Novel therapies blocking the renin–angiotensin–aldosterone system in the management of hypertension and related disorders
Bibliographic record
Abstract
Although significant advances have been made in the therapeutic blockade of the renin-angiotensin-aldosterone system (RAAS) using angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers and non-selective aldosterone receptor antagonists, there is a clear need for both additional blocking strategies and enhancements of current therapeutic approaches. Vasopeptidase inhibition may still find a role despite the small incremental value of this approach and the obvious issue of kinin-mediated adverse effects still to be fully addressed. Blockade of the RAAS upstream using renin inhibitors as well as the greater selectivity of aldosterone blockade using selective aldosterone blockers such as eplerenone are also novel approaches. Not yet in clinical use but certainly an attractive therapeutic target is angiotensin II growth factor receptor transactivation, with selective inhibitors having been developed for various specific kinase pathways. Finally, ACE2 augmentation, antisense gene strategies, and vaccination against the renin-angiotensin system should still be considered experimental, but have significant appeal as additional approaches to the blockade of this system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".