PRO-INFLAMMATORY CYTOKINES IN THE PATHOGENESIS OF BRAIN INJURIES FOLLOWING PERINATAL INFECTION AND ANOXIA
Bibliographic record
Abstract
Objectives: Antenatal infection and anoxia are the main pathogenic processes triggering grey and white matter injuries in the brain of human neonates. We used our original rat model of neonatal brain lesions to study the role of pro-inflammatory cytokines in perinatal infectious and hypoxic-ischemic (H/I) aggressions of the brain. Methods: Infectious effect was produced by administrating lipopolysaccharide (LPS) intraperitoneally (ip) to pregnant rats from embryonic day 17 (E17) to E20. H/I was induced at postnatal day 1 (P1) by ligature of the right common carotid artery followed by exposure to hypoxia (7% O2) for 3.5 hours. IL-1, IL-2 and TNF mRNA and protein expressions were studied by RT-PCR and western blot. Brain injuries were examined at P3 and P8. Results: The extent of neuronal cell injury in the brain of rats exposed to postnatal H/I was significantly increased by antenatal exposure to LPS. Experimental aggressions resulted in IL-1beta, IL-2 and TNF-alpha mRNA and protein increases in the neonatal brain. Conclusion: Our animal model provides an experimental tool to study the role of pro-inflammatory cytokines in the pathophysiology of perinatal human brain lesions and subsequent cerebral palsy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".