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- Ali, M, et al.
(författare)
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Protocol for the development of the international population registry for aphasia after stroke (I-PRAISE)
- 2022
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Ingår i: Aphasiology. - : Informa UK Limited. - 0268-7038 .- 1464-5041. ; 36:4, s. 534-554
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Tidskriftsartikel (refereegranskat)abstract
- Background: We require high-quality information on the current burden, the types of therapy and resources available, methods of delivery, care pathways and long-term outcomes for people with aphasia.Aim: To document and inform international delivery of post-stroke aphasia treatment, to optimise recovery and reintegration of people with aphasia.Methods & Procedures: Multi-centre, prospective, non-randomised, open study, employing blinded outcome assessment, where appropriate, including people with post-stroke aphasia, able to attend for 30 minutes during the initial language assessment, at first contact with a speech and language therapist for assessment of aphasia at participating sites. There is no study-mandated intervention. Assessments will occur at baseline (first contact with a speech and language therapist for aphasia assessment), discharge from Speech and Language Therapy (SLT), 6 and 12-months post-stroke. Our primary outcome is changed from baseline in the Amsterdam Nijmegen Everyday Language Test (ANELT/Scenario Test for participants with severe verbal impairments) at 12-months post-stroke. Secondary outcomes at 6 and 12 months include the Therapy Outcome Measure (TOMS), Subjective Index of Physical and Social Outcome (SIPSO), Aphasia Severity Rating Scale (ASRS), Western Aphasia Battery Aphasia Quotient (WAB-AQ), stroke and aphasia quality of life scale (SAQoL-39), European Quality of Life Scale (EQ-5D), lesion description, General Health Questionnaire (GHQ-12), resource use, and satisfaction with therapy provision and success. We will collect demography, clinical data, and therapy content. Routine neuroimaging and medication administration records will be accessed where possible; imaging will be pseudonymised and transferred to a central reading centre. Data will be collected in a central registry. We will describe demography, stroke and aphasia profiles and therapies available. International individual participant data (IPD) meta-analyses will examine treatment responder rates based on minimal detectable change & clinically important changes from baseline for primary and secondary outcomes at 6 and 12 months. Multivariable meta-analyses will examine associations between demography, therapy, medication use and outcomes, considering service characteristics. Where feasible, costs associated with treatment will be reported. Where available, we will detail brain lesion size and site, and examine correlations with SLT and language outcome at 12 months.Conclusion: International differences in care, resource utilisation and outcomes will highlight avenues for further aphasia research, promote knowledge sharing and optimise aphasia rehabilitation delivery. IPD meta-analyses will enhance and expand understanding, identifying cost-effective and promising approaches to optimise rehabilitation to benefit people with aphasia.
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| 3. |
- Hudson, Thomas J., et al.
(författare)
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International network of cancer genome projects
- 2010
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7291, s. 993-998
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Tidskriftsartikel (refereegranskat)abstract
- The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
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| 6. |
- Leebens-Mack, James H., et al.
(författare)
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One thousand plant transcriptomes and the phylogenomics of green plants
- 2019
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Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 574:7780, s. 679-
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Tidskriftsartikel (refereegranskat)abstract
- Green plants (Viridiplantae) include around 450,000-500,000 species(1,2) of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life.
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| 8. |
- Fernie, A. R., et al.
(författare)
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Perspectives on plant photorespiratory metabolism
- 2013
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Ingår i: Plant Biology. - : Wiley-Blackwell. - 1435-8603 .- 1438-8677. ; 15:4, s. 748-753
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Forskningsöversikt (refereegranskat)abstract
- Being intimately intertwined with (C3) photosynthesis, photorespiration is an incredibly high flux-bearing pathway. Traditionally, the photorespiratory cycle was viewed as closed pathway to refill the Calvin-Benson cycle with organic carbon. However, given the network nature of metabolism, it hence follows that photorespiration will interact with many other pathways. In this article, we review current understanding of these interactions and attempt to define key priorities for future research, which will allow us greater fundamental comprehension of general metabolic and developmental consequences of perturbation of this crucial metabolic process.
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| 9. |
- Fragopoulou, A., et al.
(författare)
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Scientific panel on electromagnetic field health risks : Consensus points, recommendations, and rationales
- 2010
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Ingår i: Reviews on Environmental Health. - 0048-7554. ; 25:4, s. 307-317
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Tidskriftsartikel (refereegranskat)abstract
- In November, 2009, a scientific panel met in Seletun, Norway, for three days of intensive discussion on existing scientific evidence and public health implications of the unprecedented global exposures to artificial electromagnetic fields (EMF). EMF exposures (static to 300 GHz) result from the use of electric power and from wireless telecommunications technologies for voice and data transmission, energy, security, military and radar use in weather and transportation. The Scientific Panel recognizes that the body of evidence on EMF requires a new approach to protection of public health; the growth and development of the fetus, and of children; and argues for strong preventative actions. New, biologically-based public exposure standards are urgently needed to protect public health worldwide.
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| 10. |
- Gómez-de-Mariscal, E., et al.
(författare)
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DeepImageJ : A user-friendly environment to run deep learning models in ImageJ
- 2021
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Ingår i: Nature Methods. - : Springer Nature. - 1548-7091 .- 1548-7105. ; 18:10, s. 1192-1195
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Tidskriftsartikel (refereegranskat)abstract
- DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learning models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest bioimage repository of pre-trained deep learning models (BioImage Model Zoo). Hence, nonexperts can easily perform common image processing tasks in life-science research with deep learning-based tools including pixel and object classification, instance segmentation, denoising or virtual staining. DeepImageJ is compatible with existing state of the art solutions and it is equipped with utility tools for developers to include new models. Very recently, several training frameworks have adopted the deepImageJ format to deploy their work in one of the most used softwares in the field (ImageJ). Beyond its direct use, we expect deepImageJ to contribute to the broader dissemination and reuse of deep learning models in life sciences applications and bioimage informatics.
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