Cutting Edge: NF-κB Activating Pattern Recognition and Cytokine Receptors License NLRP3 Inflammasome Activation by Regulating NLRP3 Expression
Bibliographic record
Abstract
The IL-1 family cytokines are regulated on transcriptional and posttranscriptional levels. Pattern recognition and cytokine receptors control pro-IL-1beta transcription whereas inflammasomes regulate the proteolytic processing of pro-IL-1beta. The NLRP3 inflammasome, however, assembles in response to extracellular ATP, pore-forming toxins, or crystals only in the presence of proinflammatory stimuli. How the activation of gene transcription by signaling receptors enables NLRP3 activation remains elusive and controversial. In this study, we show that cell priming through multiple signaling receptors induces NLRP3 expression, which we identified to be a critical checkpoint for NLRP3 activation. Signals provided by NF-kappaB activators are necessary but not sufficient for NLRP3 activation, and a second stimulus such as ATP or crystal-induced damage is required for NLRP3 activation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".