167 research outputs found

    The mPower Study, Parkinson Disease Mobile Data Collected Using Researchkit

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    Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease. Benefitting from large enrollment and repeated measurements on many individuals, these data may help establish baseline variability of real-world activity measurement collected via mobile phones, and ultimately may lead to quantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collection modules are available through an open source license for use in studies of other conditions. We hope that releasing data contributed by engaged research participants will seed a new community of analysts working collaboratively on understanding mobile health data to advance human health

    Expression profiling predicts outcome in breast cancer

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    Gruvberger et al. postulate, in their commentary [1] published in this issue of Breast Cancer Research, that our “prognostic gene set may not be broadly applicable to other breast tumor cohorts”, and they suggest that “it may be important to define prognostic expression profiles separately in estrogen receptor (ER) positive and negative tumors”. This is based on two observations derived from our gene expression profiling data in breast cancer [2]: the overlap between reporter genes for prognosis and ER status, and Gruvberger et al.’s inability to confirm the prognosis prediction using a nonoptimal selection of 58 of our 231 prognosis reporter genes. The overlap between our prognosis reporter genes and the ER status genes is certainly very large, mainly because ~10 % of all genes on our microarray contain informatio

    Comparison of the performance of photonic band-edge liquid crystal lasers using different dyes as the gain medium

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    The primary concern of this work is to study the emission characteristics of a series of chiral nematic liquid crystal lasers doped with different laser dyes (DCM, pyrromethene 580, and pyrromethene 597) at varying concentrations by weight (0.5-2 wt %) when optically pumped at 532 nm. Long-wavelength photonic band-edge laser emission is characterized in terms of threshold energy and slope efficiency. At every dye concentration investigated, the pyrromethene 597-doped lasers exhibit the highest slope efficiency (ranging from 15% to 32%) and the DCM-doped lasers the lowest (ranging from 5% to 13%). Similarly, the threshold was found to be, in general, higher for the DCM-doped laser samples in comparison to the pyrromethene-doped laser samples. These results are then compared with the spectral properties, quantum efficiencies and, where possible, fluorescence lifetimes of the dyes dispersed in a common nematic host. In accordance with the low thresholds and high slope efficiencies, the results show that the molar extinction coefficients and quantum efficiencies are considerably larger for the pyrromethene dyes in comparison to DCM, when dispersed in the liquid crystal host.open191
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