Interleukin-6 Treatment Results in GLUT4 Translocation and AMPK Phosphorylation in Neuronal SH-SY5Y Cells
Bibliographic record
Abstract
Interleukin-6 (IL-6) is a pleiotropic cytokine that can be released from the brain during prolonged exercise. In peripheral tissues, exercise induced IL-6 can result in GLUT4 translocation and increased glucose uptake through AMPK activation. GLUT4 is expressed in the brain and can be recruited to axonal plasma membranes with neuronal activity through AMPK activation. The aim of this study is to examine if IL-6 treatment: (1) results in AMPK activation in neuronal cells, (2) increases the activation of proteins involved in GLUT4 translocation, and (3) increases neuronal glucose uptake. Retinoic acid was used to differentiate SH-SY5Y neuronal cells. Treatment with 100 nM of insulin increased the phosphorylation of Akt and AS160 (p < 0.05). Treatment with 20 ng/mL of IL-6 resulted in the phosphorylation of STAT3 at Tyr705 (p ≤ 0.05) as well as AS160 (p < 0.05). Fluorescent Glut4GFP imaging revealed treatment with 20ng/mL of IL-6 resulted in a significant mobilization towards the plasma membrane after 5 min until 30 min. There was no difference in GLUT4 mobilization between the insulin and IL-6 treated groups. Importantly, IL-6 treatment increased glucose uptake. Our findings demonstrate that IL-6 and insulin can phosphorylate AS160 via different signaling pathways (AMPK and PI3K/Akt, respectively) and promote GLUT4 translocation towards the neuronal plasma membrane, resulting in increased neuronal glucose uptake in SH-SY5Y cells.
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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) | 0.001 | 0.001 |
| 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) | 0.003 | 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".