Dose-dependent effects of the ACE inhibitor, ramipril, on kidney function and structure in the Alport COL4A3 <sup>−/−</sup> mouse
Bibliographic record
Abstract
Introduction ACE inhibitor treatment of Alport syndrome, undertaken when individuals are still presymptomatic/oligosymptomatic delays dialysis but substantial residual risk remains so that additional treatments are desperately needed. In contrast to humans, standard-dose ACE inhibition with ramipril 10 mg/kg/day in Alport mice almost completely prevents GFR loss, precluding the ability to test new add-on therapies. Accordingly, we sought to find a dose that mirrored the ∼50% improvement in GFR seen in humans. Material and methods Escalating doses of ramipril at 0.1, 1, 3 and 10 mg/kg/day, were administered to COL4A3 −/− mice. Results After four weeks, ramipril induced a logarithmic, dose-dependent decline in cystatin C, the primary GFR-based outcome, with efficacy apparent at 0.1 mg/kg/day and a 50% improvement at 1–3 mg/kg/day. Proteinuria, the study's secondary outcome, showed a similar dose-response. In contrast, structural improvements such as podocyte density, glomerulosclerosis and tubulointerstitial fibrosis were not evident below 3 mg/kg/day. Conclusion By exploring the dose-response relationship of RAS blockade in an Alport model, the present study shows that ramipril 1 mg/kg/day may be sufficient for examining additive effects of other agents on kidney function while 3 mg/kg/day is required in order to assess the effects of add-on therapy on kidney structure as well.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".