The Proinflammatory Cytokine Tumor Necrosis Factor-α Increases the Amount of Glucose Transporter-4 at the Surface of Muscle Cells Independently of Changes in Interleukin-6
Bibliographic record
Abstract
TNFalpha is a proinflammatory cytokine secreted by macrophages in response to bacterial infection. Recently new evidence has emerged suggesting that stressed or injured myocytes produce TNFalpha that then acts as an autocrine and/or paracrine mediator. TNFalpha receptors types 1 and 2 are present in skeletal muscle cells, and muscle cells can secrete, in addition to TNFalpha, other cytokines such as IL-1beta or IL-6. Furthermore, the plasma concentration of TNFalpha is elevated in insulin-resistant states associated with obesity and type 2 diabetes. Here we show that TNFalpha increased the amount of glucose transporter (GLUT)-4 at the plasma membrane and also glucose uptake in the L6 muscle cell line stably expressing GLUT4 tagged with the c-myc epitope. Regardless of the state of differentiation of the L6 cells, TNFalpha did not affect the rate of proliferation or of apoptosis. The stimulatory effects of TNFalpha on cell surface GLUT4 and glucose uptake were blocked by nuclear factor-kappaB and p38MAPK pathway specific inhibitors (Bay 11-7082 and SB220025), and these two pathways were stimulated by TNFalpha. Furthermore, although TNFalpha increased IL-6 mRNA and protein expression, IL-6 did not mediate the effects of TNFalpha on cell surface GLUT4 levels, which also did not require de novo protein synthesis. The results indicate that TNFalpha can stimulate glucose uptake in L6 muscle cells by inducing GLUT4 translocation to the plasma membrane, possibly through activation of the nuclear factor-kappaB and p38MAPK signaling pathways and independently of the production of IL-6.
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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) | 0.002 | 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".