The renin-angiotensin system: going beyond the classical paradigms
Bibliographic record
Abstract
Thirty years ago, a novel axis of the renin-angiotensin system (RAS) was unveiled by the discovery of angiotensin-(1−7) [ANG-(1−7)] generation in vivo. Later, angiotensin-converting enzyme 2 (ACE2) was shown to be the main mediator of this reaction, and Mas was found to be the receptor for the heptapeptide. The functional analysis of this novel axis of the RAS that followed its discovery revealed numerous protective actions in particular for cardiovascular diseases. In parallel, similar protective actions were also described for one of the two receptors of ANG II, the ANG II type 2 receptor (AT 2 R), in contrast to the other, the ANG II type 1 receptor (AT 1 R), which mediates deleterious actions of this peptide, e.g., in the setting of cardiovascular disease. Very recently, another branch of the RAS was discovered, based on angiotensin peptides in which the amino-terminal aspartate was replaced by alanine, the alatensins. Ala-ANG-(1−7) or alamandine was shown to interact with Mas-related G protein-coupled receptor D, and the first functional data indicated that this peptide also exerts protective effects in the cardiovascular system. This review summarizes the presentations given at the International Union of Physiological Sciences Congress in Rio de Janeiro, Brazil, in 2017, during the symposium entitled “The Renin-Angiotensin System: Going Beyond the Classical Paradigms,” in which the signaling and physiological actions of ANG-(1−7), ACE2, AT 2 R, and alatensins were reported (with a focus on noncentral nervous system-related tissues) and the therapeutic opportunities based on these findings were discussed.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| 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".