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Characterization of a common susceptibility locus for asthma-related traits (2004)

T. Laitinen ; A. Polvi ; P. Rydman ; [et al.]

American Association for the Advancement of Science (AAAS)

In: Science. 304(5668): 300-4. doi: 10.1126/science.1090010.

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Publication Date: 2004-04-10

Description: Susceptibility to asthma depends on variation at an unknown number of genetic loci. To identify susceptibility genes on chromosome 7p, we adopted a hierarchical genotyping design, leading to the identification of a 133-kilobase risk-conferring segment containing two genes. One of these coded for an orphan G protein-coupled receptor named GPRA (G protein-coupled receptor for asthma susceptibility), which showed distinct distribution of protein isoforms between bronchial biopsies from healthy and asthmatic individuals. In three cohorts from Finland and Canada, single nucleotide polymorphism-tagged haplotypes associated with high serum immunoglobulin E or asthma. The murine ortholog of GPRA was up-regulated in a mouse model of ovalbumin-induced inflammation. Together, these data implicate GPRA in the pathogenesis of atopy and asthma.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Laitinen, Tarja -- Polvi, Anne -- Rydman, Pia -- Vendelin, Johanna -- Pulkkinen, Ville -- Salmikangas, Paula -- Makela, Siru -- Rehn, Marko -- Pirskanen, Asta -- Rautanen, Anna -- Zucchelli, Marco -- Gullsten, Harriet -- Leino, Marina -- Alenius, Harri -- Petays, Tuula -- Haahtela, Tari -- Laitinen, Annika -- Laprise, Catherine -- Hudson, Thomas J -- Laitinen, Lauri A -- Kere, Juha -- New York, N.Y. -- Science. 2004 Apr 9;304(5668):300-4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉GeneOS Limited, 00251 Helsinki, Finland.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/15073379" target="_blank"〉PubMed〈/a〉

Keywords: Algorithms ; Alternative Splicing ; Animals ; Asthma/*genetics/metabolism ; Bronchi/chemistry/cytology ; Chromosomes, Human, Pair 7/*genetics ; Epithelial Cells/chemistry ; Female ; Finland ; Gene Expression ; Genes ; Genetic Linkage ; *Genetic Predisposition to Disease ; Genetic Variation ; Genotype ; *Haplotypes ; Humans ; Hypersensitivity/genetics/metabolism ; Immunoglobulin E/blood ; Inflammation/genetics ; Lung/metabolism ; Male ; Mice ; Myocytes, Smooth Muscle/chemistry ; Polymorphism, Single Nucleotide ; Quebec ; Receptors, G-Protein-Coupled/analysis/*genetics

Print ISSN: 0036-8075

Electronic ISSN: 1095-9203

Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics

Published by American Association for the Advancement of Science (AAAS)

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Ensemble forecasting of major solar flares – First results (2015)

J. A. Guerra, A. Pulkkinen, V. M. Uritsky

Wiley

In: Space Weather

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Publication Date: 2015-09-11

Description: We present the results from the first ensemble prediction model for major solar flares (M and X classes). The primary aim of this investigation is to explore the construction of an ensemble for an initial prototyping of this new concept. Using the probabilistic forecasts from three models hosted at the Community Coordinated Modeling Center (NASA-GSFC) and the NOAA forecasts, we developed an ensemble forecast by linearly combining the flaring probabilities from all four methods. Performance-based combination weights were calculated using a Monte-Carlo-type algorithm that applies a decision threshold P t h to the combined probabilities and maximizing the Heidke Skill Score (HSS). Using the data for 13 recent solar active regions between years 2012 - 2014, we found that linear combination methods can improve the overall probabilistic prediction and improve the categorical prediction for certain values of decision thresholds. Combination weights vary with the applied threshold and none of the tested individual forecasting models seem to provide more accurate predictions than the others for all values of P t h . According to the maximum values of HSS, a performance-based weights calculated by averaging over the sample, performed similarly to a equally weighted model. The values P t h for which the ensemble forecast performs the best are 25 % for M-class flares and 15 % for X-class flares. When the human-adjusted probabilities from NOAA are excluded from the ensemble, the ensemble performance in terms of the Heidke score, is reduced.

Print ISSN: 1539-4964

Electronic ISSN: 1542-7390

Topics: Geosciences , Physics