MEK/ERK pathway mediates PKC activation‐induced recruitment of PKCζ and MMP‐9 to podosomes
Bibliographic record
Abstract
Podosomes are adhesive structures on the ventral surface of cells that invade and degrade the extracellular matrix. Recently, we reported that phorbol 12,13-dibutyrate (PDBu), a protein kinase C (PKC) activator, induced podosome formation in normal human bronchial epithelial (NHBE) cells, and atypical PKCζ regulated MMP-9 recruitment to podosomes for its release and activation. The objective of this study was to explore signaling pathways that are involved in PKC activation-induced podosome formation and matrix degradation. Herein, we found that PDBu increased phosphorylation of PI3K p85, Akt, Src, ERK1/2, and JNK. Inhibitors for PI3K, Akt, and Src suppressed PDBu-induced podosome formation and matrix degradation. In contrast, blockers for MEK/ERK or JNK did not inhibit podosome formation but reduced proteolytic activity of podosomes. Inhibition of PKCζ activity with its pseudosubstrate peptide (PS)-inhibited PDBu-induced phosphorylation of MEK/ERK and JNK. On the other hand, inhibition of MEK/ERK or JNK pathway did not affect PKCζ phosphorylation, but reduced the recruitment of PKCζ and MMP-9 to podosomes. We conclude that PKCζ may regulate MEK/ERK and JNK phosphorylation and in turn activated MEK/ERK and JNK may regulate the proteolytic activity of PDBu-induced podosomes by influencing the recruitment of PKCζ and MMP-9 to podosomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".