Blood–brain barrier disruption in CCL2 transgenic mice during pertussis toxin-induced brain inflammation
Bibliographic record
Abstract
BACKGROUND: The chemokine CCL2 has an important role in the recruitment of inflammatory cells into the central nervous system (CNS). A transgenic mouse model that overexpresses CCL2 in the CNS shows an accumulation of leukocytes within the perivascular space surrounding vessels, and which infiltrate into the brain parenchyma following the administration of pertussis toxin (PTx). METHODS: This study used contrast-enhanced magnetic resonance imaging (MRI) to quantify the extent of blood-brain barrier (BBB) disruption in this model pre- and post-PTx administration compared to wild-type mice. Contrast-enhanced MR images were obtained before and 1, 3, and 5 days after PTx injection in each animal. After the final imaging session fluorescent dextran tracers were administered intravenously to each mouse and brains were examined histologically for cellular infiltrates, BBB leakage and tight junction protein. RESULTS: BBB breakdown, defined as a disruption of both the endothelium and glia limitans, was found only in CCL2 transgenic mice following PTx administration and seen on MR images as focal areas of contrast enhancement and histologically as dextrans leaking from blood vessels. No evidence of disruption in endothelial tight junctions was observed. CONCLUSION: Genetic and environmental stimuli were needed to disrupt the integrity of the BBB in this model of neuroinflammation.
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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 | 0.001 | 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) | 0.002 | 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".