Expression of interleukin‐1 receptors and their role in interleukin‐1 actions in murine microglial cells
Bibliographic record
Abstract
Interleukin (IL)-1 is an important mediator of acute brain injury and inflammation, and has been implicated in chronic neurodegeneration. The main source of IL-1 in the CNS is microglial cells, which have also been suggested as targets for its action. However, no data exist demonstrating expression of IL-1 receptors [IL-1 type-I receptor (IL-1RI), IL-1 type-II receptor (IL-1RII) and IL-1 receptor accessory protein (IL-1RAcP)] on microglia. In the present study we investigated whether microglia express IL-1 receptors and whether they present target or modulatory properties for IL-1 actions. RT-PCR analysis demonstrated lower expression of IL-1RI and higher expression of IL-1RII mRNAs in mouse microglial cultures compared with mixed glial or pure astrocyte cultures. Bacterial lipopolysaccharide (LPS) caused increased expression of IL-1RI, IL-1RII and IL-1RAcP mRNAs, induced the release of IL-1beta, IL-6 and prostaglandin-E2 (PGE2), and activated nuclear factor kappaB (NF-kappaB) and the mitogen-activated protein kinases (MAPKs) p38, and extracellular signal-regulated protein kinase (ERK1/2), but not c-Jun N-terminal kinase (JNK) in microglial cultures. In comparison, IL-1beta induced the release of PGE2, IL-6 and activated NF-kappaB, p38, JNK and ERK1/2 in mixed glial cultures, but failed to induce any of these responses in microglial cell cultures. IL-1beta also failed to affect LPS-primed microglial cells. Interestingly, a neutralizing antibody to IL-1RII significantly increased the concentration of IL-1beta in the medium of LPS-treated microglia and exacerbated the IL-1beta-induced IL-6 release in mixed glia, providing the first evidence that microglial IL-1RII regulates IL-1beta actions by binding excess levels of this cytokine during brain inflammation.
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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".