4,987 research outputs found

    Toward understanding ambulatory activity decline in Parkinson disease

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    BACKGROUND: Declining ambulatory activity represents an important facet of disablement in Parkinson disease (PD). OBJECTIVE: The primary study aim was to compare the 2-year trajectory of ambulatory activity decline with concurrently evolving facets of disability in a small cohort of people with PD. The secondary aim was to identify baseline variables associated with ambulatory activity at 1- and 2-year follow-up assessments. DESIGN: This was a prospective, longitudinal cohort study. METHODS: Seventeen people with PD (Hoehn and Yahr stages 1-3) were recruited from 2 outpatient settings. Ambulatory activity data were collected at baseline and at 1- and 2-year annual assessments. Motor, mood, balance, gait, upper extremity function, quality of life, self-efficacy, and levodopa equivalent daily dose data and data on activities of daily living also were collected. RESULTS: Participants displayed significant 1- and 2-year declines in the amount and intensity of ambulatory activity concurrently with increasing levodopa equivalent daily dose. Worsening motor symptoms and slowing of gait were apparent only after 2 years. Concurrent changes in the remaining clinical variables were not observed. Baseline ambulatory activity and physical performance variables had the strongest relationships with 1- and 2-year mean daily steps. LIMITATIONS: The sample was small and homogeneous. CONCLUSIONS: Future research that combines ambulatory activity monitoring with a broader and more balanced array of measures would further illuminate the dynamic interactions among evolving facets of disablement and help determine the extent to which sustained patterns of recommended daily physical activity might slow the rate of disablement in PD.This study was funded primarily by the Davis Phinney Foundation and the Parkinson Disease Foundation. Additional funding was provided by Boston University Building Interdisciplinary Research Careers in Women's Health (K12 HD043444), the National Institutes of Health (R01NS077959), the Utah Chapter of the American Parkinson Disease Association (APDA), the Greater St Louis Chapter of the APDA, and the APDA Center for Advanced PD Research at Washington University. (Davis Phinney Foundation; Parkinson Disease Foundation; K12 HD043444 - Boston University Building Interdisciplinary Research Careers in Women's Health; R01NS077959 - National Institutes of Health; Utah Chapter of the American Parkinson Disease Association (APDA); Greater St Louis Chapter of the APDA; APDA Center for Advanced PD Research at Washington University

    Balance differences in people with Parkinson disease with and without freezing of gait

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    Published in final edited form as: Gait Posture. 2015 September ; 42(3): 306–309. doi:10.1016/j.gaitpost.2015.06.007.BACKGROUND: Freezing of gait (FOG) is a relatively common and remarkably disabling impairment associated with Parkinson disease (PD). Laboratory-based measures indicate that individuals with FOG (PD+FOG) have greater balance deficits than those without FOG (PD-FOG). Whether such differences also can be detected using clinical balance tests has not been investigated. We sought to determine if balance and specific aspects of balance, measured using Balance Evaluation Systems Test (BESTest), differs between PD+FOG and PD-FOG. Furthermore, we aimed to determine if time-efficient clinical balance measures (i.e. Mini-BESTest, Berg Balance Scale (BBS)) could detect balance differences between PD+FOG and PD-FOG. METHODS: Balance of 78 individuals with PD, grouped as either PD+FOG (n=32) or PD-FOG (n=46), was measured using the BESTest, Mini-BESTest, and BBS. Between-groups comparisons were conducted for these measures and for the six sections of the BESTest using analysis of covariance. A PD composite score was used as a covariate. RESULTS: Controlling for motor sign severity, PD duration, and age, PD+FOG had worse balance than PD-FOG when measured using the BESTest (p=0.008, F=7.35) and Mini-BESTest (p=0.002, F=10.37), but not the BBS (p=0.27, F=1.26). BESTest section differences were noted between PD+FOG and PD-FOG for reactive postural responses (p<0.001, F=14.42) and stability in gait (p=0.003, F=9.18). CONCLUSIONS: The BESTest and Mini-BESTest, which specifically assessed reactive postural responses and stability in gait, were more likely than the BBS to detect differences in balance between PD+FOG and PD-FOG. Because it is more time efficient to administer, the Mini-BESTest may be the preferred tool for assessing balance deficits associated with FOG.This study was conducted with funding from the Davis Phinney Foundation, Parkinson's Disease Foundation, NIH R01 NS077959, NIH UL1 TR000448, Greater St. Louis American Parkinson Disease Association (APDA), APDA Center for Advanced PD Research at Washington University in St. Louis. The funding sources had no role in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication. (Davis Phinney Foundation; Parkinson's Disease Foundation; R01 NS077959 - NIH; UL1 TR000448 - NIH; Greater St. Louis American Parkinson Disease Association (APDA); APDA Center for Advanced PD Research at Washington University in St. Louis

