Acute brain cytokine responses after global birth hypoxia in the rat
Bibliographic record
Abstract
The main cause of hypoxic/ischemic brain damage in term human neonates is intrauterine asphyxia, in which the whole body is subjected to hypoxia. Inflammatory cytokines are thought to play an important role in modulating hypoxic/ischemic damage in immature brain. Evidence for this from animal models is based mainly on studies that used a model of carotid artery ligation with hypoxia in postnatal rats. However, little is known about the role of cytokines in brain injury after whole-body hypoxia at the time of birth. This study used a well-established rat model of global birth hypoxia to assess mRNA and protein expression of three key proinflammatory cytokines, interleukin-1beta (IL-1beta), IL-6, and tumor necrosis factor-alpha, (TNF-alpha) in the brain, liver, and kidney of neonates. We observed decreased IL-1beta and TNF-alpha protein, and decreased IL-6 mRNA in brains of neonates in the 2 hr after birth hypoxia but increased IL-6 and IL-1beta in liver compared with vaginally born controls. Increasing the severity of the insult by increasing the period of anoxic exposure further decreased brain IL-1beta, whereas delivering anoxia under hypothermic conditions, known to be neuroprotective, attenuated the decrease in brain IL-1beta. These data suggest that decreased brain levels of inflammatory cytokines may modulate central nervous system responses to global birth hypoxia in rats. Our findings of decreased brain cytokine expression after global birth hypoxia contrast with reports of increased brain cytokines after carotid artery ligation with hypoxia in postnatal rats; possible reasons for these differences are discussed.
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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) | 0.000 | 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) | 0.001 | 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".