Protein Kinase C-associated Kinase (PKK) Mediates Bcl10-independent NF-κB Activation Induced by Phorbol Ester
Bibliographic record
Abstract
Protein kinase C-associated kinase (PKK) is a recently described kinase of unknown function that was identified on the basis of its specific interaction with PKC beta. PKK contains N-terminal kinase and C-terminal ankyrin repeats domains linked to an intermediate region. Here we report that the kinase domain of PKK is highly homologous to that of two mediators of nuclear factor-kappa B (NF-kappa B) activation, RICK and RIP, but these related kinases have different C-terminal domains for binding to upstream factors. We find that expression of PKK, like RICK and RIP, induces NF-kappa B activation. Mutational analysis revealed that the kinase domain of PKK is essential for NF-kappa B activation, whereas replacement of serine residues in the putative activation loop did not affect the ability of PKK to activate NF-kappa B. A catalytic inactive PKK mutant inhibited NF-kappa B activation induced by phorbol ester and Ca(2+)-ionophore, but it did not block that mediated by tumor necrosis factor alpha, interleukin-1 beta, or Nod1. Inhibition of NF-kappa B activation by dominant negative PKK was reverted by co-expression of PKC beta I, suggesting a functional association between PKK and PKC beta I. PKK-mediated NF-kappa B activation required IKK alpha and IKK beta but not IKK gamma, the regulatory subunit of the IKK complex. Moreover, NF-kappa B activation induced by PKK was not inhibited by dominant negative Bimp1 and proceeded in the absence of Bcl10, two components of a recently described PKC signaling pathway. These results suggest that PKK is a member of the RICK/RIP family of kinases, which is involved in a PKC-activated NF-kappa B signaling pathway that is independent of Bcl10 and IKK gamma.
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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 | 0.000 | 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".