    Two-year trajectory of fall risk in people with Parkinson disease: a latent class analysis

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    Published in final edited form as: Arch Phys Med Rehabil. 2016 March ; 97(3): 372–379.e1. doi:10.1016/j.apmr.2015.10.105.OBJECTIVE: To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD). DESIGN: Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories. SETTING: Assessments were conducted at 1 of 4 universities. PARTICIPANTS: Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. RESULTS: The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. CONCLUSIONS: Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD.Supported by the Davis Phinney Foundation, the Parkinson's Disease Foundation, National Institutes of Health (NIH) (grant nos. NIH R01 NS077959 and NIH UL1 TR000448), the Massachusetts and Utah Chapters of the American Parkinson Disease Association (APDA), the Greater St Louis Chapter of the APDA, and the APDA Center for Advanced Research at Washington University. (Davis Phinney Foundation; Parkinson's Disease Foundation; NIH R01 NS077959 - National Institutes of Health (NIH); NIH UL1 TR000448 - National Institutes of Health (NIH); Utah Chapter of the American Parkinson Disease Association (APDA); Greater St Louis Chapter of the APDA; APDA Center for Advanced Research at Washington University; Massachusetts Chapter of the American Parkinson Disease Association (APDA)

    Are the average gait speeds during the 10 meter and 6 minute walk tests redundant in Parkinson disease?

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    Published in final edited form as: Gait Posture. 2017 February ; 52: 178–182. doi:10.1016/j.gaitpost.2016.11.033.We investigated the relationships between average gait speed collected with the 10Meter Walk Test (Comfortable and Fast) and 6Minute Walk Test (6MWT) in 346 people with Parkinson disease (PD) and how the relationships change with increasing disease severity. Pearson correlation and linear regression analyses determined relationships between 10Meter Walk Test and 6MWT gait speed values for the entire sample and for sub-samples stratified by Hoehn & Yahr (H&Y) stage I (n=53), II (n=141), III (n=135) and IV (n=17). We hypothesized that redundant tests would be highly and significantly correlated (i.e. r>0.70, p<0.05) and would have a linear regression model slope of 1 and intercept of 0. For the entire sample, 6MWT gait speed was significantly (p<0.001) related to the Comfortable 10 Meter Walk Test (r=0.75) and Fast 10Meter Walk Test (r=0.79) gait speed, with 56% and 62% of the variance in 6MWT gait speed explained, respectively. The regression model of 6MWT gait speed predicted by Comfortable 10 Meter Walk gait speed produced slope and intercept values near 1 and 0, respectively, especially for participants in H&Y stages II-IV. In contrast, slope and intercept values were further from 1 and 0, respectively, for the Fast 10Meter Walk Test. Comfortable 10 Meter Walk Test and 6MWT gait speeds appeared to be redundant in people with moderate to severe PD, suggesting the Comfortable 10 Meter Walk Test can be used to estimate 6MWT distance in this population.This study was funded by the Davis Phinney Foundation, the Parkinson's Disease Foundation, and the National Institutes of Health (R01 NS077959, K12 HD055931, UL1 TR000448). The funding sources had no input related to study design, data collection, or decision to submit for publication. (Davis Phinney Foundation; Parkinson's Disease Foundation; R01 NS077959 - National Institutes of Health; K12 HD055931 - National Institutes of Health; UL1 TR000448 - National Institutes of Health

    Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas)

