1,131 research outputs found
The Art of Distancing: A Review of How to Do Nothing
In this symposium style review, Matt Drissell (Associate Professor of Art), Leah Zuidema (Vice President for Online & Graduate Education), and Dave Mulder (Associate Professor of Education) each bring perspectives from their area of expertise.
Posting about the book How to Do Nothing-Resisting the Attention Economy from In All Things - an online journal for critical reflection on faith, culture, art, and every ordinary-yet-graced square inch of Godâs creation.
https://inallthings.org/the-art-of-distancing-a-review-of-how-to-do-nothing
Unravelling institutional work patterns:Planning offshore wind farms in contested space
Offshore wind farms (OWF) are considered important for a timely energy transition. However, offshore space is governed by sector-specific institutional frameworks representing various and sometimes conflicting interests. Therefore, institutional change towards improved cooperation and coordination between various stakeholders, their interests and alternative institutional frameworks is necessary. Institutional work is used as an analytical lens to explore patterns resulting from the interplay between different forms of institutional work by actors over time. Data was collected through participatory observation of the Dutch North Sea Dialogues (NSD) and focused on balancing interest in the context of multi-use of OFW. Institutional change in this case relied mostly on a highly subtle interplay between forms of creating and maintaining work that result in incremental changes to existing practices. Sustainability transitions could benefit from institutional harmonization as a pathway to institutional change for improved cross-sectoral coordination and cooperation
Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information
Serious adverse events and deaths in PCSK9 inhibitor trials reported on ClinicalTrials.gov:a systematic review
Background: Previous reviews of PCSK9 inhibitor trials are limited by a focus on composite cardiovascular outcomes. ClinicalTrials.gov provides trial results for individual clinical outcomes. Aim of this systematic review was to assess the effect of PCSK9 inhibitors on the risk of myocardial infarction, stroke/TIA, heart failure, diabetes mellitus, neurocognitive events, all-cause serious adverse events (SAE), and all-cause deaths as registered on ClinicalTrials.gov. Methods: PubMed, regulatory reports, ClinicalTrials.gov, and company websites were used to search studies. Randomized trials comparing PCSK9 inhibitor with placebo in participants with hypercholesterolemia were eligible. Study characteristics, risk of bias, and numbers of participants with the outcomes of interest were collected. Results: We identified 33 lipid-lowering and 4 clinical outcomes trials with results on ClinicalTrials.gov (n = 16,958 and n = 73,836, respectively). Risk of bias was generally high. PCSK9 inhibitors did not affect the risk of any of the investigated outcomes in either type of trial. However, in clinical outcomes studies, alirocumab decreased the risk of all-cause SAE (OR 0.92; 95% CI 0.86â0.98), and evolocumab probably increased the risk of mortality (OR 1.12; 95% CI 1.00â1.25). Conclusions: Our meta-analysis of clinical events registered on ClinicalTrials.gov did not show that PCSK9 inhibitors improve cardiovascular health. Evolocumab increased the risk of all-cause mortality
Large Sample Size Fallacy in Trials About Antipsychotics for Neuropsychiatric Symptoms in Dementia
Background: A typical antipsychotics for neuropsychiatric symptoms in dementia have been tested in much larger trials than the older conventional drugs. The advantage of larger sample sizes is that negative findings become less likely and the effect estimates more precise. However, as sample sizes increase, the trials also get more expensive and time consuming while exposing more patients to drugs with unknown safety profiles. Moreover, a large sample size might yield a statistically significant effect that is not necessarily clinically relevant. Objective: To assess (1) the variation in sample size and sample size calculations of antipsychotic trials in dementia, (2) the size of reported treatment effects and related statistical significance, and (3) general study characteristics that might be related to sample size. Study Design and Setting: We performed a meta-epidemiological study of randomized trials that tested antipsychotics for neuropsychiatric symptoms in dementia. The trials compared conventional or atypical antipsychotics with placebo or another antipsychotic. Two reviewers independently extracted sample size, sample size calculations, reported treatment effects with p-values, and general study characteristics (drug type, trial duration, type of funding). We calculated a reference sample size of 83 and 433 per study group for the placebo-controlled and head-to-head trials respectively. Results: We identified 33 placebo-controlled trials, and 18 head-to-head trials. Only 14 (42%) and 2 (11%), respectively, reported a sample size calculation. The average sample size per arm was 34 (range 6-179) in placebo-controlled trials testing conventional drugs, 107 (8-237) in such trials testing atypical drugs, and 104 (95-115) in such trials testing both drug types; it was 31 (10-88) in head-to-head trials. Thirteen out of 18 trials with sample sizes larger than required (72%) reported a statistically significant treatment effect, of which two (15%) were clinically relevant. None of the head-to-head trials reported a statistically significant treatment effect, even though some suggested non-inferiority. In placebo-controlled trials of atypical drugs, longer trial duration (>6 weeks) and commercial funding were associated with higher sample size. Conclusion: Sample size calculations were poorly reported in antipsychotic trials for dementia. Placebo-controlled trials of atypical antipsychotics showed large sample size fallacy while head-to-head trials were massively underpowered
