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- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 2. |
- Narayan, Rupa, et al.
(författare)
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HLA Class I Genotype Is Associated with Relapse Risk after Allogeneic Stem Cell Transplantation for NPM1-Mutated Acute Myeloid Leukemia
- 2023
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Ingår i: Transplantation and cellular therapy. - : Elsevier BV. - 2666-6367. ; 29:7, s. 1-452
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Tidskriftsartikel (refereegranskat)abstract
- Mutation-bearing peptide ligands from mutated nucleophosmin-1 (NPM1) protein have been empirically found to be presented by HLA class I in acute myeloid leukemia (AML). We hypothesized that HLA genotype may impact allogeneic hematopoietic stem cell transplantation (allo-HCT) outcomes in NPM1-mutated AML owing to differences in antigen presentation. We evaluated the effect of the variable of predicted strong binding to mutated NPM1 peptides using HLA class I genotypes from matched donor-recipient pairs on transplant recipients’ overall survival (OS) and disease-free survival (DFS) as part of the primary objectives and cumulative incidence of relapse and nonrelapse mortality (NRM) as part of secondary objectives. Baseline and outcome data reported to the Center for International Blood and Marrow Transplant Research from a study cohort of adult patients (n = 1020) with NPM1-mutated de novo AML in first (71%) or second (29%) complete remission undergoing 8/8 matched related (18%) or matched unrelated (82%) allo-HCT were analyzed retrospectively. Class I alleles from donor-recipient pairs were analyzed for predicted strong HLA binding to mutated NPM1 using netMHCpan 4.0. A total of 429 (42%) donor-recipient pairs were classified as having predicted strong-binding HLA alleles (SBHAs) to mutated NPM1. In multivariable analyses adjusting for clinical covariates, the presence of predicted SBHAs was associated with a lower risk of relapse (hazard ratio [HR],.72; 95% confidence interval [CI],.55 to.94; P =.015). OS (HR,.81; 95% CI,.67 to.98; P =.028) and DFS (HR,.84; 95% CI,.69 to 1.01; P =.070) showed a suggestion of better outcomes if predicted SBHAs were present but did not meet the prespecified P value of <.025. NRM did not differ (HR, 1.04; P =.740). These hypothesis-generating data support further exploration of HLA genotype-neoantigen interactions in the allo-HCT context.
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