IL-1RAcPb signaling regulates adaptive mechanisms in neurons that promote their long-term survival following excitotoxic insults
Bibliographic record
Abstract
Excitotoxicity is a major component of neurodegenerative diseases and is typically accompanied by an inflammatory response. Cytokines IL-1alpha and IL-1beta are key regulators of this inflammatory response and modulate the activity of numerous cell types, including neurons. IL-1RAcPb is an isoform of IL-1RAcP expressed specifically in neurons and promotes their survival during acute inflammation. Here, we investigated in vivo whether IL-1RAcPb also promotes neuronal survival in a model of excitotoxicity. Intrastriatal injection of kainic acid (KA) in mice caused a strong induction of IL-1 cytokines mRNA in the brain. The stress response of cortical neurons at 12 h post-injection, as measured by expression of Atf3, FoxO3a, and Bdnf mRNAs, was similar in WT and AcPb-deficient mice. Importantly however, a delayed upregulation in the transcription of calpastatin was significantly higher in WT than in AcPb-deficient mice. Finally, although absence of AcPb signaling had no effect on damage to neurons in the cortex at early time points, it significantly impaired their long-term survival. These data suggest that in a context of excitotoxicity, stimulation of IL-1RAcPb signaling may promote the activity of a key neuroprotective mechanism.
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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) | 0.000 | 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) | 0.001 | 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 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".