76 research outputs found

    Telerehabilitation Policy Report: Interprofessional Policy Principles and Priorities

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    The American Occupational Therapy Association, the American Physical Therapy Association, the American Speech-Language-Hearing Association and the American Telemedicine Association are collaborating to advance telehealth and ensure sustainability of virtual care services beyond the COVID-19 pandemic. These professional associations represent the interests of more than 888,000 rehabilitation services professionals. This paper summarizes the current state of telehealth policy principles and priorities for rehabilitation services. The report outlines key considerations when advocating with policymakers to avoid the “Telehealth Cliff” for audiology and therapy services and to facilitate the continued advancement of telehealth innovation and transformation by rehabilitation services professionals

    A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz

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    We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17

    Molecular Signatures Reveal Circadian Clocks May Orchestrate the Homeorhetic Response to Lactation

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    Genes associated with lactation evolved more slowly than other genes in the mammalian genome. Higher conservation of milk and mammary genes suggest that species variation in milk composition is due in part to the environment and that we must look deeper into the genome for regulation of lactation. At the onset of lactation, metabolic changes are coordinated among multiple tissues through the endocrine system to accommodate the increased demand for nutrients and energy while allowing the animal to remain in homeostasis. This process is known as homeorhesis. Homeorhetic adaptation to lactation has been extensively described; however how these adaptations are orchestrated among multiple tissues remains elusive. To develop a clearer picture of how gene expression is coordinated across multiple tissues during the pregnancy to lactation transition, total RNA was isolated from mammary, liver and adipose tissues collected from rat dams (n = 5) on day 20 of pregnancy and day 1 of lactation, and gene expression was measured using Affymetrix GeneChips. Two types of gene expression analysis were performed. Genes that were differentially expressed between days within a tissue were identified with linear regression, and univariate regression was used to identify genes commonly up-regulated and down-regulated across all tissues. Gene set enrichment analysis showed genes commonly up regulated among the three tissues enriched gene ontologies primary metabolic processes, macromolecular complex assembly and negative regulation of apoptosis ontologies. Genes enriched in transcription regulator activity showed the common up regulation of 2 core molecular clock genes, ARNTL and CLOCK. Commonly down regulated genes enriched Rhythmic process and included: NR1D1, DBP, BHLHB2, OPN4, and HTR7, which regulate intracellular circadian rhythms. Changes in mammary, liver and adipose transcriptomes at the onset of lactation illustrate the complexity of homeorhetic adaptations and suggest that these changes are coordinated through molecular clocks

    Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

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    Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

    The genetic architecture of type 2 diabetes

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    The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

    The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

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    The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society
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