1,843 research outputs found

    A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease

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    Understanding the order and progression of change in biomarkers of neurodegeneration is essential to detect the effects of pharmacological interventions on these biomarkers. In Huntington’s disease (HD), motor, cognitive and MRI biomarkers are currently used in clinical trials of drug efficacy. Here for the first time we use directly compare data from three large observational studies of HD (total N = 532) using a probabilistic event-based model (EBM) to characterise the order in which motor, cognitive and MRI biomarkers become abnormal. We also investigate the impact of the genetic cause of HD, cytosine-adenine-guanine (CAG) repeat length, on progression through these stages. We find that EBM uncovers a broadly consistent order of events across all three studies; that EBM stage reflects clinical stage; and that EBM stage is related to age and genetic burden. Our findings indicate that measures of subcortical and white matter volume become abnormal prior to clinical and cognitive biomarkers. Importantly, CAG repeat length has a large impact on the timing of onset of each stage and progression through the stages, with a longer repeat length resulting in earlier onset and faster progression. Our results can be used to help design clinical trials of treatments for Huntington’s disease, influencing the choice of biomarkers and the recruitment of participants

    Revisiting the Properties of X-Ray Active Galactic Nuclei in the SSA22 Protocluster: Normal Supermassive Black Hole and Host-galaxy Growth for AGNs in a z = 3.09 Overdensity

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    \ua9 2023. The Author(s). Published by the American Astronomical Society. We analyze the physical properties of eight X-ray-selected active galactic nuclei (AGNs) and one candidate protoquasar system (ADF22A1) in the z = 3.09 SSA22 protocluster by fitting their X-ray-to-IR spectral energy distributions (SEDs) using our SED-fitting code, Lightning (https://www.github.com/rafaeleufrasio/lightning). We recover star formation histories (SFHs) for seven of these systems which are well fit by composite stellar population plus AGN models. We find indications that four out of nine of the SSA22 AGN systems we study have host galaxies below the main sequence, with SFR/SFRMS ≤ −0.4. The remaining SSA22 systems, including ADF22A1, are consistent with obscured supermassive black hole (SMBH) growth in star-forming galaxies. We estimate the SMBH accretion rates and masses, and compare the properties and SFHs of the nine protocluster AGN systems with X-ray-detected AGN candidates in the Chandra Deep Fields (CDF), finding that the distributions of SMBH growth rates, star formation rates (SFRs), SMBH masses, and stellar masses for the protocluster AGNs are consistent with field AGNs. We constrain the ratio between the sample-averaged SSA22 SMBH mass and CDF SMBH mass to <1.41. While the AGNs are located near the density peaks of the protocluster, we find no statistically significant trends between the AGN or host-galaxy properties and their location in the protocluster. We interpret the similarity of the protocluster and field AGN populations together with existing results as suggesting that the protocluster and field AGNs coevolve with their hosts in the same ways, while AGN-triggering events are more likely in the protocluster

    A Graph-Based Semantics Workbench for Concurrent Asynchronous Programs

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    A number of novel programming languages and libraries have been proposed that offer simpler-to-use models of concurrency than threads. It is challenging, however, to devise execution models that successfully realise their abstractions without forfeiting performance or introducing unintended behaviours. This is exemplified by SCOOP---a concurrent object-oriented message-passing language---which has seen multiple semantics proposed and implemented over its evolution. We propose a "semantics workbench" with fully and semi-automatic tools for SCOOP, that can be used to analyse and compare programs with respect to different execution models. We demonstrate its use in checking the consistency of semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of the language. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, and how the visual yet algebraic nature of the model can be used to ascertain soundness.Comment: Accepted for publication in the proceedings of FASE 2016 (to appear

    An image-based model of brain volume biomarker changes in Huntington's disease

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    Objective: Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages. Methods: We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides. Results: The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers. Interpretation: We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease

    Synergies for Improving Oil Palm Production and Forest Conservation in Floodplain Landscapes

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    Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world’s tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates (413/ha?yr413/ha?yr–637/ha?yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of 299/ha?yr-299/ha?yr--65/ha?yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes

