Keratin 8/18 regulation of insulin receptor signaling and trafficking in hepatocytes through a concerted phosphoinositide‐dependent Akt and Rab5 modulation
Bibliographic record
Abstract
ABSTRACT Keratins (Ks) are epithelial cell intermediate filament (IF) proteins that are expressed as pairs in a differentiation‐regulated manner. Hepatocyte IFs are made only of K8/K18 pairs, which means that a K8 loss in K8null mice leads to degradation of K18. Functionally, there is accumulating evidence that IFs contribute to signaling platforms. Here, we investigate the role of K8/K18 IFs in the regulation of insulin receptor (IR) signaling and trafficking in hepatocytes. We find that the IR substrate 1 (IRS1)/PI3K/Akt signaling cascade — downstream of IR—displays prolonged activation in K8‐null compared with wild‐type hepatocytes. Assessment of the Akt/ mammalian target of rapamycin complex 1–mediated feedback loop to IRS1/PI3K, in the absence or presence of drug inhibitors, further supports a preferential K8/K18 IF intervention at the surface membrane. In K8‐null hepatocytes, IR trafficking vesicles that are labeled by Rab5/EEA1/phosphatidylinositol 3‐phosphate accumulate at a juxtanuclear region via a microtubule‐dependent process. Moreover, interference with phosphatidylinositol 4,5‐biphosphate signaling aggravates IR/Rab5 accumulation. Overall, results uncover K8/K18 IF regulation of IR signaling via a concerted modulation of phosphatidylinositol 4,5‐biphosphate–dependent IRS1/PI3K/Akt signaling and Rab5/phosphatidylinositol 3‐phosphate/microtubule trafficking in hepatocytes.—Roux, A., Loranger, A., Lavoie, J. N., Marceau, N. Keratin 8/18 regulation of insulin receptor signaling and trafficking in hepatocytes through a concerted phosphoinositide‐dependent Akt and Rab5 modulation. FASEB J . 31, 3555–3573 (2017). www.fasebj.org
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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".