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1,120 results on '"Raleigh, J"'

5. Acute limb ischemia registry, the forgotten emergency

Author

Bluro, I, primary, Garagoli, F, additional, Chiabrando, J, additional, Chas, J, additional, Valle Raleigh, J, additional, Gonzalez, N, additional, Fernandez Villar, G, additional, Iroulart, J, additional, Pellegrini, M N, additional, Herzkovich, N, additional, Fernandez Recalde, M L, additional, Izaguirre, A, additional, Rojas Matas, C, additional, Kotowicz, V, additional, and Pizarro, R, additional

Published
2023
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10. The KRAS-variant and miRNA expression in RTOG endometrial cancer clinical trials 9708 and 9905.

Author

Lee, Larissa J, Ratner, Elena, Uduman, Mohamed, Winter, Kathryn, Boeke, Marta, Greven, Kathryn M, King, Stephanie, Burke, Thomas W, Underhill, Kelly, Kim, Harold, Boulware, Raleigh J, Yu, Herbert, Parkash, Vinita, Lu, Lingeng, Gaffney, David, Dicker, Adam P, and Weidhaas, Joanne

Subjects
Humans, Endometrial Neoplasms, Lymphatic Metastasis, Genetic Predisposition to Disease, ras Proteins, Proto-Oncogene Proteins, MicroRNAs, Risk Factors, Case-Control Studies, Gene Expression Regulation, Neoplastic, Mutation, Alleles, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Proto-Oncogene Proteins p21(ras), Gene Expression Regulation, Neoplastic, and over, General Science & Technology
Abstract

ObjectiveTo explore the association of a functional germline variant in the 3'-UTR of KRAS with endometrial cancer risk, as well as the association of microRNA (miRNA) signatures and the KRAS-variant with clinical characteristics and survival outcomes in two prospective RTOG endometrial cancer trials.Methods/materialsThe association of the KRAS-variant with endometrial cancer risk was evaluated by case-control analysis of 467 women with type 1 or 2 endometrial cancer and 582 age-matched controls. miRNA and DNA were isolated for expression profiling and genotyping from tumor specimens of 46 women with type 1 endometrial cancer enrolled in RTOG trials 9708 and 9905. miRNA expression levels and KRAS-variant genotype were correlated with patient and tumor characteristics, and survival outcomes were evaluated by variant allele type.ResultsThe KRAS-variant was not significantly associated with overall endometrial cancer risk (14% controls and 17% type 1 cancers), although was enriched in type 2 endometrial cancers (24%, p = 0.2). In the combined analysis of RTOG 9708/9905, miRNA expression differed by age, presence of lymphovascular invasion and KRAS-variant status. Overall survival rates at 3 years for patients with the variant and wild-type alleles were 100% and 77% (HR 0.3, p = 0.24), respectively, favoring the variant.ConclusionsThe KRAS-variant may be a genetic marker of risk for type 2 endometrial cancers. In addition, tumor miRNA expression appears to be associated with patient age, lymphovascular invasion and the KRAS-variant, supporting the hypothesis that altered tumor biology can be measured by miRNA expression, and that the KRAS-variant likely impacts endometrial tumor biology.

Published
2014

12. Generalizability of Artificial Neural Network Models in Ecological Applications: Predicting Nest Occurrence and Breeding Success of the Red-winged Blackbird Agelaius phoeniceus

Author

Ozesmi, Uygar, Tan, Can Ozan, Ozesmi, Stacy L., and Robertson, Raleigh J.

Subjects
Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods
Abstract

Separate artificial neural network (ANN) models were developed from data in two geographical regions and years apart for a marsh-nesting bird, the red-winged blackbird Agelaius phoeniceus. Each model was independently tested on the spatially and temporally distinct data from the other region to determine how generalizable it was. The first model was developed to predict occurrence of nests in two wetlands on Lake Erie, Ohio in 1995 and 1996. The second model was developed to predict breeding success in two marshes in Connecticut, USA in 1969 and 1970. Independent variables were vegetation durability, stem density, stem/nest height, distance to open water, distance to edge, and water depth. With input variable relevances, sensitivity analyses and neural interpretation diagrams we were able to understand how the different models predicted nest occurrence and breeding success and compare their differences and similarities. Both models also predicted increasing nest occurrence/breeding success with increasing water depth under the nest and increasing distance to edge. However, relationships for prediction differed in the models. Generalizability of the models was poor except when the marshes had similar values of important variables in the model. ANN models performed better than generalized linear models (GLM) on marshes with similar structures. Generalizability of the models did not differ in nest occurrence and breeding success data. Extensive testing also showed that the GLMs were not necessarily more generalizable than ANNs, suggesting that ANN models make good definitions of a study system but are too specific to generalize well to other ecologically complex systems unless input variable distributions are very similar., Comment: 42 pages, 3 figures. Presented in ISEI3 conference (2002). Ecological Modeling in press

Published
2005
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20. Time to Extinction of Bird Populations

Author

Sæther, Bernt-Erik, Engen, Steinar, Møller, Anders Pape, Visser, Marcel E., Matthysen, Erik, Fiedler, Wolfgang, Lambrechts, Marcel M., Becker, Peter H., Brommer, Jon E., Dickinson, Janis, du Feu, Chris, Gehlbach, Frederick R., Merilä, Juha, Rendell, Wallace, Robertson, Raleigh J., Thomson, David, and Török, János

Published
2005

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