Protein-tyrosine Phosphatase-1B Negatively Regulates Insulin Signaling in L6 Myocytes and Fao Hepatoma Cells
Bibliographic record
Abstract
Insulin signaling is regulated by tyrosine phosphorylation of the signaling molecules, such as the insulin receptor and insulin receptor substrates (IRSs). Therefore, the balance between protein-tyrosine kinases and protein-tyrosine phosphatase activities is thought to be important in the modulation of insulin signaling in insulin-resistant states. We thus employed the adenovirus-mediated gene transfer technique, and we analyzed the effect of overexpression of a wild-type protein-tyrosine phosphatase-1B (PTP1B) on insulin signaling in both L6 myocytes and Fao cells. In both cells, PTP1B overexpression blocked insulin-stimulated tyrosine phosphorylation of the insulin receptor and IRS-1 by more than 70% and resulted in a significant inhibition of the association between IRS-1 and the p85 subunit of phosphatidylinositol 3-kinase and Akt phosphorylation as well as mitogen-activated protein kinase phosphorylation. Moreover, insulin-stimulated glycogen synthesis was also inhibited by PTP1B overexpression in both cells. These effects were specific for insulin signaling, because platelet-derived growth factor (PDGF)-stimulated PDGF receptor tyrosine phosphorylation and Akt phosphorylation were not inhibited by PTP1B overexpression. The present findings demonstrate that PTP1B negatively regulates insulin signaling in L6 and Fao cells, suggesting that PTP1B plays an important role in insulin resistance in muscle and liver.
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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) | 0.001 | 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".