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Institution

University of Texas Health Science Center at Houston

EducationHouston, Texas, United States
About: University of Texas Health Science Center at Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 27309 authors who have published 42520 publications receiving 2151596 citations. The organization is also known as: UTHealth & The UT Health Science Center at Houston.


Papers
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Journal ArticleDOI
TL;DR: The role of AMPK activation in regulating protein synthesis during both phenylephrine- and Akt-induced cardiac hypertrophy is investigated and data suggest that the inhibition of protein synthesis by pharmacological activation of AM PK may be a key regulatory mechanism by which hypertrophic growth can be controlled.

328 citations

Journal ArticleDOI
TL;DR: In this paper, the authors presented data on neurologic recovery gathered by the Model Spinal Cord Injury (SCI) Systems over a 10-year period. And they found that SCI caused by violence is more likely than SCI from nonviolent etiologies to result in a complete injury.

328 citations

Journal ArticleDOI
TL;DR: These algorithms for the treatment of BDI represent the recommendations based on the most recent evidence available and are meant to provide a framework for clinical decision making, not to replace clinical judgment.
Abstract: Background A panel consisting of academic psychiatrists and pharmacist administrators of the Texas Department of State Health Services (formerly Texas Department of Mental Health and Mental Retardation), community mental health physicians, advocates, and consumers met in May 2004 to review new evidence in the pharmacologic treatment of bipolar I disorder (BDI). The goal of the consensus conference was to update and revise the current treatment algorithm for BDI as part of the Texas Implementation of Medication Algorithms, a statewide quality assurance program for the treatment of major psychiatric illness. The guidelines for evaluating possible medications, the criteria for selection and ranking, and the updated algorithms are described. Method Principles from previous consensus conferences were reviewed and amended. Medication algorithms for the acute treatment of hypomanic/manic or mixed and depressive episodes in BDI were developed after examining recent efficacy and safety and tolerability data. Recommendations for maintenance treatments were developed. Results The panel updated the 2 primary algorithms (hypomanic/manic/mixed and depressive) based on clinical evidence for efficacy, tolerability, and safety developed since 2000. Expert consensus was utilized where clinical evidence was limited. Prevention of new episodes or prophylaxis treatment recommendations were developed based on recent data from longer-term trials. Maintenance recommendations are provided as levels versus a specified staged algorithm, as for acute treatment, due to the relatively limited database to inform treatment. Conclusions These algorithms for the treatment of BDI represent the recommendations based on the most recent evidence available. These recommendations are meant to provide a framework for clinical decision making, not to replace clinical judgment. As with any algorithm, treatment practices will evolve beyond the recommendations of this consensus conference as new evidence and additional medications become available.

328 citations

Journal ArticleDOI
TL;DR: Standardized susceptibility testing for selected organism-drug combinations has been shown to have similar predictive utility, and antifungal susceptibility testing is now increasingly and appropriately used as a routine adjunct to the treatment of fungal infections.
Abstract: The in vitro susceptibility of an infecting organism to the antimicrobial agent selected for therapy is one of several factors that influence the likelihood that therapy for an infection will be successful. To appreciate the value of antifungal susceptibility testing, it is helpful to review the overall predictive utility of antibacterial susceptibility testing. After >30 years of study, in vitro susceptibility can be said to predict the response of bacterial infections with an accuracy that is well summarized as the "90-60 rule": infections due to susceptible isolates respond to therapy approximately 90% of the time, whereas infections due to resistant isolates respond approximately 60% of the time. On the basis of a growing body of knowledge, standardized susceptibility testing for selected organism-drug combinations (most notably, Candida species and the azole antifungal agents) has been shown to have similar predictive utility. Antifungal susceptibility testing is now increasingly and appropriately used as a routine adjunct to the treatment of fungal infections.

328 citations

Journal ArticleDOI
TL;DR: The results suggest that MCs and TCs transmit temporally distinct odor information to different OC targets, and in anterior OC areas, the two cell types projected to segregated subareas.
Abstract: Odor signals are conveyed from the olfactory bulb to the olfactory cortex (OC) by mitral cells (MCs) and tufted cells (TCs). However, whether and how the two types of projection neuron differ in function and axonal connectivity is still poorly understood. Odor responses and axonal projection patterns were compared between MCs and TCs in mice by visualizing axons of electrophysiologically identified single neurons. TCs demonstrated shorter onset latency for reliable responses than MCs. The shorter latency response of TCs was maintained in a wide range of odor concentrations, whereas MCs responded only to strong signals. Furthermore, individual TCs projected densely to focal targets only in anterior areas of the OC, whereas individual MCs dispersedly projected to all OC areas. Surprisingly, in anterior OC areas, the two cell types projected to segregated subareas. These results suggest that MCs and TCs transmit temporally distinct odor information to different OC targets.

327 citations


Authors

Showing all 27450 results

NameH-indexPapersCitations
Paul M. Ridker2331242245097
Eugene Braunwald2301711264576
Eric N. Olson206814144586
Hagop M. Kantarjian2043708210208
André G. Uitterlinden1991229156747
Gordon B. Mills1871273186451
Eric Boerwinkle1831321170971
Bruce M. Psaty1811205138244
Aaron R. Folsom1811118134044
Daniel R. Weinberger177879128450
Bharat B. Aggarwal175706116213
Richard A. Gibbs172889249708
Russel J. Reiter1691646121010
James F. Sallis169825144836
Steven N. Blair165879132929
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
2022231
20213,048
20202,807
20192,467
20182,224