Enhanced susceptibility of S‐100B transgenic mice to neuroinflammation and neuronal dysfunction induced by intracerebroventricular infusion of human β‐amyloid
Bibliographic record
Abstract
S-100B is an astrocyte-derived protein that is increased in focal areas of the brain most severely affected by neuropathological changes in Alzheimer's disease (AD). Cell-based and clinical studies have implicated S-100B in progression of a pathologic, glial-mediated pro-inflammatory state in the CNS. However, the relationship between S-100B levels and susceptibility to AD-relevant neuroinflammation and neuronal dysfunction in vivo has not been determined. To test the hypothesis that overexpression of S-100B increases vulnerability to beta-amyloid (Abeta)-induced damage, we used S-100B-overexpressing transgenic (Tg) and S-100B knockout (KO) mice in a mouse model that involves intracerebroventricular infusion of human oligomeric Abeta1-42. This model mimics many features of AD, including robust neuroinflammation, Abeta plaques, synaptic damage and neuronal loss in the hippocampus. S-100B Tg, KO, and wild-type (WT) mice were infused with Abeta for 28 days, sacrificed at 60 days, and hippocampal endpoints analyzed. We found that Tg mice showed increased vulnerability to Abeta-induced neuropathology relative to either WT or KO mice. Specifically, Tg mice exhibited enhanced glial activation and neuroinflammation, increased nitrotyrosine staining (a marker of glial-induced neuronal damage), and more pronounced loss of synaptic markers. Interestingly, Tg mice showed no significant differences in Abeta plaque burden compared with WT or KO mice, suggesting that, as in the human situation, the severity of neuronal dysfunction did not correlate with amyloid deposition. Our data are consistent with a model in which S-100B overexpression in AD enhances glial activation and leads to an augmented neuroinflammatory process that increases the severity of neuropathologic sequelae.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".