Protective effect of nimodipine on behavior and white matter of rats with hydrocephalus
Bibliographic record
Abstract
OBJECT: Hydrocephalus, a pathological dilation of the ventricles of the brain, causes damage to periventricular white matter, at least in part, through chronic ischemia. The authors tested the hypothesis that treatment with nimodipine, an L-type calcium channel-blocking agent with demonstrated efficacy in a range of cerebral ischemic disorders, would ameliorate the adverse effects of experimental hydrocephalus. METHODS: Hydrocephalus was induced in 3-week-old rats by injection of kaolin into the cisterna magna. The rats were treated by continuous administration of nimodipine or control vehicle for 2 weeks, beginning 2 weeks after induction of hydrocephalus. During the treatment period, the animals underwent repeated tests of motor and cognitive behavior. At the end of the treatment period, the rat brains were analyzed by histopathological and biochemical means. Nimodipine treatment prevented the declines in motor and cognitive behavior that were observed in untreated control rats. During the treatment period, ventricular enlargement, determined by magnetic resonance imaging, was equal in the two groups, although the corpus callosum was thicker in the treated rats. Myelin content in white matter and synaptophysin content in gray matter, an indicator of synapses, did not differ. CONCLUSIONS: The protective effect of nimodipine is most likely based on improved blood flow, although prevention of calcium influx-mediated proteolytic processes in axons cannot be excluded. Adjunctive pharmacological therapy may be beneficial to patients with hydrocephalus.
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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 | 0.000 | 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".