Increased susceptibility of S100B transgenic mice to perinatal hypoxia‐ischemia
Bibliographic record
Abstract
S100B is a glial-derived protein that is a well-established biomarker for severity of neurological injury and prognosis for recovery. Cell-based and clinical studies have implicated S100B in the initiation and maintenance of a pathological, glial-mediated proinflammatory state in the central nervous system. However, the relationship between S100B levels and susceptibility to neurological injury in vivo has not been determined. We used S100B transgenic (Tg) and knockout (KO) mice to test the hypothesis that overexpression of S100B increases vulnerability to cerebral hypoxic-ischemic injury and that this response correlates with an increase in neuroinflammation from activated glia. Postnatal day 8 Tg mice subjected to hypoxia-ischemia showed a significant increase in mortality compared with KO and wild-type mice. Tg mice also exhibited greater cerebral injury and volume loss in the ischemic hemisphere after an 8-day recovery, as assessed by histopathology and magnetic resonance imaging. Measurement of glial fibrillary acidic protein and S100B levels showed a significant increase in the Tg mice, consistent with heightened glial activation and neuroinflammation in response to injury. This is the first demonstration to our knowledge that overexpression of S100B in vivo enhances pathological response to injury.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".