Neonatal treatment with fluoxetine alters locomotor activity and the cortical glial/neuron index in rats with cerebral palsy
Bibliographic record
Abstract
Cerebral palsy (CP) is characterized by motor disorders, including deficits in locomotor activity, coordination, and balance. Selective serotonin reuptake inhibitors have been shown to play an important role in brain plasticity. This study investigates the effect of neonatal treatment using fluoxetine on locomotor activity and histomorphometric parameters of the primary somatosensory cortex (S1) in rats submitted to an experimental model of CP. CP was found to reduce bodyweight and locomotion parameters and also to increase the glia/neuron index in the S1. Administration of fluoxetine 10 mg/kg reduced bodyweight, impaired locomotor activity parameters, and increased the number of glial cells and the glia/neuron ratio in the S1 in rats with CP. However, treatment with fluoxetine 5 mg/kg was not found to be associated with adverse effects on locomotor activity and seems to improve histomorphometric parameters by way of minor changes in the S1 in animals with CP. These results thus indicate that experimental CP, in combination with the use of a high dose of fluoxetine (10 mg/kg), impairs locomotor and histomorphometric parameters in the S1, while treatment with a low dose of fluoxetine (5 mg/kg) averts the negative outcomes associated with a high dose of fluoxetine in relation to these parameters but produces no protective 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 | 0.000 |
| 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".