Effects of mood stabilizers on DNA damage in an animal model of mania
Bibliographic record
Abstract
OBJECTIVE: Recent studies have suggested that oxidative stress and DNA damage may play a role in the pathophysiology of bipolar disorder (BD). We investigated the effects of the mood stabilizers lithium and valproate on amphetamine-induced DNA damage in an animal model of mania and their correlation with oxidative stress markers. METHODS: In the first experiment (reversal model), we treated adult male Wistar rats with D-amphetamine (AMPH) or saline for 14 days; between the 8th and 14th days, rats also received lithium, valproate or saline. In the second experiment (prevention model), rats received either lithium, valproate or saline for 14 days; between the 8th and 14th days, we added AMPH or saline. We evaluated DNA damage using single-cell gel electrophoresis (comet assay), and we assessed the mutagenic potential using the micronucleus test. We assessed oxidative stress levels by lipid peroxidation levels (TBARS) and antioxidant enzyme activities (superoxide dismutase and catalase). We assessed DNA damage and oxidative stress markers in blood/plasma and hippocampal samples. We evaluated mutagenesis in fresh lymphocytes. RESULTS: In both models, we found that AMPH increased peripheral and hippocampal DNA damage. The index of DNA damage correlated positively with lipid peroxidation, whereas lithium and valproate were able to modulate the oxidative balance and prevent recent damage to the DNA. However, lithium and valproate were not able to prevent micronucleus formation. CONCLUSION: Our results support the notion that lithium and valproate exert central and peripheral antioxidant-like properties. In addition, the protection to the integrity of DNA conferred by lithium seems to be limited to transient DNA damage and does not alter micronuclei formation.
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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) | 0.001 | 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 | 0.001 |
| 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".