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Institution

University of Texas Southwestern Medical Center

HealthcareDallas, Texas, United States
About: University of Texas Southwestern Medical Center is a healthcare organization based out in Dallas, Texas, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 39107 authors who have published 75242 publications receiving 4497256 citations. The organization is also known as: UT Southwestern & UT Southwestern Medical School.
Topics: Population, Cancer, Medicine, Gene, Receptor


Papers
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Journal ArticleDOI
21 Jun 1979-Nature
TL;DR: It is now recognised that receptor-mediated endocytosis has a fundamental role in the growth, nutrition and differentiation of animal cells.
Abstract: Proteins and peptides can enter cells by receptor-mediated endocytosis, a coupled process by which selected extracellular proteins or peptides are first bound to specific cell surface receptors and then rapidly internalised by the cell. Internalisation follows clustering of the receptors in specialised regions of the cell surface called coated pits that invaginate to form intracellular coated vesicles. It is now recognised that receptor-mediated endocytosis has a fundamental role in the growth, nutrition and differentiation of animal cells.

1,956 citations

Journal ArticleDOI
15 May 2003-Nature
TL;DR: The results indicate that Bmi-1 is essential for the generation of self-renewing adult HSCs, which are required for haematopoiesis to persist for the lifetime of the animal.
Abstract: A central issue in stem cell biology is to understand the mechanisms that regulate the self-renewal of haematopoietic stem cells (HSCs), which are required for haematopoiesis to persist for the lifetime of the animal1. We found that adult and fetal mouse and adult human HSCs express the proto-oncogene Bmi-1. The number of HSCs in the fetal liver of Bmi-1-/- mice2 was normal. In postnatal Bmi-1-/- mice, the number of HSCs was markedly reduced. Transplanted fetal liver and bone marrow cells obtained from Bmi-1-/- mice were able to contribute only transiently to haematopoiesis. There was no detectable self-renewal of adult HSCs, indicating a cell autonomous defect in Bmi-1-/- mice. A gene expression analysis revealed that the expression of stem cell associated genes3, cell survival genes, transcription factors, and genes modulating proliferation including p16Ink4a and p19Arf was altered in bone marrow cells of the Bmi-1-/- mice. Expression of p16Ink4a and p19Arf in normal HSCs resulted in proliferative arrest and p53-dependent cell death, respectively. Our results indicate that Bmi-1 is essential for the generation of self-renewing adult HSCs.

1,934 citations

Journal ArticleDOI
TL;DR: An extensive study of 59 ligands interacting with six different proteins finds that MM/PBSA can serve as a powerful tool in drug design, where correct ranking of inhibitors is often emphasized, and the accuracy of the binding free energies calculated by three Generalized Born (GB) models is evaluated.
Abstract: The Molecular Mechanics/Poisson−Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/lig...

1,926 citations

Journal ArticleDOI
TL;DR: Analysis of sensitivity to change in symptom severity in an open-label trial of fluoxetine showed that the IDs-C and IDS-SR were highly related to the 17-item Hamilton Rating Scale for Depression.
Abstract: The psychometric properties of the 28- and 30-item versions of the Inventory of Depressive Symptomatology, Clinician-Rated (IDS-C) and Self-Report (IDS-SR) are reported in a total of 434 (28-item) and 337 (30-item) adult out-patients with current major depressive disorder and 118 adult euthymic subjects (15 remitted depressed and 103 normal controls). Cronbach's alpha ranged from 0.92 to 0.94 for the total sample and from 0.76 to 0.82 for those with current depression. Item total correlations, as well as several tests of concurrent and discriminant validity are reported. Factor analysis revealed three dimensions (cognitive/mood, anxiety/arousal and vegetative) for each scale. Analysis of sensitivity to change in symptom severity in an open-label trial of fluoxetine (N = 58) showed that the IDS-C and IDS-SR were highly related to the 17-item Hamilton Rating Scale for Depression. Given the more complete item coverage, satisfactory psychometric properties, and high correlations with the above standard ratings, the 30-item IDS-C and IDS-SR can be used to evaluate depressive symptom severity. The availability of similar item content for clinician-rated and self-reported versions allows more direct evaluations of these two perspectives.

1,921 citations

Journal ArticleDOI
TL;DR: This guide provides a nonstatistical audience with a methodological approach for building, interpreting, and using nomograms to estimate cancer prognosis or other health outcomes.
Abstract: Nomograms are widely used for cancer prognosis, primarily because of their ability to reduce statistical predictive models into a single numerical estimate of the probability of an event, such as death or recurrence, that is tailored to the profile of an individual patient. User-friendly graphical interfaces for generating these estimates facilitate the use of nomograms during clinical encounters to inform clinical decision making. However, the statistical underpinnings of these models require careful scrutiny, and the degree of uncertainty surrounding the point estimates requires attention. This guide provides a nonstatistical audience with a methodological approach for building, interpreting, and using nomograms to estimate cancer prognosis or other health outcomes.

1,917 citations


Authors

Showing all 39410 results

NameH-indexPapersCitations
Eugene Braunwald2301711264576
Joseph L. Goldstein207556149527
Eric N. Olson206814144586
Craig B. Thompson195557173172
Thomas C. Südhof191653118007
Scott M. Grundy187841231821
Michael S. Brown185422123723
Eric Boerwinkle1831321170971
Jiaguo Yu178730113300
John J.V. McMurray1781389184502
Eric J. Nestler178748116947
John D. Minna169951106363
Yuh Nung Jan16246074818
Andrew P. McMahon16241590650
Elliott M. Antman161716179462
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023114
2022407
20215,247
20204,674
20194,094
20183,400