Effect of mood stabilizers in the regulation of glutathione-s-transferase M1 expression
Bibliographic record
Abstract
Background. Common mood stabilizers used to treat Bipolar Disorder (BD) have been shown to exert neuroprotective effects against oxidative damage. Recent studies in rat cerebral cortical cells have shown that chronic treatment with lithium and valproate, induces the expression of the antioxidant enzyme, glutathione-s-transferase class Mu-1 (GST-M1). The effect of other mood stabilizers such as lamotrigine, olanzapine and carbamazepine on the expression and activity of GST-M1 was studied. Methods. GST-M1 protein levels and GST enzyme activity were measured by immunoblotting and spectrophotometric assays respectively, in rat cerebral cortical cells treated with mood stabilizing drugs. Results. Although acute treatment with lamotrigine and olanzapine had no effect on GST-M1 protein levels, chronic treatment with these two drugs not only increased GST-M1 protein levels, but also increased GST enzyme activity. However, both acute and chronic treatment with carbamazepine had no effect on GST-M1 protein levels. Conclusions. Induction of GST-M1 expression to fight oxidative damage may be one of the mechanisms of mood stabilizers pharmacological action in treating bipolar disorder.
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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) | 0.002 | 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".