Research Triangle Park

About: Research Triangle Park is a nonprofit organization based out in Durham, North Carolina, United States. It is known for research contribution in the topics: Population & Receptor. The organization has 24961 authors who have published 35800 publications receiving 1684504 citations. The organization is also known as: RTP.

Cross-Talk between Nuclear Factor-κB and the Steroid Hormone Receptors: Mechanisms of Mutual Antagonism

Abstract: Nuclear factor κB (NF-κB) is an inducible transcription factor that positively regulates the expression of proimmune and proinflammatory genes, while glucocorticoids are potent suppressors of immune and inflammatory responses. NF-κB and the glucocorticoid receptor (GR) physically interact, resulting in repression of NF-κB transactivation. In transient cotransfection experiments, we demonstrate a dose-dependent, mutual antagonism between NF-κB and GR. Functional dissection of the NF-κB p50 and p65 subunits and deletion mutants of GR indicate that the GR antagonism is specific to the p65 subunit of NF-κB heterodimer, whereas multiple domains of GR are essential to repress p65-mediated transactivation. Despite its repression of GR transactivation, p65 failed to block the transrepressive GR homologous down-regulation function. We also demonstrate that negative interactions between p65 and GR are not selective for GR, but also occur between NF-κB and androgen, progesterone B, and estrogen receptors. However, a...

Multiple Opiate Receptors: Different Regional Distribution in the Brain and Differential Binding of Opiates and Opioid Peptides

Abstract: In rat brain membrane preparations, the parenterally and orally active peptide, [D-Ala2, MePhe4, Met(O)5-ol]-enkephalin, binds to morphine receptor sites ([3H]naloxone or [3H]dihydromorphine binding sites) with an affinity higher than that for enkephalin receptor sites ([125I] [D-Ala2, D-Leu5]-enkephalin binding sites). [125I] [D-Ala2, MePhe4, Met(O)5-ol]-enkephalin binds to morphine receptor sites stereospecifically, in a saturable manner and with characteristics similar to that of [3H]dihydromorphine; this ligand can be used as an 125I-labeled probe to measure specific binding to morphine receptor sites. Na+ decreases and Mn2+ increases the binding capacity with a concomitant reduction of affinity for [125I] [D-Ala2, MePhe4, Met(O)5-ol]-enkephalin. This peptide does not bind to neuroblastoma cells with high affinity. The brain regional distribution of binding of [125I] [D-Ala2, MePhe4, Met(O)5-ol]-enkephalin or [3H]naloxone and [125I] [D-Ala2, D-Leu5]-enkephalin are different. The differential potency of binding of opiate agonists, antagonists, mixed agonist-antagonists, enkephalins and enkephalin analogues is studied by competition of binding of [3H]naloxone or [125I] [D-Ala2, MePhe4, Met(O)5-ol]-enkephalin (morphine receptor) and of [125I] [D-Ala2, D-Leu5]-enkephalin sites (enkephalin receptor). All of these results support the contention that there are multiple opiate receptors with differing characteristics.

Metabolomics enables precision medicine: "A White Paper, Community Perspective"

Abstract: Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or “-omics” level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person’s metabolic state provides a close representation of that individual’s overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject’s response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient’s metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its “Precision Medicine and Pharmacometabolomics Task Group”, with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.