Involvement of kinins, AT(1-7), ACSDKP in the beneficial therapeutic effects of converting enzyme inhibitors
Bibliographic record
Abstract
In addition to angiotensins, other endogenous agents, especially vasodilators, have been implicated in the cardiovascular effects of the angiotensin-converting enzyme inhibitors (ACEi). Bradykinin (BK) and related kinins, AT(1-7) and AcSDKP, a negative regulator of hematopoiesis, are the most important and efficient agents. They have been studied a) as substrates or inhibitors of the purified converting enzyme from the rabbit lung; b) as potentiators (AT(1-7), AcSDKP) of the myotropic effect of BK in the rabbit isolated jugular vein (rbJV) or as inhibitors of the myotropic effect of angiotensin I in the rabbit aorta (rbA). Hypothetical interactions between ACEi and the B2 receptor (crosstalk) and the antagonism of the AT1 receptor by AT(1-7) and AcSDKP have also been looked upon. Results indicate that AT(1-7) is an inhibitor of ACE of average-low potency and is a very weak antagonist of the AT1 receptor. AcSDKP is not active either as inhibitor of ACE or as antagonist of the AT1 receptor. This compound is also inactive as potentiator of the myotropic effect of BK on the rbJV and as inhibitor of AT1 in the rbA. Crosstalk between ACE and the kinin B2 receptor could not be demonstrated since changes of BK activities in desensitized tissues (rbJV) were compatible with the block of BK degradation by ACEi.
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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 | 0.000 | 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 | 0.001 |
| 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".