Protein Tyrosine Phosphatase‐1B (PTP‐1B) Knockdown Improves Palmitate‐Induced Insulin Resistance in C2C12 Skeletal Muscle Cells
Bibliographic record
Abstract
Insulin resistance is the central defect in type 2 diabetes and obesity. During the development of insulin resistance a lipid accumulation is accompanied by increased PTP-1B expression in the muscle. The aim of this study was to examine the effects of PTP-1B knockdown on insulin signaling and insulin resistance in the presence or absence of palmitate in C2C12 skeletal muscle cells. A stable C2C12 cell line was established using short hairpin RNA (shRNA) to knockdown protein expression of PTP1B. Analysis of PTP-1B protein expression and phosphorylation and protein levels of IRS-1 and Akt were detected by western blot. The effects of PTP-1B knockdown on the glucose uptake was also measured in C2C12 cells. The stable C2C12 cell line harboring the PTP-1B shRNA showed 62% decrease in the PTP-1B protein levels. 0.5 mM palmitate significantly induced insulin resistance in both control (26%) and PTP-1B knockdown cells (16.5%) compared to the untreated cells. Under treatment with palmitate, insulin stimulated phosphorylation of IRS-1 (Tyr632) and Akt (Ser473) in knockdown cells was significantly 1.55- and 1.86-fold, respectively, greater than the controls. In the presence of palmitate, insulin dependent glucose uptake was significantly about 3-fold higher in PTP-1B knockdown stable C2C12 cells compared to the control cells. Our data showed that decreasing the PTP-1B protein level by shRNA can enhance the activity of important elements of insulin signaling. The improvement in insulin action persisted even in palmitate treated insulin resistant myotubes.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".