The Protective Effects of Vitamin E and Zinc Supplementation Against Lithium-Induced Brain Toxicity of Male Albino Rats
Bibliographic record
Abstract
Lithium (Li) therapy has widely used in the treatment of bipolar disorder. Consequently, consciousness of the side effects and pathogenesis of this metal is needed for such treatments. Recently, information on the interaction of Li with oxidative markers and organs toxicity attend the researchers over the world. In the present study we have tried to evaluate the influence of oral administration of LiCl for 4 weeks on the oxidative stress marker and histological structure of brain in male rats. Fifty adult male albino rats weighing 135±15 gm was categorized into 5 groups (10 rats each). Group I worked as negative control, group II administrated with LiCl (0.20 mg/kg bw) in drinking water, group III, IV and V were administrated with Zn (10 mg/kg bw), VE (100 mg/kg bw) and their combination twice a week besides the daily administration of LiCl for 4 weeks, respectively. Rats after anesthesia with ether killed for collocation of brain for histopathological and biochemical analysis. Data obtained showed a significant increase in LPO, NO, GSH and Li content and the activities of SOD, CAT and AChE with demylination of the nerve fibers and degeneration of neurons in brain of LiCl treated rats. Co-treatment of rats with Zn or VE results in a significant decrease in LPO, NO, GSH content in the activities of SOD, CAT and AChE with less or normal structure of the brain. However, co-treatment with combination of Zn and VE caused a significant increase in SOD, CAT and AChE activities with normal histological structure.In conclusion, the data from the present study show that Zn and VE and their interaction are effective in protection against Li- induced brain toxicity in rat with priority for the combination.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".