EFFECT OF MELATONIN ON REGENERATION OF CORTICAL NEURONS IN RATS WITH TRAUMATIC BRAIN INJURY
Bibliographic record
Abstract
Purpose To investigate the effect of melatonin on regeneration of cortical neurons in rats with traumatic brain injury (TBI). Methods Sprague-Dawley rats (n=36) were randomly divided into sham, TBI+vehicle and TBI+melatonin groups. Cerebral blood flow and cognitive function were observed via laser Doppler flowmetry and by Morris water maze testing, respectively. The serum malondialdehyde (MDA) and superoxide dismutase (SOD) levels were used to assess oxidative stress. Immunofluorescence and terminal deoxynucleotidyl transferase dUTP nick end labelling assay was used to observe the newborn neurons and apoptotic cells. Results Cerebral blood flow in the TBI+melatonin group was higher than that of the TBI+vehicle group at one, 12, 24 and 48 h post-injury, but the difference was not statistically significant (P>0.05). The cognitive function of the rats was better in the TBI+melatonin group than the TBI+vehicle group (P<0.05). The MDA and SOD levels were better in the TBI+melatonin group than the TBI+vehicle group (P<0.05) and it was similar to the sham group at 14 d (P>0.05). The number of apoptotic cells was lower in the TBI+melatonin group than the TBI+vehicle group (P<0.05). The number of DCX+/BrdU+ immature newborn neurons and NeuN+/BrdU+ mature newborn neurons was higher in the TBI+melatonin group than the TBI+vehicle group (P<0.05). Conclusion These results indicated that melatonin reduced oxidative stress level and cells apoptosis of brain and promoted the regeneration of neurons in the cortex of rats with TBI, leading to improve cognitive functional recovery.
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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 | 0.000 | 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".