Keratin 8/18 Modulation of Protein Kinase C-mediated Integrin-dependent Adhesion and Migration of Liver Epithelial Cells
Bibliographic record
Abstract
Keratins are intermediate filament (IF) proteins of epithelial cells, expressed as pairs in a lineage/differentiation manner. Hepatocyte and hepatoma cell IFs are made solely of keratins 8/18 (K8/K18), the hallmark of all simple epithelia. Cell attachment/spreading (adhesion) and migration involve the formation of focal adhesions at sites of integrin interactions with extracellular matrix, actin adaptors such as talin and vinculin, and signaling molecules such as focal adhesion kinase (FAK) and member(s) of the protein kinase C (PKC) family. Here, we identify the novel PKCdelta as mediator of the K8/K18 modulation of hepatoma cell adhesion and migration. We also demonstrate a K8/K18-dependent relationship between PKCdelta and FAK activation through an integrin/FAK-positive feedback loop, in correlation with a reduced FAK time residency at focal adhesions. Notably, a K8/K18 loss results to a time course modulation of the receptor of activated C-kinase-1, beta1-integrin, plectin, PKC, and c-Src complex formation. Although the K8/K18 modulation of hepatocyte adhesion also occurs through a PKC mediation, these differentiated epithelial cells exhibit minimal migrating ability, in link with marked differences in protein partner content and distribution. Together, these results uncover a key regulatory function for K8/K18 IFs in the PKC-mediated integrin/FAK-dependent adhesion and migration of simple epithelial cells.
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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 | 0.000 |
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".