Myeloid cell transmigration across the CNS vasculature triggers IL-1β–driven neuroinflammation during autoimmune encephalomyelitis in mice
Bibliographic record
Abstract
Growing evidence supports a role for IL-1 in multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), but how it impacts neuroinflammation is poorly understood. We show that susceptibility to EAE requires activation of IL-1R1 on radiation-resistant cells via IL-1β secreted by bone marrow-derived cells. Neutrophils and monocyte-derived macrophages (MDMs) are the main source of IL-1β and produce this cytokine as a result of their transmigration across the inflamed blood-spinal cord barrier. IL-1R1 expression in the spinal cord is found in endothelial cells (ECs) of the pial venous plexus. Accordingly, leukocyte infiltration at EAE onset is restricted to IL-1R1(+) subpial and subarachnoid vessels. In response to IL-1β, primary cultures of central nervous system ECs produce GM-CSF, G-CSF, IL-6, Cxcl1, and Cxcl2. Initiation of EAE or subdural injection of IL-1β induces a similar cytokine/chemokine signature in spinal cord vessels. Furthermore, the transfer of Gr1(+) cells on the spinal cord is sufficient to induce illness in EAE-resistant IL-1β knockout (KO) mice. Notably, transfer of Gr1(+) cells isolated from C57BL/6 mice induce massive recruitment of recipient myeloid cells compared with cells from IL-1β KO donors, and this recruitment translates into more severe paralysis. These findings suggest that an IL-1β-dependent paracrine loop between infiltrated neutrophils/MDMs and ECs drives neuroinflammation.
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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 | 0.001 |
| Open science | 0.001 | 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".