A quantitative trait locus for aortic smooth muscle cell number acting independently of blood pressure: implicating the angiotensin receptor AT1B gene as a candidate
Bibliographic record
Abstract
Vascular hyperplasia may be involved in the remodeling of vasculature. It was unknown whether there were genetic determinants for aortic smooth muscle cell number (SMCN) and, if so, whether they acted independently of those for blood pressure (BP). To unravel this issue, we utilized congenic strains previously constructed for BP studies. These strains were made by replacing various chromosome 2 segments of the Dahl salt-sensitive (S) rat with those of the Milan normotensive rat (MNS). We measured and compared SMCN in aortic cross-sectional areas and BPs of these strains. Consequently, a quantitative trait locus (QTL) for SMCN was localized to a chromosome region not containing a BP QTL, but harboring the locus for the angiotensin II receptor AT1B (Agtr1b). Agtr1b became a candidate for the SMCN QTL because 1) two significant mutations were found in the coding region between S and all congenic strains possessing the MNS alleles, and 2) contractile responses to angiotensin II were significantly and selectively reduced in congenic rats harboring the MNS alleles of the SMCN QTL compared with S rats. The current investigation presents the first line of evidence that a QTL for aortic SMCN exists, and it acts independently of QTLs for BP. The relevant congenic strains developed therein potentially provide novel mammalian models for the studies of vascular remodeling disorders.
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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 | 0.001 | 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) | 0.001 | 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".