Cyclosporine A and Tacrolimus Reduce the Amount of GLUT4 at the Cell Surface in Human Adipocytes: Increased Endocytosis as a Potential Mechanism for the Diabetogenic Effects of Immunosuppressive Agents
Bibliographic record
Abstract
CONTEXT: Immunosuppressive agents are associated with profound metabolic side effects including new-onset diabetes and dyslipidemia after organ transplantation. OBJECTIVE: To investigate the effects of cyclosporine A (CsA) and tacrolimus on glucose uptake and insulin signaling in human adipocytes and their impact on the regulation of cellular trafficking of the glucose transporter 4 (GLUT4). DESIGN: Isolated human adipocytes were incubated with therapeutic concentrations of either CsA or tacrolimus, and glucose uptake and expression of insulin signaling proteins were assessed. Furthermore, we studied effects of CsA and tacrolimus on the regulation of cellular trafficking of GLUT4 in differentiated human preadipocytes and L6 cells. RESULTS: CsA and tacrolimus had a concentration-dependent inhibitory effect on basal and insulin-stimulated (14)C-glucose uptake in adipocytes. Although phosphorylation at Tyr1146 of the insulin receptor was inhibited by tacrolimus, the phosphorylation and/or protein levels of the insulin signaling proteins IRS1/2, p85-PI3K, PKB, AS160, and mTORC1, as well as GLUT4 and GLUT1, were unchanged by CsA or tacrolimus. Furthermore, CsA and tacrolimus reduced the GLUT4 amount localized at the cell surface of differentiated human preadipocytes and L6 cells in the presence of insulin. This occurred by an increased rate of GLUT4 endocytosis, with no change in the exocytosis rate. CONCLUSIONS: These results suggest that therapeutic concentrations of CsA and tacrolimus can inhibit glucose uptake independent of insulin signaling by removing GLUT4 from the cell surface via an increased rate of endocytosis. This mechanism can contribute to the development of insulin resistance and diabetes associated with immunosuppressive therapy. In addition, it may provide novel pharmacological approaches for the treatment of diabetes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".