Constitutive Nuclear Expression of the IκB Kinase Complex and Its Activation in Human Neutrophils
Bibliographic record
Abstract
A singular feature of human neutrophils is that they constitutively express substantial amounts of NF-kappaB/Rel proteins and IkappaB-alpha in the nucleus. In this study, we show that in these cells, IkappaB kinase alpha (IKKalpha), IKKbeta, and IKKgamma also partially localize to the nucleus, whereas IKK-related kinases (IKKepsilon, TANK-binding kinase-1) are strictly cytoplasmic, and the NF-kappaB-inducing kinase is strictly nuclear. Following neutrophil activation, IKKbeta and IKKgamma become transiently phosphorylated in both the cytoplasm and nucleus, whereas IKKalpha transiently vanishes from both compartments in what appears to be an IKKbeta-dependent process. These responses are paralleled by the degradation of IkappaB-alpha, and by the phosphorylation of RelA on serine 536, in both compartments. Although both proteins can be IKK substrates, inhibition of IKK prevented IkappaB-alpha phosphorylation, while that of RelA was mostly unaffected. Finally, we provide evidence that the nuclear IKK isoforms (alpha, beta, gamma) associate with chromatin following neutrophil activation, which suggests a potential role in gene regulation. This is the first study to document IKK activation and the phosphorylation of NF-kappaB/Rel proteins in primary neutrophils. More importantly, our findings unveil a hitherto unsuspected mode of activation for the IKK/IkappaB signaling cascade within the cell nucleus.
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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".