Racial differences in neurocognitive outcomes post-stroke: The impact of healthcare variables

AbstractObjectives:The present study examined differences in neurocognitive outcomes among non-Hispanic Black and White stroke survivors using the NIH Toolbox-Cognition Battery (NIHTB-CB), and investigated the roles of healthcare variables in explaining racial differences in neurocognitive outcomes post-stroke.Methods:One-hundred seventy adults (91 Black; 79 White), who participated in a multisite study were included (age:M=56.4;SD=12.6; education:M=13.7;SD=2.5; 50% male; years post-stroke: 1–18; stroke type: 72% ischemic, 28% hemorrhagic). Neurocognitive function was assessed with the NIHTB-CB, using demographically corrected norms. Participants completed measures of socio-demographic characteristics, health literacy, and healthcare use and access. Stroke severity was assessed with the Modified Rankin Scale.Results:An independent samplesttest indicated Blacks showed more neurocognitive impairment (NIHTB-CB Fluid Composite T-score:M=37.63;SD=11.67) than Whites (Fluid T-score:M=42.59,SD=11.54;p=.006). This difference remained significant after adjusting for reading level (NIHTB-CB Oral Reading), and when stratified by stroke severity. Blacks also scored lower on health literacy, reported differences in insurance type, and reported decreased confidence in the doctors treating them. Multivariable models adjusting for reading level and injury severity showed that health literacy and insurance type were statistically significant predictors of the Fluid cognitive composite (p&lt;.001 andp=.02, respectively) and significantly mediated racial differences on neurocognitive impairment.Conclusions:We replicated prior work showing that Blacks are at increased risk for poorer neurocognitive outcomes post-stroke than Whites. Health literacy and insurance type might be important modifiable factors influencing these differences. (JINS, 2017,23, 640–652)</jats:p

Dynamics near the Surface Reconstruction of W(100)

Using Brownian molecular dynamics simulation, we study the surface dynamics near the reconstruction transition of W(100) via a model Hamiltonian. Results for the softening and broadening of the surface phonon spectrum near the transition are compared with previous calculations and with He atom scattering data. From the critical behavior of the central peak in the dynamical structure factor, we also estimate the exponent of the power law anomaly for adatom diffusion near the transition temperature.Comment: 8 pages, 8 figures, to appear in Phys. Rev.

Anthropogenic Space Weather

Anthropogenic effects on the space environment started in the late 19th century and reached their peak in the 1960s when high-altitude nuclear explosions were carried out by the USA and the Soviet Union. These explosions created artificial radiation belts near Earth that resulted in major damages to several satellites. Another, unexpected impact of the high-altitude nuclear tests was the electromagnetic pulse (EMP) that can have devastating effects over a large geographic area (as large as the continental United States). Other anthropogenic impacts on the space environment include chemical release ex- periments, high-frequency wave heating of the ionosphere and the interaction of VLF waves with the radiation belts. This paper reviews the fundamental physical process behind these phenomena and discusses the observations of their impacts.Comment: 71 pages, 35 figure

From Lurker to Active Participant

The original publication is available from www.springerlink.com. Sloep, P. B., & Kester, L. (2009). From Lurker to Active Participant. In R. Koper (Ed)., Learning Network Services for Professional Development (pp. 17-26). Berlin, Germany: Springer Verlag.In this chapter we will specifically go into the question of how prospective Learning Network users may be convinced of these benefits, for that is likely to be the necessary condition for their active participation in any Learning Network. Their question would be ‘Why should I participate?’, this chapter inventories an-swers to that question, which are then translated into a few guidelines for those contemplating to set up a particular, topic-bound Learning Network. Two kinds of answer are distinguished. Proximate answers, which affect the decision to partici-pate here and now; and ultimate answers, which motivate participation, but only in the long run, after the decision to participate has already been taken. Both are im-portant, the former to persuade people to participate, the latter to persuade people to keep participating. Before going into them, we’ll introduce a concrete example to add some realism to the discussion.The work on this publication has been sponsored in part by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

