Phospholipase C signaling tonically represses basal atrial natriuretic factor secretion from the atria of the heart
Bibliographic record
Abstract
The cardiac hormone atrial natriuretic factor (ANF or ANP) plays significant, well-established roles in a large number of physiological and pathophysiological processes, including water and electrolyte balance, blood pressure regulation, and cardiovascular growth. Understanding the regulation of its production and secretion by atrial cardiomyocytes is incomplete. We have previously established a significant role of G(i/o) protein signaling in modulating ANF secretion as promoted by stretch of the atrial myocardium. In the present study, we investigated the role of G(q) protein signaling and its relationship to G(i/o) protein signaling using pharmacological manipulation of proximal effectors of G(αq) in an ex vivo model of spontaneously beating rat atria. Phospholipase C (PLC) and protein kinase C (PKC) inhibitors dramatically increased basal secretion of ANF. Furthermore, although atrial wall stretch is a potent stimulus for secretion, stretch unexpectedly reduced ANF secretion to basal levels under PLC and PKC inhibitory conditions. Inhibition of the inositol triphosphate receptor did not appear to affect basal secretion but dose-dependently blocked stretch-secretion coupling. The results obtained demonstrate that the PLC and PKC signaling cascades play important albeit unexpected roles in the regulation of basal and stimulated ANF secretion and suggest interplay between the G(q) and G(i/o) protein signaling pathways.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".