Editors' Review and Introduction: Learning Grammatical Structures: Developmental, CrossâSpecies, and Computational Approaches
Human languages all have a grammar, that is, rules that determine how symbols in a language can be combined to create complex meaningful expressions. Despite decades of research, the evolutionary, developmental, cognitive, and computational bases of grammatical abilities are still not fully understood. âArtificial Grammar Learningâ (AGL) studies provide important insights into how rules and structured sequences are learned, the relevance of these processes to language in humans, and whether the cognitive systems involved are shared with other animals. AGL tasks can be used to study how human adults, infants, animals, or machines learn artificial grammars of various sorts, consisting of rules defined typically over syllables, sounds, or visual items. In this introduction, we distill some lessons from the nine other papers in this special issue, which review the advances made from this growing body of literature. We provide a critical synthesis, identify the questions that remain open, and recognize the challenges that lie ahead. A key observation across the disciplines is that the limits of human, animal, and machine capabilities have yet to be found. Thus, this interdisciplinary area of research firmly rooted in the cognitive sciences has unearthed exciting new questions and venues for research, along the way fostering impactful collaborations between traditionally disconnected disciplines that are breaking scientific ground
Tuning the Loading and Release Properties of MicroRNA-Silencing Porous Silicon Nanoparticles by Using Chemically Diverse Peptide Nucleic Acid Payloads
Peptide nucleic acids (PNAs) are a class of artificial oligonucleotide mimics that have garnered much attention as precision biotherapeutics for their efficient hybridization properties and their exceptional biological and chemical stability. However, the poor cellular uptake of PNA is a limiting factor to its more extensive use in biomedicine; encapsulation in nanoparticle carriers has therefore emerged as a strategy for internalization and delivery of PNA in cells. In this study, we demonstrate that PNA can be readily loaded into porous silicon nanoparticles (pSiNPs) following a simple salt-based trapping procedure thus far employed only for negatively charged synthetic oligonucleotides. We show that the ease and versatility of PNA chemistry also allows for producing PNAs with different net charge, from positive to negative, and that the use of differently charged PNAs enables optimization of loading into pSiNPs. Differently charged PNA payloads determine different release kinetics and allow modulation of the temporal profile of the delivery process. In vitro silencing of a set of specific microRNAs using a pSiNP-PNA delivery platform demonstrates the potential for biomedical applications
Antipsychotics for agitation and psychosis in people with Alzheimer's disease and vascular dementia:A Cochrane Review
Effects Of Increasing The Involvement Of Community-Dwelling Frail Older Adults In A Proactive Assessment Service:A Pragmatic Trial
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A coupled terrestrial and aquatic biogeophysical model of the Upper Merrimack River watershed, New Hampshire, to inform ecosystem services evaluation and management under climate and land-cover change
Accurate quantification of ecosystem services (ES) at regional scales is increasingly important for making informed decisions in the face of environmental change. We linked terrestrial and aquatic ecosystem process models to simulate the spatial and temporal distribution of hydrological and water quality characteristics related to ecosystem services. The linked model integrates two existing models (a forest ecosystem model and a river network model) to establish consistent responses to changing drivers across climate, terrestrial, and aquatic domains. The linked model is spatially distributed, accounts for terrestrialâaquatic and upstreamâdownstream linkages, and operates on a daily time-step, all characteristics needed to understand regional responses. The model was applied to the diverse landscapes of the Upper Merrimack River watershed, New Hampshire, USA. Potential changes in future environmental functions were evaluated using statistically downscaled global climate model simulations (both a high and low emission scenario) coupled with scenarios of changing land cover (centralized vs. dispersed land development) for the time period of 1980â2099. Projections of climate, land cover, and water quality were translated into a suite of environmental indicators that represent conditions relevant to important ecosystem services and were designed to be readily understood by the public. Model projections show that climate will have a greater influence on future aquatic ecosystem services (flooding, drinking water, fish habitat, and nitrogen export) than plausible changes in land cover. Minimal changes in aquatic environmental indicators are predicted through 2050, after which the high emissions scenarios show intensifying impacts. The spatially distributed modeling approach indicates that heavily populated portions of the watershed will show the strongest responses. Management of land cover could attenuate some of the changes associated with climate change and should be considered in future planning for the region
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