The biased signaling has been extensively studied in the original mu opioid receptor (MOR-1), particularly through G protein and β-arrestin2 signaling pathways. The concept that the G protein pathway is often linked to the therapeutic effect of the drug, while the β-arrestin pathway is associated to the side effects has been proposed to develop biased analgesic compounds with limited side-effects associated with traditional opiates. The mu opioid receptor gene, OPRM1, undergoes extensive alternative pre-mRNA splicing, generating multiple splice variants or isoforms that are conserved from rodent to human. One type of the Oprm1 splice variants are the full-length 7 transmembrane (7TM) C-terminal splice variants, which have identical receptor structures including entire binding pocket, but contain a different intracellular C-terminal tail resulted from 3' alternative splicing. Increasing evidence suggest that these full-length 7TM C-terminal variants play important roles in mu opioid pharmacology, raising questions regarding biased signaling at these multiple C-terminal variants. In the present study, we investigated the effect of different C-terminal variants on mu agonist-induced G protein coupling, β-arrestin2 recruitment, and ultimately, signaling bias. We found that mu agonists produced marked differences in G protein activation and β-arrestin2 recruitment among various C-terminal variants, leading to biased signaling at various level. Particularly, MOR-1O, an exon 7-associated variant, showed greater β-arrestin2 bias for most mu agonists than MOR-1, an exon 4-associated variant. Biased signaling of G protein-coupled receptors has been defined by evidences that different agonists can produce divergent signaling transduction pathways through a single receptor. Our findings that a single mu agonist can induce differential signaling through multiple 7TM splice variants provide a new perspective on biased signaling at least for Oprm1, which perhaps is important for our understanding of the complex mu opioid actions in vivo where all the 7TM splice variants co-exist.
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http://dx.doi.org/10.1007/s10571-020-00973-5 | DOI Listing |
Front Public Health
January 2025
Karolinska Institutet, Department of Medicine Solna, Division of Clinical Epidemiology, Stockholm, Sweden.
Background: Mexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analysis methods.
Purpose: To explore if multimodal machine learning can enhance identifying predictive features from obesogenic environments and investigating complex disease or social patterns, using the Mexican National Health and Nutrition Survey.
Behav Res Methods
January 2025
Methods Center, Eberhard Karls University of Tübingen, Haußerstr. 11, 72076, Tübingen, Germany.
Due to the increased availability of intensive longitudinal data, researchers have been able to specify increasingly complex dynamic latent variable models. However, these models present challenges related to overfitting, hierarchical features, non-linearity, and sample size requirements. There are further limitations to be addressed regarding the finite sample performance of priors, including bias, accuracy, and type I error inflation.
View Article and Find Full Text PDFPersonal Ment Health
February 2025
Department of Clinical, Educational and Health Psychology, University College London, London, UK.
This paper applies error management theory (EMT) (Haselton and Buss 2000) to explore how disruptions in epistemic trust-trust in communicated information-can be understood as adaptive responses to early adversity in individuals with borderline personality disorder (BPD). I propose that epistemic mistrust (EM) and epistemic credulity (EC), characterized by inappropriate trust patterns, arise from the differential costs of trusting unreliable versus mistrusting reliable information. Although these biases may seem maladaptive, they function as evolutionary survival mechanisms in response to harsh environments.
View Article and Find Full Text PDFReceptors for the vasoactive adipokine apelin, termed APJ receptors, are G-protein-coupled receptors and are widely expressed throughout the cardiovascular system. APJ receptors can also signal via G-protein-independent pathways, including G-protein-coupled-receptor kinase 2 (GRK2), which inhibits nitric oxide synthase (eNOS) activity and nitric oxide (NO) production in endothelial cells. Apelin causes endothelium-dependent, NO-mediated relaxation of coronary arteries from normotensive animals, but the effects of activating APJ receptor signaling pathways in hypertensive coronary arteries are largely unknown.
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