C‐type natriuretic peptide activates a non‐selective cation current in acutely isolated rat cardiac fibroblasts via natriuretic peptide C receptor‐mediated signalling
Bibliographic record
Abstract
In the heart, fibroblasts play an essential role in the deposition of the extracellular matrix and they also secrete a number of hormonal factors. Although natriuretic peptides, including C-type natriuretic peptide (CNP) and brain natriuretic peptide, have antifibrotic effects on cardiac fibroblasts, the effects of CNP on fibroblast electrophysiology have not been examined. In this study, acutely isolated ventricular fibroblasts from the adult rat were used to measure the effects of CNP (2 x 10(-8) M) under whole-cell voltage-clamp conditions. CNP, as well as the natriuretic peptide C receptor (NPR-C) agonist cANF (2 x 10(-8) M), significantly increased an outwardly rectifying non-selective cation current (NSCC). This current has a reversal potential near 0 mV. Activation of this NSCC by cANF was abolished by pre-treating fibroblasts with pertussis toxin, indicating the involvement of G(i) proteins. The cANF-activated NSCC was inhibited by the compounds Gd(3+), SKF 96365 and 2-aminoethoxydiphenyl borate. Quantitative RT-PCR analysis of mRNA from rat ventricular fibroblasts revealed the expression of several transient receptor potential (TRP) channel transcripts. Additional electrophysiological analysis showed that U73122, a phospholipase C antagonist, inhibited the cANF-activated NSCC. Furthermore, the effects of CNP and cANF were mimicked by the diacylglycerol analogue 1-oleoyl-2-acetyl-sn-glycerol (OAG), independently of protein kinase C activity. These are defining characteristics of specific TRPC channels. More detailed molecular analysis confirmed the expression of full-length TRPC2, TRPC3 and TRPC5 transcripts. These data indicate that CNP, acting via the NPR-C receptor, activates a NSCC that is at least partially carried by TRPC channels in cardiac fibroblasts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".