Regulation of NFKBIZ by precise Regnase-1 endoribonuclease cleavage and subsequent uridylation
Bibliographic record
Abstract
SUMMARY A conserved sequence in the 3′UTR of NFKBIZ mRNA has long been recognized as a regulator of cytokine production and interferon responses. We show that the endoribonuclease Regnase-1 controls NFKBIZ expression through a precise and modular RNA degradation mechanism. The structured core element undergoes specific endonucleolytic cleavage, while flanking upstream and downstream stem–loop modules, previously implicated in Regnase-1 recognition, act cooperatively to enhance cleavage efficiency by ∼25-fold. Following cleavage, the upstream fragment is rapidly uridylated, accelerating decay of the NFKBIZ open reading frame. This pathway explains how driver mutations – found in this RNA region – responsible for diffuse large B-cell lymphoma elevate NFKBIZ expression and how a segment of the SARS-CoV-2 genome – previously linked to NFKBIZ activation – suppresses Regnase-1 cleavage via hybridization to this regulatory RNA segment. Together, these findings define a mechanistic framework for Regnase-1–mediated control of NFKBIZ, linking its cleavage activity to both lymphomagenesis and viral pathogenesis.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".