Changes in circle area after gravity compensation training in chronic stroke patients

After a stroke, many people experience difficulties to selectively activate muscles. As a result many patients move the affected arm in stereotypical patterns. Shoulder abduction is often accompanied by elbow flexion, reducing the ability to extend the elbow. This involuntary coupling reduces the patient's active range of motion. Gravity compensation reduces the activation level of shoulder abductors which limits the amount of coupled elbow flexion. As a result, stroke patients can instantaneously increase their active range of motion [1]. The objective of the present study is to examine whether training in a gravity compensated environment can also lead to an increased range of motion in an unsupported environment. Parts of this work have been presented at EMBC2009, Minneapolis, USA

Performance of Single Nucleotide Polymorphisms versus Haplotypes for Genome-Wide Association Analysis in Barley

Genome-wide association studies (GWAS) may benefit from utilizing haplotype information for making marker-phenotype associations. Several rationales for grouping single nucleotide polymorphisms (SNPs) into haplotype blocks exist, but any advantage may depend on such factors as genetic architecture of traits, patterns of linkage disequilibrium in the study population, and marker density. The objective of this study was to explore the utility of haplotypes for GWAS in barley (Hordeum vulgare) to offer a first detailed look at this approach for identifying agronomically important genes in crops. To accomplish this, we used genotype and phenotype data from the Barley Coordinated Agricultural Project and constructed haplotypes using three different methods. Marker-trait associations were tested by the efficient mixed-model association algorithm (EMMA). When QTL were simulated using single SNPs dropped from the marker dataset, a simple sliding window performed as well or better than single SNPs or the more sophisticated methods of blocking SNPs into haplotypes. Moreover, the haplotype analyses performed better 1) when QTL were simulated as polymorphisms that arose subsequent to marker variants, and 2) in analysis of empirical heading date data. These results demonstrate that the information content of haplotypes is dependent on the particular mutational and recombinational history of the QTL and nearby markers. Analysis of the empirical data also confirmed our intuition that the distribution of QTL alleles in nature is often unlike the distribution of marker variants, and hence utilizing haplotype information could capture associations that would elude single SNPs. We recommend routine use of both single SNP and haplotype markers for GWAS to take advantage of the full information content of the genotype data

Influence of gravity compensation training on synergistic movement patterns of the upper extremity after stroke, a pilot study

Background\ud \ud The majority of stroke patients have to cope with impaired arm function. Gravity compensation of the arm instantaneously affects abnormal synergistic movement patterns. The goal of the present study is to examine whether gravity compensated training improves unsupported arm function. \ud \ud Methods\ud \ud Seven chronic stroke patients received 18 half-hour sessions of gravity compensated reach training, in a period of six weeks. During training a motivating computer game was played. Before and after training arm function was assessed with the Fugl-Meyer assessment and a standardized, unsupported circle drawing task. Synergistic movement patterns were identified based on concurrent changes in shoulder elevation and elbow flexion/extension angles. \ud \ud Results\ud \ud Median increase of Fugl-Meyer scores was 3 points after training. The training led to significantly increased work area of the hemiparetic arm, as indicated by the normalized circle area. Roundness of the drawn circles and the occurrence of synergistic movement patterns remained similar after the training. \ud \ud Conclusions\ud \ud A decreased strength of involuntary coupling might contribute to the increased arm function after training. More research is needed to study working mechanisms involved in post stroke rehabilitation training. The used training setup is simple and affordable and is therefore suitable to use in clinical setting

Optimal Taylor–Couette flow: radius ratio dependence

Taylor–Couette flow with independently rotating inner (i) and outer (o) cylinders is explored numerically and experimentally to determine the effects of the radius ratio η on the system response. Numerical simulations reach Reynolds numbers of up to Rei=9.5×10^3 and Reo=5×10^3, corresponding to Taylor numbers of up to Ta=10^8 for four different radius ratios η=ri/ro between 0.5 and 0.909. The experiments, performed in the Twente Turbulent Taylor–Couette (T3C) set-up, reach Reynolds numbers of up to Rei=2×10^6 and Reo=1.5×10^6, corresponding to Ta=5×10^12 for η=0.714--0.909. Effective scaling laws for the torque Jω(Ta) are found, which for sufficiently large driving Ta are independent of the radius ratio η. As previously reported for η=0.714, optimum transport at a non-zero Rossby number Ro=ri|ωi−ωo|/[2(ro−ri)ωo] is found in both experiments and numerics. Here Roopt is found to depend on the radius ratio and the driving of the system. At a driving in the range between Ta∼3×10^8 and Ta∼10^10, Roopt saturates to an asymptotic η-dependent value. Theoretical predictions for the asymptotic value of Roopt are compared to the experimental results, and found to differ notably. Furthermore, the local angular velocity profiles from experiments and numerics are compared, and a link between a flat bulk profile and optimum transport for all radius ratios is reported

Effect of position feedback during task-oriented upper-limb training after stroke: Five-case pilot study

