IKK promotes naïve T cell survival by repressing RIPK1-dependent apoptosis and activating NF-κB
Bibliographic record
Abstract
The inhibitor of κB kinase (IKK) complex regulates the activation of the nuclear factor κB (NF-κB) family of transcription factors. In addition, IKK represses extrinsic cell death pathways dependent on receptor-interacting serine/threonine-protein kinase 1 (RIPK1) by directly phosphorylating this kinase. Here, we showed that peripheral naïve T cells in mice required the continued expression of IKK1 and IKK2 for their survival; however, the loss of these cells was only partially prevented when extrinsic cell death pathways were blocked by either deleting Casp8 (which encodes the apoptosis-inducing caspase 8) or inhibiting the kinase activity of RIPK1. Inducible deletion of Rela (which encodes the NF-κB p65 subunit) in mature CD4 + T cells also resulted in loss of naïve CD4 + T cells and in reduced abundance of the interleukin-7 receptor (IL-7R) encoded by the NF-κB target Il7r , revealing an additional reliance upon NF-κB for the long-term survival of mature T cells. Together, these data indicate that the IKK-dependent survival of naïve CD4 + T cells depends on both repression of extrinsic cell death pathways and activation of an NF-κB–dependent survival program.
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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) | 0.002 | 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".