Intraperitoneal cannabidiol attenuates neonatal germinal matrix hemorrhage-induced neuroinflamation and perilesional apoptosis
Bibliographic record
Abstract
Background. As the survival of preterm infants has increased significantly, germinal matrix hemorrhage (GMH) has become an important public health issue. Nevertheless, treatment strategies for the direct neuronal injury are still scarce. The present study aims to analyze the neuroprotective properties of cannabidiol in germinal matrix hemorrhage.Methods. 112 Wistar rat pups (P7) were submitted to an experimental collagenase induced model of GMH. Inflammatory response and neuronal death were analyzed both at the perilesional area as at the distant ipsilateral CA1 hippocampal area. Immunohistochemistry for GFAP and caspase 3 was used. The ipsilateral free water content was assessed for stimation of cerebral edema, and neurodevelopment and neurofunctional tests were conducted.Results. Reduction of reactive astrocytosis was observed both in the perilesional area 24 hours and 14 days after the hemorrhage lesion (p < 0.001) and in the Stratum oriens of the ipsilateral hippocampal CA1 14 days after the hemorrhage lesion (p < 0.05) in the treated groups. Similarly, there was a reduction in the number of Caspase 3-positive astrocytes in the perilesional area in the treated groups 24 hours after the hemorrhage lesion (p < 0.001). Finally, we found a significant increase in the weight of the rats treated with cannabidiol.Conclusion. The treatment of GMH with cannabidiol significantly reduced the number of apoptotic cells and reactive astrocytes in the perilesional area and the ipsilateral hippocampus. In addition, this response was sustained 14 days after the hemorrhage. These results corroborate our hypothesis that cannabidiol is a potential neuroprotective agent in the treatment of germinal matrix hemorrhage.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".