Feedback is an important element in motor learning during rehabilitation therapy following stroke. The objective of this pilot study was to better understand the effect of position feedback during task-oriented reach training of the upper limb in people with chronic stroke. Five subjects participated in the training for 30 minutes three times a week for 6 weeks. During training, subjects performed reaching movements over a predefined path. When deviation from this path occurred, shoulder and elbow joints received position feedback using restraining forces. We recorded the amount of position feedback used by each subject. During pre- and posttraining assessments, we collected data from clinical scales, isometric strength, and workspace of the arm. All subjects showed improvement on one or several kinematic variables during a circular motion task after training. One subject showed improvement on all clinical scales. Subjects required position feedback between 7.4% and 14.7% of training time. Although augmented feedback use was limited, kinematic outcome measures and movement performance during training increased in all subjects, which was comparable with other studies. Emphasis on movement errors at the moment they occur may possibly stimulate motor learning when movement tasks with sufficiently high levels of difficulty are applied

Inter-molecular structure factors of macromolecules in solution: integral equation results

The inter-molecular structure of semidilute polymer solutions is studied theoretically. The low density limit of a generalized Ornstein-Zernicke integral equation approach to polymeric liquids is considered. Scaling laws for the dilute-to-semidilute crossover of random phase (RPA) like structure are derived for the inter-molecular structure factor on large distances when inter-molecular excluded volume is incorporated at the microscopic level. This leads to a non-linear equation for the excluded volume interaction parameter. For macromolecular size-mass scaling exponents, $\nu$, above a spatial-dimension dependent value, $\nu_c=2/d$, mean field like density scaling is recovered, but for $\nu<\nu_c$ the density scaling becomes non-trivial in agreement with field theoretic results and justifying phenomenological extensions of RPA. The structure of the polymer mesh in semidilute solutions is discussed in detail and comparisons with large scale Monte Carlo simulations are added. Finally a new possibility to determine the correction to scaling exponent $\omega_{12}$ is suggested.Comment: 11 pages, 5 figures; to be published in Phys. Rev. E (1999

New Method for Phase transitions in diblock copolymers: The Lamellar case

A new mean-field type theory is proposed to study order-disorder transitions (ODT) in block copolymers. The theory applies to both the weak segregation (WS) and the strong segregation (SS) regimes. A new energy functional is proposed without appealing to the random phase approximation (RPA). We find new terms unaccounted for within RPA. We work out in detail transitions to the lamellar state and compare the method to other existing theories of ODT and numerical simulations. We find good agreements with recent experimental results and predict that the intermediate segregation regime may have more than one scaling behavior.Comment: 23 pages, 8 figure

Selective Phenotyping, Entropy Reduction, and the Mastermind game

<p>Abstract</p> <p>Background</p> <p>With the advance of genome sequencing technologies, phenotyping, rather than genotyping, is becoming the most expensive task when mapping genetic traits. The need for efficient selective phenotyping strategies, <it>i</it>.<it>e</it>. methods to select a subset of genotyped individuals for phenotyping, therefore increases. Current methods have focused either on improving the detection of causative genetic variants or their precise genomic location separately.</p> <p>Results</p> <p>Here we recognize selective phenotyping as a Bayesian model discrimination problem and introduce SPARE (Selective Phenotyping Approach by Reduction of Entropy). Unlike previous methods, SPARE can integrate the information of previously phenotyped individuals, thereby enabling an efficient incremental strategy. The effective performance of SPARE is demonstrated on simulated data as well as on an experimental yeast dataset.</p> <p>Conclusions</p> <p>Using entropy reduction as an objective criterion gives a natural way to tackle both issues of detection and localization simultaneously and to integrate intermediate phenotypic data. We foresee entropy-based strategies as a fruitful research direction for selective phenotyping.</p

Extension of the bayesian alphabet for genomic selection

<p>Abstract</p> <p>Background</p> <p>Two Bayesian methods, BayesC<it>π </it>and BayesD<it>π</it>, were developed for genomic prediction to address the drawback of BayesA and BayesB regarding the impact of prior hyperparameters and treat the prior probability <it>π </it>that a SNP has zero effect as unknown. The methods were compared in terms of inference of the number of QTL and accuracy of genomic estimated breeding values (GEBVs), using simulated scenarios and real data from North American Holstein bulls.</p> <p>Results</p> <p>Estimates of <it>π </it>from BayesC<it>π</it>, in contrast to BayesD<it>π</it>, were sensitive to the number of simulated QTL and training data size, and provide information about genetic architecture. Milk yield and fat yield have QTL with larger effects than protein yield and somatic cell score. The drawback of BayesA and BayesB did not impair the accuracy of GEBVs. Accuracies of alternative Bayesian methods were similar. BayesA was a good choice for GEBV with the real data. Computing time was shorter for BayesC<it>π </it>than for BayesD<it>π</it>, and longest for our implementation of BayesA.</p> <p>Conclusions</p> <p>Collectively, accounting for computing effort, uncertainty as to the number of QTL (which affects the GEBV accuracy of alternative methods), and fundamental interest in the number of QTL underlying quantitative traits, we believe that BayesC<it>π </it>has merit for routine applications.</p