    Robust markers and sample sizes for multi‐centre trials of Huntington's disease

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    Objective: The identification of sensitive biomarkers is essential to validate therapeutics for Huntington disease (HD). We directly compare structural imaging markers across the largest collective imaging HD dataset to identify a set of imaging markers robust to multicenter variation and to derive upper estimates on sample sizes for clinical trials in HD. Methods: We used 1 postprocessing pipeline to retrospectively analyze T1-weighted magnetic resonance imaging (MRI) scans from 624 participants at 3 time points, from the PREDICT-HD, TRACK-HD, and IMAGE-HD studies. We used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible treatment effects in disease-affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers. Results: We identified a set of common anatomical regions that have similarly large standardized effect sizes (>0.5) between healthy control and premanifest HD (PreHD) groups. These included subcortical, white matter, and cortical regions and nonventricular cerebrospinal fluid (CSF). We also observed a consistent spatial distribution of effect size by region across the whole brain. We found that multicenter studies were necessary to capture treatment effect variance; for a 20% treatment effect, power of >80% was achieved for the caudate (n = 661), pallidum (n = 687), and nonventricular CSF (n = 939), and, crucially, these imaging markers provided greater power than standard clinical markers. Interpretation: Our findings provide the first cross-study validation of structural imaging markers in HD, supporting the use of these measurements as endpoints for both observational studies and clinical trial

    Utilization of outpatient services in refugee settlement health facilities: a comparison by age, gender, and refugee versus host national status

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    <p>Abstract</p> <p>Background</p> <p>Comparisons between refugees receiving health care in settlement-based facilities and persons living in host communities have found that refugees have better health outcomes. However, data that compares utilization of health services between refugees and the host population, and across refugee settlements, countries and regions is limited. The paper will address this information gap. The analysis in this paper uses data from the United Nations High Commissioner of Refugees (UNHCR) Health Information System (HIS).</p> <p>Methods</p> <p>Data about settlement populations and the use of outpatient health services were exported from the UNHCR health information system database. Tableau Desktop was used to explore the data. STATA was used for data cleaning and statistical analysis. Differences in various indicators of the use of health services by region, gender, age groups, and status (host national vs. refugee population) were analyzed for statistical significance using generalized estimating equation models that adjusted for correlated data within refugee settlements over time.</p> <p>Results</p> <p>Eighty-one refugee settlements were included in this study and an average population of 1.53 million refugees was receiving outpatient health services between 2008 and 2009. The crude utilization rate among refugees is 2.2 visits per person per year across all settlements. The refugee utilization rate in Asia (3.5) was higher than in Africa on average (1.8). Among refugees, females have a statistically significant higher utilization rate than males (2.4 visits per person per year vs. 2.1). The proportion of new outpatient attributable to refugees is higher than that attributable to host nationals. In the Asian settlements, only 2% outpatient visits, on average, were attributable to host community members. By contrast, in Africa, the proportion of new outpatient (OPD) visits by host nationals was 21% on average; in many Ugandan settlements, the proportion of outpatient visits attributable to host community members was higher than that for refugees. There was no statistically significant difference between the size of the male and female populations across refugee settlements. Across all settlements reporting to the UNHCR database, the percent of the refugee population that was less than five years of age is 16% on average.</p> <p>Conclusions</p> <p>The availability of a centralized database of health information across UNHCR-supported refugee settlements is a rich resource. The SPHERE standard for emergencies of 1-4 visits per person per year appears to be relevant for Asia in the post-emergency phase, but not for Africa. In Africa, a post-emergency standard of 1-2 visits per person per year should be considered. Although it is often assumed that the size of the female population in refugee settlements is higher than males, we found no statistically significant difference between the size of the male and female populations in refugee settlements overall. Another assumption---that the under-fives make up 20% of the settlement population during the emergency phase---does not appear to hold for the post-emergency phase; under-fives made up about 16% of refugee settlement populations.</p

    Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

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    Abstract Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.http://deepblue.lib.umich.edu/bitstream/2027.42/78272/1/1748-5908-4-50.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/2/1748-5908-4-50-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/3/1748-5908-4-50-S3.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/4/1748-5908-4-50-S4.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/5/1748-5908-4-50.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/6/1748-5908-4-50-S2.PDFPeer Reviewe
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