Intracrine signaling through lipid mediators and their cognate nuclear G-protein-coupled receptors: a paradigm based on PGE<sub>2</sub>, PAF, and LPA<sub>1</sub>receptorsThis paper is one of a selection of papers published in this Special Issue, entitled The Nucleus: A Cell Within A Cell.
Bibliographic record
Abstract
Prostaglandins (PGs), platelet-activating factor (PAF), and lysophosphatidic acid (LPA) are ubiquitous lipid mediators that play important roles in inflammation, cardiovascular homeostasis, and immunity and are also known to modulate gene expression of specific pro-inflammatory genes. The mechanism of action of these lipids is thought to be primarily dependent on their specific plasma membrane receptors belonging to the superfamily of G-protein-coupled receptors (GPCR). Increasing evidence suggests the existence of a functional intracellular GPCR population. It has been proposed that immediate effects are mediated via cell surface receptors whereas long-term responses are dependent upon intracellular receptor effects. Indeed, receptors for PAF, LPA, and PGE(2) (specifically EP(1), EP(3), and EP(4)) localize at the cell nucleus of cerebral microvascular endothelial cells of newborn pigs, rat hepatocytes, and cells overexpressing each receptor. Stimulation of isolated nuclei with these lipids reveals biological functions including transcriptional regulation of major genes, namely c-fos, cylooxygenase-2, and endothelial as well as inducible nitric oxide synthase. In the present review, we shall focus on the nuclear localization and signaling of GPCRs recognizing PGE(2), PAF, and LPA phospholipids as ligands. Mechanisms on how nuclear PGE2, PAF, and LPA receptors activate gene transcription and nuclear localization pathways are presented. Intracrine signaling for lipid mediators uncover novel pathways to elicit their effects; accordingly, intracellular GPCRs constitute a distinctive mode of action for gene regulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".