Impact of angiotensin-receptor blockers on intrarenal renin-angiotensin system activity in hypertension: A PK/PD modelling study
Bibliographic record
Abstract
Abstract The renin-angiotensin system (RAS) is a primary regulator of volume homeostasis and blood pressure, whose over-activation is commonly associated with hypertension. Indeed, medications that target the RAS are generally effective in reducing blood pressure. However, more can be learned about how these medications influence the intrarenal RAS. Angiotensin-receptor blockers (ARBs) in particular have been shown to exert different effects on the intrarenal and systemic RASs in various experimental models of hypertension. In rats chronically infused with angiotensin II (Ang II), ARBs consistently prevent intrarenal, but not systemic Ang II levels from rising. The former effect is sufficient in preventing the development of hypertension. The regulation of intrarenal RAS, independently of the systemic RAS, by ARBs has been hypothesized to be mediated by the inhibition of all positive feedback loops inherent to the intrarenal RAS, also known as the “key point breakdown effect.” To investigate the validity of this hypothesis, we developed a PK/PD model of the ARB Losartan that considers the kidney, and applied the model to study how this class of medication influences intrarenal RAS activity and consequently blood pressure regulation in male rats. Simulations indicate that ARBs more effectively inhibit the activation of the intrarenal RAS because, unlike in the plasma, this process relies on the accumulation of cell-associated Ang II. We hypothesize that it is by blocking this intracellular uptake pathway, and restricting Ang II to extracellular regions of the kidney where the peptide cannot initiate downstream signalling, that Losartan normalizes blood pressure. While the key point break down effect assists in this response, it alone is not sufficient. Our results highlight the intrarenal RAS as the key pharmacological target of ARB treatment and emphasize the importance of this local tissue RAS in the development of hypertension.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".