1D Frustrated Ferromagnetic Model with Added Dzyaloshinskii-Moriya Interaction

The one-dimensional (1D) isotropic frustrated ferromagnetic spin-1/2 model is considered. Classical and quantum effects of adding a Dzyaloshinskii-Moriya (DM) interaction on the ground state of the system is studied using the analytical cluster method and numerical Lanczos technique. Cluster method results, show that the classical ground state magnetic phase diagram consists of only one single phase: "chiral". The quantum corrections are determined by means of the Lanczos method and a rich quantum phase diagram including the gapless Luttinger liquid, the gapped chiral and dimer orders is obtained. Moreover, next nearest neighbors will be entangled by increasing DM interaction and for open chains, end-spins are entangled which shows the long distance entanglement (LDE) feature that can be controlled by DM interaction.Comment: 8 pages, 9 figure

Asymptotic Expansions for Stationary Distributions of Perturbed Semi-Markov Processes

New algorithms for computing of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes are presented. The algorithms are based on special techniques of sequential phase space reduction, which can be applied to processes with asymptotically coupled and uncoupled finite phase spaces.Comment: 83 page

Cosmological parameters from SDSS and WMAP

We measure cosmological parameters using the three-dimensional power spectrum P(k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a ``vanilla'' flat adiabatic Lambda-CDM model without tilt (n=1), running tilt, tensor modes or massive neutrinos. Adding SDSS information more than halves the WMAP-only error bars on some parameters, tightening 1 sigma constraints on the Hubble parameter from h~0.74+0.18-0.07 to h~0.70+0.04-0.03, on the matter density from Omega_m~0.25+/-0.10 to Omega_m~0.30+/-0.04 (1 sigma) and on neutrino masses from <11 eV to <0.6 eV (95%). SDSS helps even more when dropping prior assumptions about curvature, neutrinos, tensor modes and the equation of state. Our results are in substantial agreement with the joint analysis of WMAP and the 2dF Galaxy Redshift Survey, which is an impressive consistency check with independent redshift survey data and analysis techniques. In this paper, we place particular emphasis on clarifying the physical origin of the constraints, i.e., what we do and do not know when using different data sets and prior assumptions. For instance, dropping the assumption that space is perfectly flat, the WMAP-only constraint on the measured age of the Universe tightens from t0~16.3+2.3-1.8 Gyr to t0~14.1+1.0-0.9 Gyr by adding SDSS and SN Ia data. Including tensors, running tilt, neutrino mass and equation of state in the list of free parameters, many constraints are still quite weak, but future cosmological measurements from SDSS and other sources should allow these to be substantially tightened.Comment: Minor revisions to match accepted PRD version. SDSS data and ppt figures available at http://www.hep.upenn.edu/~max/sdsspars.htm

Aquatic therapy for children with Duchenne muscular dystrophy: a pilot feasibility randomised controlled trial and mixed-methods process evaluation.

