The Effect of Postischemic Hypothermia on Apoptotic Cell Death in the Neonatal Rat Brain
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Hypothermia is the most effective neuroprotective therapy against ischemic injury in the developing brain. However, the mechanism of hypothermic neuroprotection is not well understood. We sought to investigate whether hypothermia mediates neuroprotection by modulating ischemia-induced apoptosis. METHODS: Seven-day-old rat pups were randomly assigned to either control or hypoxia-ischemia (HI) groups. In the HI group, the internal carotid artery was ligated and cut. This was followed by transient hypoxia at 8% oxygen for 90 min. In the control rats, the internal carotid was isolated but not ligated. Immediately after the hypoxic episode, pups in the HI group were either placed in water baths maintained at 28°C for 24 h (core temperatures at 31°C) or they remained in a normothermic environment. Animals were sacrificed at 24, 48 and 72 h and 1 week after the HI insult. Brain sections were processed for immunohistochemistry and Western blots. RESULTS: Caspase 3 expression was significantly higher in the core compared with the peri-infarct area at all time points in normothermic rats. Hypothermia reduced caspase 3 expression in the core but had little effect in the peri-infarct area. Hypothermia reduced apoptosis-inducing factor translocation to the nucleus in the core and peri-infarct area. Concurrently, X-linked inhibitor of apoptosis (XIAP) expression was significantly potentiated in the hypothermic-ischemic core but not in the peri-infarct area. CONCLUSION: Hypothermic modulation of caspase-dependent apoptosis may be mediated by upregulating XIAP. However, the effect of hypothermia on caspase-independent apoptosis may be mediated by XIAP-independent mechanisms. Importantly, these effects are mediated in both the core and the penumbral regions of ischemic lesion.
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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 | 0.000 |
| 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".