Differential Contribution of Insulin Receptor Substrates 1 Versus 2 to Insulin Signaling and Glucose Uptake in L6 Myotubes
Bibliographic record
Abstract
Insulin receptor substrates-1 and 2 (IRS-1 and IRS-2) are pivotal in relaying insulin signaling in insulin-responsive tissues such as muscle. However, the precise contribution of IRS-1 vis-a-vis IRS-2 in insulin-mediated metabolic and mitogenic responses has not been compared directly in differentiated muscle cells. This study aimed to determine the relative contribution of IRS-1 versus IRS-2 in these responses, using small interfering RNA (siRNA)-mediated specific gene silencing. In L6 myotubes, transfection of siRNA targeted specifically against IRS-1 (siIRS-1) or IRS-2 (siIRS-2) reduced the cognate protein expression by 70-75%. Insulin-induced ERK phosphorylation was much more sensitive to IRS-2 than IRS-1 ablation, whereas p38MAPK phosphorylation was reduced by 43 or 62% in myotubes treated with siIRS-1 or siIRS-2, respectively. Insulin-induced Akt1 and Akt2 phosphorylation was reduced in myotubes treated with siIRS-1, but only Akt2 phosphorylation was reduced in myotubes treated with siIRS-2. In contrast, siIRS-1 treatment caused a marked reduction in insulin-induced actin remodeling, glucose uptake, and GLUT4 translocation, and siIRS-2 was without effect on these responses. Notably, combined siIRS-1 and siIRS-2, although reducing each IRS by around 75%, caused no further drop in glucose uptake than that achieved with siIRS-1 alone, but abolished p38MAPK phosphorylation. We conclude that insulin-stimulated Akt1 phosphorylation, actin remodeling, GLUT4 translocation, and glucose uptake are regulated mainly by IRS-1, whereas IRS-2 contributes selectively to ERK signaling, and Akt2 and p38MAPK lie downstream of both IRS in muscle cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".