as PROSPERO CRD42013003889. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

An eScience-Bayes strategy for analyzing omics data

<p>Abstract</p> <p>Background</p> <p>The omics fields promise to revolutionize our understanding of biology and biomedicine. However, their potential is compromised by the challenge to analyze the huge datasets produced. Analysis of omics data is plagued by the curse of dimensionality, resulting in imprecise estimates of model parameters and performance. Moreover, the integration of omics data with other data sources is difficult to shoehorn into classical statistical models. This has resulted in <it>ad hoc </it>approaches to address specific problems.</p> <p>Results</p> <p>We present a general approach to omics data analysis that alleviates these problems. By combining eScience and Bayesian methods, we retrieve scientific information and data from multiple sources and coherently incorporate them into large models. These models improve the accuracy of predictions and offer new insights into the underlying mechanisms. This "eScience-Bayes" approach is demonstrated in two proof-of-principle applications, one for breast cancer prognosis prediction from transcriptomic data and one for protein-protein interaction studies based on proteomic data.</p> <p>Conclusions</p> <p>Bayesian statistics provide the flexibility to tailor statistical models to the complex data structures in omics biology as well as permitting coherent integration of multiple data sources. However, Bayesian methods are in general computationally demanding and require specification of possibly thousands of prior distributions. eScience can help us overcome these difficulties. The eScience-Bayes thus approach permits us to fully leverage on the advantages of Bayesian methods, resulting in models with improved predictive performance that gives more information about the underlying biological system.</p

Modeling convergent ON and OFF pathways in the early visual system

For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron’s response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus–response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological “linear–nonlinear” (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron’s receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data