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.

Circulating Tumor Cells versus Imaging—Predicting Overall Survival in Metastatic Breast Cancer

Abstract: Purpose: The presence of ≥5 circulating tumor cells (CTC) in 7.5 mL blood from patients with measurable metastatic breast cancer before and/or after initiation of therapy is associated with shorter progression-free and overall survival. In this report, we compared the use of CTCs to radiology for prediction of overall survival. Experimental Design: One hundred thirty-eight metastatic breast cancer patients had imaging studies done before and a median of 10 weeks after the initiation of therapy. All scans were centrally reviewed by two independent radiologists using WHO criteria to determine radiologic response. CTC counts were determined ∼4 weeks after initiation of therapy. Specimens were analyzed at one of seven laboratories and reviewed by a central laboratory. Results: Interreader variability for radiologic responses and CTC counts were 15.2% and 0.7%, respectively. The median overall survival of 13 (9%) patients with radiologic nonprogression and ≥5 CTCs was significantly shorter than that of the 83 (60%) patients with radiologic nonprogression and P = 0.0389). The median overall survival of the 20 (14%) patients with radiologic progression and P = 0.0039). Conclusions: Assessment of CTCs is an earlier, more reproducible indication of disease status than current imaging methods. CTCs may be a superior surrogate end point, as they are highly reproducible and correlate better with overall survival than do changes determined by traditional radiology.

Amazon rainforests green‐up with sunlight in dry season

Abstract: Received 23 December 2005; revised 6 February 2006; accepted 8 February 2006; published 22 March 2006. [1] Metabolism and phenology of Amazon rainforests significantly influence global dynamics of climate, carbon and water, but remain poorly understood. We analyzed Amazon vegetation phenology at multiple scales with Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements from 2000 to 2005. MODIS Enhanced Vegetation Index (EVI, an index of canopy photosynthetic capacity) increased by 25% with sunlight during the dry season across Amazon forests, opposite to ecosystem model predictions that water limitation should cause dry season declines in forest canopy photosynthesis. In contrast to intact forests, areas converted to pasture showed dry-season declines in EVI-derived photosynthetic capacity, presumably because removal of deep-rooted forest trees reduced access to deep soil water. Local canopy photosynthesis measured from eddy flux towers in both a rainforest and forest conversion site confirm our interpretation of satellite data, and suggest that basin-wide carbon fluxes can be constrained by integrating remote sensing and local flux measurements. Citation: Huete, A. R., K. Didan, Y. E. Shimabukuro, P. Ratana, S. R. Saleska, L. R. Hutyra, W. Yang, R. R. Nemani, and R. Myneni (2006), Amazon rainforests green-up with sunlight in dry season, Geophys. Res. Lett., 33, L06405, doi:10.1029/2005GL025583.

Low-Fat Dietary Pattern and Risk of Invasive Breast Cancer: The Women's Health Initiative Randomized Controlled Dietary Modification Trial

Abstract: ContextThe hypothesis that a low-fat dietary pattern can reduce breast cancer risk has existed for decades but has never been tested in a controlled intervention trial.ObjectiveTo assess the effects of undertaking a low-fat dietary pattern on breast cancer incidence.Design and SettingA randomized, controlled, primary prevention trial conducted at 40 US clinical centers from 1993 to 2005.ParticipantsA total of 48 835 postmenopausal women, aged 50 to 79 years, without prior breast cancer, including 18.6% of minority race/ethnicity, were enrolled.InterventionsWomen were randomly assigned to the dietary modification intervention group (40% [n = 19 541]) or the comparison group (60% [n = 29 294]). The intervention was designed to promote dietary change with the goals of reducing intake of total fat to 20% of energy and increasing consumption of vegetables and fruit to at least 5 servings daily and grains to at least 6 servings daily. Comparison group participants were not asked to make dietary changes.Main Outcome MeasureInvasive breast cancer incidence.ResultsDietary fat intake was significantly lower in the dietary modification intervention group compared with the comparison group. The difference between groups in change from baseline for percentage of energy from fat varied from 10.7% at year 1 to 8.1% at year 6. Vegetable and fruit consumption was higher in the intervention group by at least 1 serving per day and a smaller, more transient difference was found for grain consumption. The number of women who developed invasive breast cancer (annualized incidence rate) over the 8.1-year average follow-up period was 655 (0.42%) in the intervention group and 1072 (0.45%) in the comparison group (hazard ratio, 0.91; 95% confidence interval, 0.83-1.01 for the comparison between the 2 groups). Secondary analyses suggest a lower hazard ratio among adherent women, provide greater evidence of risk reduction among women having a high-fat diet at baseline, and suggest a dietary effect that varies by hormone receptor characteristics of the tumor.ConclusionsAmong postmenopausal women, a low-fat dietary pattern did not result in a statistically significant reduction in invasive breast cancer risk over an 8.1-year average follow-up period. However, the nonsignificant trends observed suggesting reduced risk associated with a low-fat dietary pattern indicate that longer, planned, nonintervention follow-up may yield a more definitive comparison.Clinical Trials RegistrationClinicalTrials.gov Identifier: NCT00000611

Enzo: an adaptive mesh refinement code for astrophysics

Abstract: This paper describes the open-source code Enzo, which uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows. The code is Cartesian, can be run in one, two, and three dimensions, and supports a wide variety of physics including hydrodynamics, ideal and non-ideal magnetohydrodynamics, N-body dynamics (and, more broadly, self-gravity of fluids and particles), primordial gas chemistry, optically thin radiative cooling of primordial and metal-enriched plasmas (as well as some optically-thick cooling models), radiation transport, cosmological expansion, and models for star formation and feedback in a cosmological context. In addition to explaining the algorithms implemented, we present solutions for a wide range of test problems, demonstrate the code's parallel performance, and discuss the Enzo collaboration's code development methodology.

Phase-shifting speckle interferometry

Abstract: Speckle patterns have high frequency phase data, which make it difficult to find the absolute phase of a single speckle pattern; however, the phase of the difference between two correlated speckle patterns can be determined. This is done by applying phase-shifting techniques to speckle interferometry, which will quantitatively determine the phase of double-exposure speckle measurements. The technique uses computer control to take data and calculate phase without an intermediate recording step. The randomness of the speckle causes noisy data points which are removed by data processing routines. One application of this technique is finding the phase of deformations, where up to ten waves of wavefront deformation can easily be measured. Results of deformations caused by tilt of a metal plate and a disbond in a honeycomb structure brazed to an aluminum plate are shown.