Ethanol and cyclophosphamide induce similar nephrotoxic effects: possible role for Nox4 and superoxide
Bibliographic record
Abstract
We tested the hypothesis that ethanol consumption would aggravate the renal damage induced by cyclophosphamide (CYP). Male C57BL/6 J mice from control (n = 8) and CYP (n = 12) groups had free access to filtered water and standard rodent chow for 12 weeks. Then, 24 h before euthanasia mice received an intraperitoneal injection of saline or CYP (300 mg/kg). Mice from ethanol (n = 8) and CYP + ethanol (n = 12) groups had free access to increasing doses of ethanol for 12 weeks. Twenty-four hours before euthanasia, mice from ethanol and CYP + ethanol groups received an intraperitoneal injection of saline or CYP, respectively. Ethanol, CYP, or the association of both drugs augmented serum levels of creatinine and increased the levels of superoxide ([Formula: see text]) generation and thiobarbituric acid reactive substances in the renal cortex. Upregulation of Nox4 and increased activity of superoxide dismutase were detected in the renal cortex of mice treated with ethanol, CYP, or the combination of these drugs; however, these molecular alterations induced by CYP were not potentiated by ethanol consumption. Our findings revealed that chronic ethanol consumption had no potentiating effect on the nephrotoxic effects displayed by CYP. It is possible that the combination of these drugs showed no synergistic effect because they share the same molecular mechanisms of renal toxicity.
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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) | 0.000 | 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 | 0.000 |
| 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".