University of Arizona

About: University of Arizona is a education organization based out in Tucson, Arizona, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 63805 authors who have published 155998 publications receiving 6854915 citations. The organization is also known as: UA & U of A.

Molecular diagnosis of Burkitt's lymphoma.

Abstract: Background The distinction between Burkitt’s lymphoma and diffuse large-B-cell lymphoma is crucial because these two types of lymphoma require different treatments. We examined whether gene-expression profiling could reliably distinguish Burkitt’s lymphoma from diffuse large-B-cell lymphoma. Methods Tumor-biopsy specimens from 303 patients with aggressive lymphomas were profiled for gene expression and were also classified according to morphology, immunohistochemistry, and detection of the t(8;14) c-myc translocation. Results A classifier based on gene expression correctly identified all 25 pathologically verified cases of classic Burkitt’s lymphoma. Burkitt’s lymphoma was readily distinguished from diffuse large-B-cell lymphoma by the high level of expression of c-myc target genes, the expression of a subgroup of germinal-center B-cell genes, and the low level of expression of major-histocompatibility-complex class I genes and nuclear factor-κB target genes. Eight specimens with a pathological diagnosis of diffuse large-B-cell lymphoma had the typical gene-expression profile of Burkitt’s lymphoma, suggesting they represent cases of Burkitt’s lymphoma that are difficult to diagnose by current methods. Among 28 of the patients with a molecular diagnosis of Burkitt’s lymphoma, the overall survival was superior among those who had received intensive chemotherapy regimens instead of lower-dose regimens. Conclusions Gene-expression profiling is an accurate, quantitative method for distinguishing Burkitt’s lymphoma from diffuse large-B-cell lymphoma.

HI4PI: a full-sky H i survey based on EBHIS and GASS

Abstract: Deutsche Forschungsgemeinschaft (DFG) [KA1265/5-1, KA1265/5-2, KE757/71, KE757/7-2, KE757/7-3, KE757/11-1.]; International Max Planck Research School for Astronomy and Astrophysics at the Universities of Bonn and Cologne (IMPRS Bonn/Cologne); Estonian Research Council [IUT26-2]; European Regional Development Fund [TK133]; Australian Research Council Future Fellowship [FT150100024]; NSF CAREER grant [AST-1149491]

New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree

Abstract: Markers on the non-recombining portion of the human Y chromosome continue to have applications in many fields including evolutionary biology, forensics, medical genetics, and genealogical reconstruction. In 2002, the Y Chromosome Consortium published a single parsimony tree showing the relationships among 153 haplogroups based on 243 binary markers and devised a standardized nomenclature system to name lineages nested within this tree. Here we present an extensively revised Y chromosome tree containing 311 distinct haplogroups, including two new major haplogroups (S and T), and incorporating approximately 600 binary markers. We describe major changes in the topology of the parsimony tree and provide names for new and rearranged lineages within the tree following the rules presented by the Y Chromosome Consortium in 2002. Several changes in the tree topology have important implications for studies of human ancestry. We also present demography-independent age estimates for 11 of the major clades in the new Y chromosome tree.

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

Abstract: Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by � 60 days and in standard deviation by � 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS