| 1. |
- 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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| 2. |
- Wit, J M., et al.
(författare)
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Personalized Approach to Growth Hormone Treatment: Clinical Use of Growth Prediction Models
- 2013
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Ingår i: Hormone Research in Paediatrics. - : Karger. - 1663-2818 .- 1663-2826. ; 79:5, s. 257-270
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Forskningsöversikt (refereegranskat)abstract
- The goal of growth hormone (GH) treatment in a short child is to attain a fast catch-up growth toward the target height (TH) standard deviation score (SDS), followed by a maintenance phase, a proper pubertal height gain, and an adult height close to TH. The short-term response variable of GH treatment, first-year height velocity (HV) (cm/year or change in height SDS), can either be compared with GH response charts for diagnosis, age and gender, or with predicted HV based on prediction models. Three types of prediction models have been described: the Kabi International Growth Hormone Study models, the Gothenburg models and the Cologne model. With these models, 50-80% of the variance could be explained. When used prospectively, individualized dosing reduces the variation in growth response in comparison with a fixed dose per body weight. Insulin-like growth factor-I-based dose titration also led to a decrease in the variation. It is uncertain whether adding biochemical, genetic or proteomic markers may improve the accuracy of the prediction. Prediction models may lead to a more evidence-based approach to determine the GH dose regimen and may reduce the drug costs for GH treatment. There is a need for user-friendly software programs to make prediction models easily available in the clinic.
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| 3. |
- Rubin, T., et al.
(författare)
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'Quantum-based realizations of the pascal' status and progress of the empir-project: quantumpascal
- 2022
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Ingår i: 6th TC16 Conference on Pressure and Vacuum Measurement 2022, Together with the 24th TC3 Conference on the Measurement of Force, Mass and Torque, the 14th TC5 Conference on the Measurement of Hardness, and the 5th TC22 Conference on Vibration Measurement. - : International Measurement Confederation (IMEKO). - 9781713870227
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Konferensbidrag (refereegranskat)abstract
- The QuantumPascal (QP) project combines the capabilities of 12 European institutions to enable traceable pressure measurements utilizing quantum-based methods that evaluate the number density instead of force per area to target the wide pressure range between 1 Pa and 3 MPa. This article summarizes the goals and results since the project start in June 2019.
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