Altered expression of natriuretic peptide receptors in proANP gene disrupted mice
Bibliographic record
Abstract
BACKGROUND: The atrial natriuretic peptide (ANP) family is a complex system consisting of at least three polypeptides and at least three types of receptor. Each peptide interacts with different types of receptor at varying degrees of affinity. To determine if natriuretic peptide levels influence natriuretic peptide receptor expression and regulation, we examined the expression of guanylyl cyclase linked GC-A, GC-B and C-receptor in the lungs of mice with a mutation that inactivates the ANP gene (Nppa). METHODS: The mRNA level of GC-A, GC-B and C-receptor in the lung were studied by ribonuclease protection assays (RPA). RESULTS: Results of RPA showed that although the mRNA level of GC-A and GC-B of heterozygous ANP+/- was not different from wild type ANP+/+ mice, they were significantly higher in the homozygous mutant ANP-/- mice. In addition, C-receptor mRNA level in ANP+/- and ANP-/- was significantly lower than ANP+/+ mice. The C-receptor results were confirmed by receptor binding assays and affinity cross-linking studies. CONCLUSIONS: Taken together these data suggest that permanent removal of ANP from the natriuretic peptide system results in an up-regulation of GC-A and GC-B, and a corresponding down-regulation of C-receptor in the lung of proANP gene disrupted mice. We postulated that changes in the natriuretic peptide receptor population may result in chronic hypertension and cardiac hypertrophy in the ANP-/- mice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".