NF-κB and IκBα Are Found in the Mitochondria
Bibliographic record
Abstract
The transcription factor NF-kappa B has been shown to be predominantly cytoplasmically localized in the absence of an inductive signal. Stimulation of cells with inflammatory cytokines such as tumor necrosis factor alpha or interleukin-1 induces the degradation of I kappa B, the inhibitor of NF-kappa B, allowing nuclear accumulation of NF-kappa B and regulation of specific gene expression. The degradation of I kappa B is controlled initially by phosphorylation induced by the I kappa B kinase, which leads to ubiquitination and subsequent proteolysis of the inhibitor by the proteasome. We report here that NF-kappa B and I kappa B alpha (but not I kappa B beta) are also localized in the mitochondria. Stimulation of cells with tumor necrosis factor alpha leads to the phosphorylation of mitochondrial I kappa B alpha and its subsequent degradation by a nonproteasome-dependent pathway. Interestingly, expression of the mitochondrially encoded cytochrome c oxidase III and cytochrome b mRNAs were reduced by cytokine treatment of cells. Inhibition of activation of mitochondrial NF-kappa B by expression of the superrepressor form of I kappa B alpha inhibited the loss of expression of both cytochrome c oxidase III and cytochrome b mRNA. These data indicate that the NF-kappa B regulatory pathway exists in mitochondria and that NF-kappa B can negatively regulate mitochondrial mRNA expression.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".