Effect of inter-renal aortic coarctation-induced hypertension on function and expression of vascular α<sub>1A</sub>- and α<sub>1D</sub>-adrenoceptors
Bibliographic record
Abstract
We investigated the effect of inter-renal aortic coarctation on the function and expression of vascular α(1A)- and α(1D)-adrenoceptors and plasma angiotensin II (ATII) in rats. Male Wistar rats, either sham operated (SO), or with aortic coarctation for 7 (AC7) and 14 days (AC14) were used for agonist-induced pressor responses in vehicle (physiological saline)- and antagonist-treated anesthetized animals, immunoblot analysis (α(1A)- and α(1D)-adrenoceptor in aorta and caudal arteries), and immunoassay (plasma ATII). The α(1D)-adrenoceptor antagonist, BMY-7378 (BMY) blocked noradrenaline-induced responses in the order SO > AC7 ≫ AC14; in contrast, the α(1A)-adrenoceptor antagonist RS-100329 (RS), produced a marginal shift to the right of the dose-response curve to noradrenaline, along with a strong decrease of the maximum pressor effect in the order SO > AC7 = AC14. The potency of the α(1A)-adrenoceptor agonist A-61603 increased in rats with AC14, and responses were inhibited by RS in the order AC14 > AC7 > SO. In aorta, α(1D)-adrenoceptor protein increased in AC7 and decreased in AC14; α(1A)-adrenoreceptor protein increased in the caudal artery of AC7 and returned to control values in AC14. Plasma ATII increased in AC7 and AC14, compared with SO rats. These results suggest an early and direct relationship between ATII and α(1D)-adrenoreceptors in the development of hypertension in this experimental model.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".