Inhibitory actions of ceramide upon PKC-ε/ERK interactions
Bibliographic record
Abstract
We have previously shown that interleukin-1 receptor-generated ceramide induces growth arrest in smooth muscle pericytes by inhibiting an upstream kinase in the extracellular signal-regulated kinase (ERK) cascade. Here, we now report the mechanism by which ceramide inhibits ERK activity. Ceramide renders the human embryonic kidney 293 cells (HEK 293) resistant to the mitogenic actions of growth factors and activators of protein kinase C (PKC). A role for PKC to mediate ceramide inhibition of growth factor-induced ERK activity and mitogenesis is suggested, as exogenous ceramide directly inhibits both immunoprecipitated and recombinant PKC-epsilon activities. To confirm that PKC-epsilon is necessary for ceramide-inhibited ERK activity, HEK 293 cells were transfected with a dominant-negative mutant of PKC-epsilon (DeltaPKC-epsilon). These transfected cells respond to insulin-like growth factor I (IGF-I) with a significantly decreased ERK activity that is not further reduced by ceramide treatment. Coimmunoprecipitation studies reveal that the treatment with IGF-I induces the association of ERK with PKC-epsilon but not with PKC-zeta. Ceramide treatment significantly inhibits the IGF-I-induced PKC-epsilon interaction with bioactive phosphorylated ERK. Ceramide also inhibits IGF-I-induced PKC-epsilon association with Raf-1, an upstream kinase of ERK. Together, these studies demonstrate that ceramide exerts anti-mitogenic actions by limiting the ability of PKC-epsilon to form a signaling complex with Raf-1 and ERK.
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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 | 0.000 |
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".