Mechanical load-induced alterations in B-type natriuretic peptide gene expression
Bibliographic record
Abstract
Atrial natriuretic peptide (ANP), B-type natriuretic peptide (BNP), and C-type natriuretic peptide are the known members of the mammalian natriuretic peptide system. Like ANP, BNP is a natriuretic and diuretic hormone that also causes peripheral vasodilation and inhibition of the sympathetic and renin-angiotensin systems. Although originally isolated from porcine brain, the BNP gene is expressed in a specific manner in cardiac myocytes in both the atria and the ventricles, but it is mainly released from the ventricles. The major determinant of BNP secretion is wall stretch, and the levels of BNP mRNA increase substantially in response to cardiac overload. In the clinical setting, BNP appears to be the most powerful neurohumoral predictor of left-ventricular function and prognosis. An acute increase in BNP gene expression occurs within 1 h and mimics the rapid induction of proto-oncogenes in response to hemodynamic stress. BNP can be used as a myocyte-specific marker to identify mechanisms that couple acute mechanical overload to alterations in cardiac gene expression. This paper is focused on the mechanisms that regulate BNP gene expression in cardiac overload. Particularly, autocrine-paracrine factors as well as cytoplasmic signaling pathways and transcription factors involved in mechanical stretch-induced BNP gene expression are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".