Metalloproteinases Control Brain Inflammation Induced by Pertussis Toxin in Mice Overexpressing the Chemokine CCL2 in the Central Nervous System
Bibliographic record
Abstract
Inflammatory leukocytes infiltrate the CNS parenchyma in neuroinflammation. This involves cellular migration across various structures associated with the blood-brain barrier: the vascular endothelium, the glia limitans, and the perivascular space between them. Leukocytes accumulate spontaneously in the perivascular space in brains of transgenic (Tg) mice that overexpress CCL2 under control of a CNS-specific promoter. The Tg mice show no clinical symptoms, even though leukocytes have crossed the endothelial basement membrane. Pertussis toxin (PTx) given i.p. induced encephalopathy and weight loss in Tg mice. We used flow cytometry, ultra-small superparamagnetic iron oxide-enhanced magnetic resonance imaging, and immunofluorescent staining to show that encephalopathy involved leukocyte migration across the glia limitans into the brain parenchyma, identifying this as the critical step in inducing clinical symptoms. Metalloproteinase (MPs) enzymes are implicated in leukocyte infiltration in neuroinflammation. Unmanipulated Tg mice had elevated expression of tissue inhibitor of metalloproteinase-1, matrix metalloproteinase (MMP)-10, and -12 mRNA in the brain. PTx further induced expression of tissue inhibitor of metalloproteinase-1, metalloproteinase disintegrins-12, MMP-8, and -10 in brains of Tg mice. Levels of the microglial-associated MP MMP-15 were not affected in control or PTx-treated Tg mice. PTx also up-regulated expression of proinflammatory cytokines IL-1beta and TNF-alpha mRNA in Tg CNS. Weight loss and parenchymal infiltration, but not perivascular accumulation, were significantly inhibited by the broad-spectrum MP inhibitor BB-94/Batimastat. Our finding that MPs mediate PTx-induced parenchymal infiltration to the chemokine-overexpressing CNS has relevance for the pathogenesis of human diseases involving CNS inflammation, such as multiple sclerosis.
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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 | 0.001 | 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 | 0.001 |
| 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".