Renoprotective effects of aliskiren on adenine-induced tubulointerstitial nephropathy: possible underlying mechanisms
Bibliographic record
Abstract
The present study investigated the possible renoprotective effect of direct renin inhibitor (aliskiren) on renal dysfunctions, as well as its underlying mechanisms in rat model of adenine-induced tubulointerstitial nephropathy. Forty male Sprague-Dawley rats were randomized into 4 groups; normal group, aliskiren group (normal rats received 10 mg/kg aliskiren), adenine group (animals received high-adenine diet for 4 weeks and saline for 12 weeks), and adenine + aliskiren group (animals received adenine for 4 weeks and aliskiren 10 mg/kg for 12 weeks). It was found that adenine caused significant decrease in body mass, Hb, HR, serum Ca(2+), eNOS and nrf2 expression, GSH, and catalase in kidney tissues with significant increase in arterial blood pressure (ABP), serum creatinine, BUN, plasma renin activity (PRA), K(+) and P, urinary albumin excretion (UAE), caspase-3, and MDA (lipid peroxidation marker) in kidney tissues compared to normal group (p < 0.05). Administration of aliskiren caused significant improvement in all studied parameters compared to adenine group (p < 0.05). We concluded that aliskiren has renoprotective effect against adenine-induced nephropathy. This might be due to inhibition of PRA, attenuation of oxidative stress, activation of Nrf2 and eNOS genes, and suppression of caspase-3.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".