Oxidative damage in the livers of senescence-accelerated mice: a gender-related response
Bibliographic record
Abstract
The prevalence of liver diseases emphasizes the need of animal models to research on the mechanism of disease pathogenesis. Furthermore, most of the liver pathologies have the oxidative stress as an important component. The senescence-accelerated mouse strain SAMP8 was proposed as a valuable animal model for the study of liver diseases. To gain a better understanding of the mechanisms underlying degenerative processes in SAMP8 mice livers, we studied the oxidative-induced damage in 5-month-old SAMP8 mice and SAMR1, senescence-accelerated-resistant mice. We found profound differences in the antioxidant response to aging between sexes, with males displaying lowest levels of main antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR) in SAMP8; whereas females had no difference in their activities, except for GR, when compared with their SAMR1 controls. The results obtained show the binomial SOD/CAT as an important factor for counteracting reactive oxygen species-dependent damage. There were not pathological differences at the morphological level between both strains, although the decay in protection against free radicals had an immediate response by increasing lipid and protein oxidative damage in SAMP8 mice liver. At 5 months, both male and female SAMP8 mice confront the oxidative stress challenge to different extents. Indeed, proteins seem to be the most vulnerable biomolecule in SAMP8 male mice.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".