Effects of alpha‐lipoic acid in an animal model of mania induced by<scp>d</scp>‐amphetamine
Bibliographic record
Abstract
OBJECTIVES: Oxidative stress and neurotrophic factors are involved in the pathophysiology of bipolar disorder (BD). Alpha-lipoic acid (ALA) is a naturally occurring compound with strong antioxidant properties. The present study investigated ALA effects in an amphetamine-induced model of mania. METHODS: In the reversal protocol, adult mice were first given d-amphetamine (AMPH) 2 mg/kg, intraperitoneally (i.p.) or saline for 14 days. Between days 8 and 14, the animals received ALA 50 or 100 mg/kg orally, lithium (Li) 47.5 mg/kg i.p., or saline. In the prevention paradigm, mice were pretreated with ALA, Li, or saline prior to AMPH. Locomotor activity was assessed in the open-field task. Superoxide dismutase (SOD) activity, reduced glutathione (GSH), and thiobarbituric acid-reactive substance (TBARS) levels were evaluated in the prefrontal cortex (PFC), hippocampus (HC), and striatum (ST). Brain-derived neurotrophic factor (BDNF) levels were measured in the HC. RESULTS: ALA and Li prevented and reversed the AMPH-induced increase in locomotor activity. PREVENTION MODEL: ALA and Li co-administration with AMPH prevented the decrease in SOD activity induced by AMPH in the HC and ST, respectively; ALA and Li prevented GSH alteration in the HC and TBARS formation in all brain areas studied. REVERSAL MODEL: ALA reversed the decrease in SOD activity in the ST. TBARS formation was reversed by ALA and Li in all brain areas. Furthermore, ALA reversed AMPH-induced decreases in BDNF and GSH in the HC. CONCLUSIONS: Our findings showed that ALA, similarly to Li, is effective in reversing and preventing AMPH-induced behavioral and neurochemical alterations, providing a rationale for the design of clinical trials investigating ALA's possible antimanic effect.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".