American journal of physiology. Endocrinology and metabolism
-
Am. J. Physiol. Endocrinol. Metab. · Mar 2012
ReviewTackling endothelial dysfunction by modulating NOS uncoupling: new insights into its pathogenesis and therapeutic possibilities.
Endothelial nitric oxide synthase (eNOS) serves as a critical enzyme in maintaining vascular pressure by producing nitric oxide (NO); hence, it has a crucial role in the regulation of endothelial function. The bioavailability of eNOS-derived NO is crucial for this function and might be affected at multiple levels. ⋯ Therefore, modulating eNOS uncoupling by stabilizing eNOS activity, enhancing its substrate, cofactors, and transcription, and reversing uncoupled eNOS are attractive therapeutic approaches to improve endothelial function. This review provides an extensive overview of the important role of eNOS uncoupling in the pathogenesis of endothelial dysfunction and the potential therapeutic interventions to modulate eNOS for tackling endothelial dysfunction.
-
Am. J. Physiol. Endocrinol. Metab. · Sep 2008
ReviewWhy are we shaped differently, and why does it matter?
Body fat distribution is an important predictor of metabolic abnormalities in obese humans. Dysregulation of free fatty acid (FFA) release, especially from upper body subcutaneous adipose tissue, appears to contribute substantially to these metabolic disturbances. ⋯ Regional variations in the storage of fatty acids, both meal derived and direct reuptake, and storage of circulating FFAs that may help to explain why some depots expand at the expense of others have been reported. We review the quantitative data on regional lipolysis, meal, and FFA storage in adults to provide an overview of fat balance differences in adults with different fat distribution patterns.
-
Am. J. Physiol. Endocrinol. Metab. · Apr 2004
ReviewTen categories of statistical errors: a guide for research in endocrinology and metabolism.
A simple framework is introduced that defines ten categories of statistical errors on the basis of type of error, bias or imprecision, and source: sampling, measurement, estimation, hypothesis testing, and reporting. Each of these ten categories is illustrated with examples pertinent to research and publication in the disciplines of endocrinology and metabolism. Some suggested remedies are discussed, where appropriate. A review of recent issues of American Journal of Physiology: Endocrinology and Metabolism and of Endocrinology finds that very small sample sizes may be the most prevalent cause of statistical error in this literature.