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    © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Houskeeper, H. F., Rosenthal, I. S., Cavanaugh, K. C., Pawlak, C., Trouille, L., Byrnes, J. E. K., Bell, T. W., & Cavanaugh, K. C. Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas). Plos One, 17(1), (2022): e0257933, https://doi.org/10.1371/journal.pone.0257933.Giant kelp populations that support productive and diverse coastal ecosystems at temperate and subpolar latitudes of both hemispheres are vulnerable to changing climate conditions as well as direct human impacts. Observations of giant kelp forests are spatially and temporally uneven, with disproportionate coverage in the northern hemisphere, despite the size and comparable density of southern hemisphere kelp forests. Satellite imagery enables the mapping of existing and historical giant kelp populations in understudied regions, but automating the detection of giant kelp using satellite imagery requires approaches that are robust to the optical complexity of the shallow, nearshore environment. We present and compare two approaches for automating the detection of giant kelp in satellite datasets: one based on crowd sourcing of satellite imagery classifications and another based on a decision tree paired with a spectral unmixing algorithm (automated using Google Earth Engine). Both approaches are applied to satellite imagery (Landsat) of the Falkland Islands or Islas Malvinas (FLK), an archipelago in the southern Atlantic Ocean that supports expansive giant kelp ecosystems. The performance of each method is evaluated by comparing the automated classifications with a subset of expert-annotated imagery (8 images spanning the majority of our continuous timeseries, cumulatively covering over 2,700 km of coastline, and including all relevant sensors). Using the remote sensing approaches evaluated herein, we present the first continuous timeseries of giant kelp observations in the FLK region using Landsat imagery spanning over three decades. We do not detect evidence of long-term change in the FLK region, although we observe a recent decline in total canopy area from 2017–2021. Using a nitrate model based on nearby ocean state measurements obtained from ships and incorporating satellite sea surface temperature products, we find that the area of giant kelp forests in the FLK region is positively correlated with the nitrate content observed during the prior year. Our results indicate that giant kelp classifications using citizen science are approximately consistent with classifications based on a state-of-the-art automated spectral approach. Despite differences in accuracy and sensitivity, both approaches find high interannual variability that impedes the detection of potential long-term changes in giant kelp canopy area, although recent canopy area declines are notable and should continue to be monitored carefully.This work was funded by the National Aeronautics and Space Administration as part of the Citizen Science for Earth Systems Program (https://earthdata.nasa.gov/esds/competitive-programs/csesp) with grant #80NSSC18M0103 (awarded to JEKB), which also provided salary to HFH, and by the National Science Foundation through the Santa Barbara Coastal Long-Term Environmental Research (https://sbclter.msi.ucsb.edu) program with grants #OCE 0620276 and 1232779. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Oceanographic connectivity explains the intra-specific diversity of mangrove forests at global scales

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    The distribution of mangrove intra-specific biodiversity can be structured by historical demographic processes that enhance or limit effective population sizes. Oceanographic connectivity (OC) may further structure intra-specific biodiversity by preserving or diluting the genetic signatures of historical changes. Despite its relevance for biogeography and evolution, the role of oceanographic connectivity in structuring the distribution of mangrove’s genetic diversity has not been addressed at global scale. Here we ask whether connectivity mediated by ocean currents explains the intra-specific diversity of mangroves. A comprehensive dataset of population genetic differentiation was compiled from the literature. Multigenerational connectivity and population centrality indices were estimated with biophysical modeling coupled with network analyses. The variability explained in genetic differentiation was tested with competitive regression models built upon classical isolation-by-distance (IBD) models considering geographic distance. We show that oceanographic connectivity can explain the genetic differentiation of mangrove populations regardless of the species, region, and genetic marker (significant regression models in 95% of cases, with an average R-square of 0.44 ± 0.23 and Person’s correlation of 0.65 ± 0.17), systematically improving IBD models. Centrality indices, providing information on important stepping-stone sites between biogeographic regions, were also important in explaining differentiation (R-square improvement of 0.06 ± 0.07, up to 0.42). We further show that ocean currents produce skewed dispersal kernels for mangroves, highlighting the role of rare long-distance dispersal events responsible for historical settlements. Overall, we demonstrate the role of oceanographic connectivity in structuring mangrove intra-specific diversity. Our findings are critical for mangroves’ biogeography and evolution, but also for management strategies considering climate change and genetic biodiversity conservation

    Supersymmetric Dark Matter after LHC Run 1

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    Different mechanisms operate in various regions of the MSSM parameter space to bring the relic density of the lightest neutralino, neutralino_1, assumed here to be the LSP and thus the Dark Matter (DM) particle, into the range allowed by astrophysics and cosmology. These mechanisms include coannihilation with some nearly-degenerate next-to-lightest supersymmetric particle (NLSP) such as the lighter stau (stau_1), stop (stop_1) or chargino (chargino_1), resonant annihilation via direct-channel heavy Higgs bosons H/A, the light Higgs boson h or the Z boson, and enhanced annihilation via a larger Higgsino component of the LSP in the focus-point region. These mechanisms typically select lower-dimensional subspaces in MSSM scenarios such as the CMSSM, NUHM1, NUHM2 and pMSSM10. We analyze how future LHC and direct DM searches can complement each other in the exploration of the different DM mechanisms within these scenarios. We find that the stau_1 coannihilation regions of the CMSSM, NUHM1, NUHM2 can largely be explored at the LHC via searches for missing E_T events and long-lived charged particles, whereas their H/A funnel, focus-point and chargino_1 coannihilation regions can largely be explored by the LZ and Darwin DM direct detection experiments. We find that the dominant DM mechanism in our pMSSM10 analysis is chargino_1 coannihilation: {parts of its parameter space can be explored by the LHC, and a larger portion by future direct DM searches.Comment: 21 pages, 8 figure

    PGI31 PAIN AFTER LIVER TRANSPLANT: A CROSS SECTIONAL STUDY

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