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| 14. |
- Chiwara, P, et al.
(författare)
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Evaluating the Potential of Southampton Carbon Flux Model (SCARF) for Monitoring Terrestrial Gross Primary Productivity Across African Ecosystems
- 2016
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Ingår i: AGU Fall Meeting Abstracts.
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Konferensbidrag (refereegranskat)abstract
- Accurate knowledge about the amount and dynamics of terrestrial gross primary productivity is an important component for understanding of ecosystem functioning and processes. Recently a new diagnostic model, Southampton Carbon Flux (SCARF), was developed to predict terrestrial gross primary productivity at regional to global scale based on a chlorophyll index derived from MERIS data. The model aims at mitigating some shortcomings in traditional light-use-efficiency based models by (i) using the fraction of photosynthetic active radiation absorbed only by the photosynthetic components of the canopy (FAPARps) and (ii) using the intrinsic quantum yields of C3 and C4 photosynthesis thereby reducing errors from land cover misclassification. Initial evaluation of the model in northern higher latitude ecosystems shows good agreement with in situ measurements. The current study calibrated and validated the model for a diversity of vegetation types across Africa in order to test its performance over a water limiting environment. The validation was based on GPP measurements from seven eddy flux towers across Africa. Sensitivity and uncertainty analyses were also performed to determine the importance of key biophysical and meteorological input parameters.Overall, modelled GPP values show good agreement with in situ measured GPP at most sites except tropical rainforest site. Mean daily GPP varied significantly across sites depending on the vegetation types and climate; from a minimum of -0.12 gC m2 day-1 for the semi-arid savannah to a maximum of 7.30 gC m2 day-1 for tropical rain forest ecosystems at Ankasa (Ghana). The model results have modest to very strong positive agreement with observed GPP at most sites (R2 values ranging from 0.60 for Skukuza in South Africa) and 0.85 for Mongu in Zambia) except tropical rain forest ecosystem (R2=0.34). Overall, the model has a stronger across-site coefficient of determination (R2=0.78) than MOD17 GPP product (R2=0.68). PAR and VPD are the parameters that propagate much variation in model output at most sites especially in semi-arid and sub-humid ecosystems. The results demonstrate that the SCARF model can improve prediction of GPP across a wide range of African ecosystems..Key words: GPP, climate change, diagnostic model, photosynthetic quantum yield, C3/C4 photosynthesis
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| 16. |
- Dadaev, T, et al.
(författare)
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Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
- 2018
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 2256-
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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| 19. |
- Figlioli, G, et al.
(författare)
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The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer
- 2019
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Ingår i: NPJ breast cancer. - : Springer Science and Business Media LLC. - 2374-4677. ; 5, s. 38-
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Tidskriftsartikel (refereegranskat)abstract
- Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors.
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| 20. |
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