Keratin impact on PKCδ- and ASMase-mediated regulation of hepatocyte lipid raft size – implication for FasR-associated apoptosis
Bibliographic record
Abstract
Keratins are epithelial cell intermediate filament (IF) proteins that are expressed as pairs in a cell-differentiation-regulated manner. Hepatocytes express the keratin 8 and 18 pair (denoted K8/K18) of IFs, and a loss of K8 or K18, as in K8-null mice, leads to degradation of the keratin partner. We have previously reported that a K8/K18 loss in hepatocytes leads to altered cell surface lipid raft distribution and more efficient Fas receptor (FasR, also known as TNFRSF6)-mediated apoptosis. We demonstrate here that the absence of K8 or transgenic expression of the K8 G62C mutant in mouse hepatocytes reduces lipid raft size. Mechanistically, we find that the lipid raft size is dependent on acid sphingomyelinase (ASMase, also known as SMPD1) enzyme activity, which is reduced in absence of K8/K18. Notably, the reduction of ASMase activity appears to be caused by a less efficient redistribution of surface membrane PKCδ toward lysosomes. Moreover, we delineate the lipid raft volume range that is required for an optimal FasR-mediated apoptosis. Hence, K8/K18-dependent PKCδ- and ASMase-mediated modulation of lipid raft size can explain the more prominent FasR-mediated signaling resulting from K8/K18 loss. The fine-tuning of ASMase-mediated regulation of lipid rafts might provide a therapeutic target for death-receptor-related liver diseases.
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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".