Constitutive Interferon Attenuates RIPK1/3-Mediated Cytokine Translation
Bibliographic record
Abstract
Receptor-interacting protein kinase 1 (RIPK1) and 3 (RIPK3) are well known for their capacity to drive necroptosis via mixed-lineage kinase-like domain (MLKL). Recently, RIPK1/3 kinase activity has been shown to drive inflammation via activation of MAPK signaling. However, the regulatory mechanisms underlying this kinase-dependent cytokine production remain poorly understood. In the present study, we establish that the kinase activity of RIPK1/3 regulates cytokine translation in mouse and human macrophages. Furthermore, we show that this inflammatory response is downregulated by type I interferon (IFN) signaling, independent of type I IFN-promoted cell death. Specifically, low-level constitutive IFN signaling attenuates RIPK-driven activation of cap-dependent translation initiation pathway components AKT, mTORC1, 4E-BP and eIF4E, while promoting RIPK-dependent cell death. Altogether, these data characterize constitutive IFN signaling as a regulator of RIPK-dependent inflammation and establish cap-dependent translation as a crucial checkpoint in the regulation of cytokine production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".