Constitutive Association of TGF-β–Activated Kinase 1 with the IκB Kinase Complex in the Nucleus and Cytoplasm of Human Neutrophils and Its Impact on Downstream Processes
Bibliographic record
Abstract
Neutrophils influence innate and adaptative immunity by generating numerous mediators whose regulation largely depends on the IkappaB kinase (IKK)/IkappaB/NF-kappaB signaling cascade. A singular feature of neutrophils is that they express several components of this pathway (namely, NF-kappaB/Rel proteins and IkappaB-alpha) in both the nucleus and cytoplasm. We recently reported that the IKK complex of neutrophils is similarly expressed and activated in both cellular compartments. However, the upstream IKK kinase has not yet been identified. In this study, we report that neutrophils express the mitogen-activated protein 3 kinase, TGF-beta-activated kinase 1 (TAK1), as well as its associated partners, TAK1-binding protein (TAB) 1, TAB2, and TAB4, in both the cytoplasm and nucleus. Following cell stimulation by TNF-alpha or LPS, TAK1 becomes rapidly and transiently activated. Blocking TAK1 kinase activity with a highly selective inhibitor (5z-7-oxozeaenol) attenuated the phosphorylation of nuclear and cytoplasmic IKKalpha/beta, IkappaB-alpha, and RelA, and also impaired IkappaB-alpha degradation and NF-kappaB DNA binding in activated neutrophils. Moreover, TAK1 was found to be involved in the activation of p38 MAPK and ERK, which also influence cytokine generation in neutrophils. As a result, inflammatory cytokine expression and release were profoundly impaired following TAK1 inhibition. Similarly, the delayed apoptosis observed in response to LPS or TNF-alpha was reversed by TAK1 inhibition. By contrast, IKKgamma phosphorylation and STAT1 activation were unaffected by TAK1 inhibition. Our data establish the central role of TAK1 in controlling nuclear and cytoplasmic signaling cascades in primary neutrophils, making it a promising target for therapeutic intervention in view of the foremost role of neutrophils in several chronic inflammatory conditions.
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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".