Angiotensin II Decreases Glucose Uptake by Downregulation of GLUT1 in the Cell Membrane of the Vascular Smooth Muscle Cell Line A10
Bibliographic record
Abstract
Recent evidence suggests a crosstalk between angiotensin II (Ang II) and insulin. However, whether this crosstalk affects glucose uptake, particularly in terms of actin filament involvement, has not yet been studied in vascular smooth muscle cells. Pretreatment of cells with either Ang II or cytochalasin D disarranged actin filaments in a time-dependent manner and inhibited glucose uptake. However, insulin increased actin reorganization and glucose uptake. Membrane fractionation studies showed that Ang II decreased GLUT-1 at the cell membrane, whereas it increased GLUT-1 in the cytoplasm, indicating that Ang II may cause internalization of GLUT-1 via actin disorganization, consequently decreasing glucose uptake. The effects of Ang II on glucose uptake and actin reorganization were blocked by AT1 receptor antagonist, but not by AT2 antagonist. Either P38 or ERK1/2 inhibitors partially reversed the Ang II-inhibited actin reorganization and glucose uptake, suggesting that MAPK signaling pathways could be involved as downstream events in Ang II signaling, and this signaling may interfere with insulin-induced actin reorganization and glucose uptake. These data imply that Ang II induces insulin resistance by decreasing glucose uptake via disarrangement of actin filaments, which provides a novel insight into understanding of insulin resistance by Ang II at the molecular level.
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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".