BACKGROUND: Duchenne muscular dystrophy (DMD) is a rare disease that causes the progressive loss of motor abilities such as walking. Standard treatment includes physiotherapy. No trial has evaluated whether or not adding aquatic therapy (AT) to land-based therapy (LBT) exercises helps to keep muscles strong and children independent. OBJECTIVES: To assess the feasibility of recruiting boys with DMD to a randomised trial evaluating AT (primary objective) and to collect data from them; to assess how, and how well, the intervention and trial procedures work. DESIGN: Parallel-group, single-blind, randomised pilot trial with nested qualitative research. SETTING: Six paediatric neuromuscular units. PARTICIPANTS: Children with DMD aged 7-16 years, established on corticosteroids, with a North Star Ambulatory Assessment (NSAA) score of 8-34 and able to complete a 10-m walk without aids/assistance. Exclusions: > 20% variation between baseline screens 4 weeks apart and contraindications. INTERVENTIONS: Participants were allocated on a 1 : 1 ratio to (1) optimised, manualised LBT (prescribed by specialist neuromuscular physiotherapists) or (2) the same plus manualised AT (30 minutes, twice weekly for 6 months: active assisted and/or passive stretching regime; simulated or real functional activities; submaximal exercise). Semistructured interviews with participants, parents (n = 8) and professionals (n = 8) were analysed using Framework analysis. An independent rater reviewed patient records to determine the extent to which treatment was optimised. A cost-impact analysis was performed. Quantitative and qualitative data were mixed using a triangulation exercise. MAIN OUTCOME MEASURES: Feasibility of recruiting 40 participants in 6 months, participant and therapist views on the acceptability of the intervention and research protocols, clinical outcomes including NSAA, independent assessment of treatment optimisation and intervention costs. RESULTS: Over 6 months, 348 children were screened - most lived too far from centres or were enrolled in other trials. Twelve (30% of target) were randomised to AT (n = 8) or control (n = 4). People in the AT (n = 8) and control (n = 2: attrition because of parental report) arms contributed outcome data. The mean change in NSAA score at 6 months was -5.5 [standard deviation (SD) 7.8] for LBT and -2.8 (SD 4.1) in the AT arm. One boy suffered pain and fatigue after AT, which resolved the same day. Physiotherapists and parents valued AT and believed that it should be delivered in community settings. The independent rater considered AT optimised for three out of eight children, with other children given programmes that were too extensive and insufficiently focused. The estimated NHS costs of 6-month service were between £1970 and £2734 per patient. LIMITATIONS: The focus on delivery in hospitals limits generalisability. CONCLUSIONS: Neither a full-scale frequentist randomised controlled trial (RCT) recruiting in the UK alone nor a twice-weekly open-ended AT course delivered at tertiary centres is feasible. Further intervention development research is needed to identify how community-based pools can be accessed, and how families can link with each other and community physiotherapists to access tailored AT programmes guided by highly specialised physiotherapists. Bayesian RCTs may be feasible; otherwise, time series designs are recommended. TRIAL REGISTRATION: Current Controlled Trials ISRCTN41002956. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 27. See the NIHR Journals Library website for further project information

Clinical and molecular characterisation of KCNT1-related severe early onset epilepsy

Objective: To characterise the phenotypic spectrum, molecular genetic findings and functional consequences of pathogenic variants in early onset KCNT1-epilepsy. Methods: We identified a cohort of 31 patients with epilepsy of infancy with migrating focal seizures (EIMFS) and screened for variants in KCNT1 using direct Sanger sequencing, a multiple gene next generation sequencing panel and whole exome sequencing. Additional patients with non-EIMFS early onset epilepsy in whom we identified KCNT1 variants on local diagnostic multiple gene panel testing were also included. Where possible, we performed homology modelling to predict putative effects of variants on protein structure and function. We undertook electrophysiological assessment of mutant KCNT1 channels in a Xenopus oocyte model system. Results: We identified pathogenic variants in KCNT1 in 12 patients, four of which are novel. Most variants occurred de novo. Ten had a clinical diagnosis of EIMFS and the other two presented with early onset severe nocturnal frontal lobe seizures. Three patients had a trial of quinidine with good clinical response in one. Computational modelling analysis implicates abnormal pore function (F346L) and impaired tetramer formation (F502V) as putative disease mechanisms. All evaluated KCNT1 variants resulted in marked gain-of-function, with significantly increased channel amplitude and variable blockade by quinidine. Conclusions: Gain-of-function KCNT1 pathogenic variants cause a spectrum of severe focal epilepsies with onset in early infancy. Currently, genotype-phenotype correlations are unclear, though clinical outcome is poor for the majority of cases. Further elucidation of disease mechanisms may facilitate the development of targeted treatments, much needed for this pharmacoresistant genetic epilepsy

Principles of Bioimage Informatics: Focus on Machine Learning of Cell Patterns

Abstract. The field of bioimage informatics concerns the development and use of methods for computational analysis of biological images. Traditionally, analysis of such images has been done manually. Manual annotation is, however, slow, expensive, and often highly variable from one expert to another. Furthermore, with modern automated microscopes, hundreds to thousands of images can be collected per hour, making manual analysis infeasible. This field borrows from the pattern recognition and computer vision literature (which contain many techniques for image processing and recognition), but has its own unique challenges and tradeoffs. Fluorescence microscopy images represent perhaps the largest class of biological images for which automation is needed. For this modality, typical problems include cell segmentation, classification of phenotypical response, or decisions regarding differentiated responses (treatment vs. control setting). This overview focuses on the problem of subcellular location determination as a running example, but the techniques discussed are often applicable to other problems.