Movement variability in stroke patients and controls performing two upper limb functional tasks: a new assessment methodology

Background: In the evaluation of upper limb impairment post stroke there remains a gap between detailed kinematic analyses with expensive motion capturing systems and common clinical assessment tests. In particular, although many clinical tests evaluate the performance of functional tasks, metrics to characterise upper limb kinematics are generally not applicable to such tasks and very limited in scope. This paper reports on a novel, user-friendly methodology that allows for the assessment of both signal magnitude and timing variability in upper limb movement trajectories during functional task performance. In order to demonstrate the technique, we report on a study in which the variability in timing and signal magnitude of data collected during the performance of two functional tasks is compared between a group of subjects with stroke and a group of individually matched control subjects. Methods: We employ dynamic time warping for curve registration to quantify two aspects of movement variability: 1) variability of the timing of the accelerometer signals' characteristics and 2) variability of the signals' magnitude. Six stroke patients and six matched controls performed several trials of a unilateral ('drinking') and a bilateral ('moving a plate') functional task on two different days, approximately 1 month apart. Group differences for the two variability metrics were investigated on both days. Results: For 'drinking from a glass' significant group differences were obtained on both days for the timing variability of the acceleration signals' characteristics (p = 0.002 and p = 0.008 for test and retest, respectively); all stroke patients showed increased signal timing variability as compared to their corresponding control subject. 'Moving a plate' provided less distinct group differences. Conclusion: This initial application establishes that movement variability metrics, as determined by our methodology, appear different in stroke patients as compared to matched controls during unilateral task performance ('drinking'). Use of a user-friendly, inexpensive accelerometer makes this methodology feasible for routine clinical evaluations. We are encouraged to perform larger studies to further investigate the metrics' usefulness when quantifying levels of impairment

Tripartite Relationship Among Synaptic, Amyloid, and Tau Proteins: An In Vivo and Postmortem Study

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Evanescent light-matter Interactions in Atomic Cladding Wave Guides

Alkali vapors, and in particular rubidium, are being used extensively in several important fields of research such as slow and stored light non-linear optics3 and quantum computation. Additionally, the technology of alkali vapors plays a major role in realizing myriad industrial applications including for example atomic clocks magentometers8 and optical frequency stabilization. Lately, there is a growing effort towards miniaturizing traditional centimeter-size alkali vapor cells. Owing to the significant reduction in device dimensions, light matter interactions are greatly enhanced, enabling new functionalities due to the low power threshold needed for non-linear interactions. Here, taking advantage of the mature Complimentary Metal-Oxide-Semiconductor (CMOS) compatible platform of silicon photonics, we construct an efficient and flexible platform for tailored light vapor interactions on a chip. Specifically, we demonstrate light matter interactions in an atomic cladding wave guide (ACWG), consisting of CMOS compatible silicon nitride nano wave-guide core with a Rubidium (Rb) vapor cladding. We observe the highly efficient interaction of the electromagnetic guided mode with the thermal Rb cladding. The nature of such interactions is explained by a model which predicts the transmission spectrum of the system taking into account Doppler and transit time broadening. We show, that due to the high confinement of the optical mode (with a mode area of 0.3{\lambda}2), the Rb absorption saturates at powers in the nW regime.Comment: 10 Pages 4 Figures. 1 Supplementar

Is albumin gradient or fluid to serum albumin ratio better than the pleural fluid lactate dehydroginase in the diagnostic of separation of pleural effusion?

BACKGROUND: To determine the accuracy of serum-effusion albumin gradient (SEAG) and pleural fluid to serum albumin ratio (ALBR) in the diagnostic separation of pleural effusion into transudate and exudate and to compare SEAG and ALBR with pleural fluid LDH (FLDH) the most widely used test. METHODS: Data collected from 200 consecutive patients with a known cause of pleural effusion in a United Kingdom district general hospital. RESULTS: The median and inter quartile ranges (IQR) for SEAG 93.5 (33.8 to 122.5) g/dl, ALBR 0.49 (0.42 to 0.62) and FLDH 98.5 IU/L(76.8 to 127.5) in transudates were significantly lower than the corresponding values for exudates 308.5 (171 to 692), 0.77 (0.63 to 0.85), 344 (216 to 695) all p < 0.0001. The Area Under the Curve (AUC) with 95% confidence intervals (Cl) for SEAG, ALBR and FLDH were 0.81 (0.75 to 0.87), 0.79 (0.72 to 0.86) and 0.9 (0.87 to 0.96) respectively. The positive likelihood ratios with 95%CI for FLDH, SEAG, and ALBR were: 7.3(3.5–17), 6.3(3–15) 6.2(3–14) respectively. There was a significant negative correlation between SEAG and ALBR (r= -0.89, p < 0.0001). CONCLUSION: The discriminative value for SEAG and ALBR appears to be similar in the diagnostic separation of transudates and exudates. FLDH is a superior test compared to SEAG and ALBR

A network perspective on the topological importance of enzymes and their phylogenetic conservation

<p>Abstract</p> <p>Background</p> <p>A metabolic network is the sum of all chemical transformations or reactions in the cell, with the metabolites being interconnected by enzyme-catalyzed reactions. Many enzymes exist in numerous species while others occur only in a few. We ask if there are relationships between the phylogenetic profile of an enzyme, or the number of different bacterial species that contain it, and its topological importance in the metabolic network. Our null hypothesis is that phylogenetic profile is independent of topological importance. To test our null hypothesis we constructed an enzyme network from the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. We calculated three network indices of topological importance: the degree or the number of connections of a network node; closeness centrality, which measures how close a node is to others; and betweenness centrality measuring how frequently a node appears on all shortest paths between two other nodes.</p> <p>Results</p> <p>Enzyme phylogenetic profile correlates best with betweenness centrality and also quite closely with degree, but poorly with closeness centrality. Both betweenness and closeness centralities are non-local measures of topological importance and it is intriguing that they have contrasting power of predicting phylogenetic profile in bacterial species. We speculate that redundancy in an enzyme network may be reflected by betweenness centrality but not by closeness centrality. We also discuss factors influencing the correlation between phylogenetic profile and topological importance.</p> <p>Conclusion</p> <p>Our analysis falsifies the hypothesis that phylogenetic profile of enzymes is independent of enzyme network importance. Our results show that phylogenetic profile correlates better with degree and betweenness centrality, but less so with closeness centrality. Enzymes that occur in many bacterial species tend to be those that have high network importance. We speculate that this phenomenon originates in mechanisms driving network evolution. Closeness centrality reflects phylogenetic profile poorly. This is because metabolic networks often consist of distinct functional modules and some are not in the centre of the network. Enzymes in these peripheral parts of a network might be important for cell survival and should therefore occur in many bacterial species. They are, however, distant from other enzymes in the same network.</p