Aliskiren increases bradykinin and tissue kallikrein mRNA levels in the heart
Bibliographic record
Abstract
1. Aliskiren is a renin inhibitor with an IC(50) of 0.6 nmol/L for human renin, 4.5 nmol/L for mouse renin and 80 nmol/L for rat renin. 2. In the present study, we compared the effects of aliskiren (10 mg/kg per day), the angiotensin-converting enzyme inhibitor perindopril (0.2 mg/kg per day) and their combination on angiotensin and bradykinin peptides in female heterozygous (mRen-2)27 rats, transgenic for the mouse renin gene. 3. All three treatments produced similar reductions in systolic blood pressure, heart weight and plasma aldosterone levels and reduced angiotensin II levels in lung, but only perindopril and the combination reduced angiotensin II levels in kidney of (mRen-2)27 rats. In contrast, aliskiren and the combination, but not perindopril alone, increased cardiac bradykinin levels. Aliskiren increased immunostaining for tissue kallikrein in the heart and reduced cardiac fibrosis. 4. We investigated the mechanism underlying the increase in bradykinin levels following aliskiren treatment in Sprague-Dawley rats, in which aliskiren has a lower potency for renin inhibition. Aliskiren (10 mg/kg per day) reduced renal angiotensin levels within 24 h, but treatment for > 24 h was required to increase cardiac bradykinin levels. Moreover, 3 mg/kg per day aliskiren increased cardiac bradykinin levels, but did not reduce renal angiotensin levels. Aliskiren did not potentiate the hypotensive effects of bradykinin; however, it increased tissue kallikrein, but not plasma kallikrein, mRNA levels in the heart. 5. These data demonstrate that the aliskiren-induced increase in cardiac bradykinin levels is independent of renin inhibition and changes in bradykinin metabolism, but is associated with increased tissue kallikrein gene expression.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".