| 1. |
- Nielsen, Rasmus Oestergaard, et al.
(författare)
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Statement on methods in sport injury research from the 1st METHODS MATTER Meeting, Copenhagen, 2019
- 2020
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Ingår i: British Journal of Sports Medicine. - : BMJ PUBLISHING GROUP. - 0306-3674 .- 1473-0480. ; 54:15, s. 941-947
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Forskningsöversikt (refereegranskat)abstract
- High quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best practice methods-methods matter (greatly!). The 1st METHODS MATTER Meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting.
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| 2. |
- Nielsen, Rasmus Ostergaard, et al.
(författare)
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Statement on Methods in Sport Injury Research From the First METHODS MATTER Meeting, Copenhagen, 2019
- 2020
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Ingår i: Journal of Orthopaedic and Sports Physical Therapy. - : J O S P T. - 0190-6011 .- 1938-1344. ; 50:5, s. 226-233
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- SYNOPSIS: High-quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best-practice methods-methods matter (greatly!). The first METHODS MATTER meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting. Meeting participants agreed that the definition of sport injury depends on the research question and context. It was considered essential to be explicit about the goal of the research effort and to use frameworks to illustrate the assumptions that underpin measurement and the analytical strategy. Complex systems were discussed to illustrate how potential risk factors can interact in a nonlinear way. This approach is often a useful alternative to identifying single risk factors. Investigating changes in exposure status over time is important when analyzing sport injury etiology, and analyzing recurrent injury, subsequent injury, or injury exacerbation remains challenging. The choice of statistical model should consider the research question, injury measure (eg, prevalence, incidence), type and granularity of injury data (categorical or continuous), and study design. Multidisciplinary collaboration will be a cornerstone for future high-quality sport injury research. Working outside professional silos in a diverse, multidisciplinary team benefits the research process, from the formulation of research questions and designs to the statistical analyses and dissemination of study results in implementation contexts. This article has been copublished in the British Journal of Sports Medicine and the Journal of Orthopaedic & Sports Physical Therapy.
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| 3. |
- Şorman, Alevgül, et al.
(författare)
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Democratizing Energy, Energizing Democracy : Central Dimensions Surfacing in the Debate
- 2020
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Ingår i: Frontiers in Energy Research. - : Frontiers Media S.A.. - 2296-598X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- This perspective piece sets out to contribute to the academic and practitioner debates around energy transitions and democracy initiatives in the age of a climate crisis. For tackling present-day energy challenges in a democratic, equitable and just manner, critical social science and humanities research on meaning and materialities, new actors and narratives, values and democracy is indispensable. In doing so, we centralize our work around three fundamental axes: The Concept, reflecting on the energy itself and revitalizing its essence; The Political, embracing the value laden, political and gendered nature of energy, and recognizing citizens' initiatives as counter currents to centralized energy decision-making; and The People, anticipating the far right’s post-truth narratives that jeopardize planetary futures. We contend that “normative, political and embodied” research and praxis can serve for diversifying the energy transition debate as well as energizing bottom-up community led initiatives in order to democratize the energy playing field of recent times.
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| 4. |
- Wernersson, Erik, et al.
(författare)
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Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images
- 2024
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Ingår i: Nature Methods. - 1548-7091 .- 1548-7105.
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Tidskriftsartikel (refereegranskat)abstract
- Microscopy-based spatially resolved omic methods are transforming the life sciences. However, these methods rely on high numerical aperture objectives and cannot resolve crowded molecular targets, limiting the amount of extractable biological information. To overcome these limitations, here we develop Deconwolf, an open-source, user-friendly software for high-performance deconvolution of widefield fluorescence microscopy images, which efficiently runs on laptop computers. Deconwolf enables accurate quantification of crowded diffraction limited fluorescence dots in DNA and RNA fluorescence in situ hybridization images and allows robust detection of individual transcripts in tissue sections imaged with x20 air objectives. Deconvolution of in situ spatial transcriptomics images with Deconwolf increased the number of transcripts identified more than threefold, while the application of Deconwolf to images obtained by fluorescence in situ sequencing of barcoded Oligopaint probes drastically improved chromosome tracing. Deconwolf greatly facilitates the use of deconvolution in many bioimaging applications. Deconwolf is a computationally efficient and user-friendly software tool for fluorescence microscopy image deconvolution that improves the analysis of diverse fluorescence in situ hybridization methods and can handle large datasets.
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