77 resultados para Negative dimensional integration method (NDIM)
Resumo:
Estrogen is a ligand for the estrogen receptor (ER), which on binding 17beta-estradiol, functions as a ligand-activated transcription factor and regulates the transcription of target genes. This is the slow genomic mode of action. However, rapid non-genomic actions of estrogen also exist at the cell membrane. Using a novel two-pulse paradigm in which the first pulse rapidly initiates non-genomic actions using a membrane-limited estrogen conjugate (E-BSA), while the second pulse promotes genomic transcription from a consensus estrogen response element (ERE), we have demonstrated that rapid actions of estrogen potentiate the slower transcriptional response from an ERE-reporter in neuroblastoma cells. Since rapid actions of estrogen activate kinases, we used selective inhibitors in the two-pulse paradigm to determine the intracellular signaling cascades important in such potentiation. Inhibition of protein kinase A (PKA), PKC, mitogen activated protein kinase (MAPK) or phosphatidylinositol 3-OH kinase (PI-3K) in the first pulse decreases potentiation of transcription. Also, our data with both dominant negative and constitutive mutants of Galpha subunits show that Galpha(q) initiates the rapid signaling cascade at the membrane in SK-N-BE(2)C neuroblastoma cells. We discuss two models of multiple kinase activation at the membrane Pulses of estrogen induce lordosis behavior in female rats. Infusion of E-BSA into the ventromedial hypothalamus followed by 17beta-estradiol in the second pulse could induce lordosis behavior, demonstrating the applicability of this paradigm in vivo. A model where non-genomic actions of estrogen couple to genomic actions unites both aspects of hormone action.
Resumo:
Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.