Insulin Inhibits IL-10–Mediated Regulatory T Cell Function: Implications for Obesity
Bibliographic record
Abstract
Chronic inflammation is known to promote metabolic dysregulation in obesity and type 2 diabetes. Although the precise origin of the unchecked inflammatory response in obesity is unclear, it is known that overproduction of proinflammatory cytokines by innate immune cells affects metabolism. For example, TNF-α contributes to the inability of cells to respond to insulin and to the increase in levels of insulin. Whether this hyperinsulinemia itself is part of a feedback loop that affects the progression of chronic adipose inflammation is unknown. In this article, we show that regulatory T cells (Tregs) express the insulin receptor, and that high levels of insulin impair the ability of Tregs to suppress inflammatory responses via effects on the AKT/mTOR signaling pathway. Insulin activated AKT signaling in Tregs, leading to inhibition of both IL-10 production and the ability of Tregs to suppress the production of TNF-α by macrophages in a contact-independent manner. The effect of insulin on Treg suppression was limited to IL-10 production and it did not alter the expression of other proteins associated with Treg function, including CTLA-4, CD39, and TGF-β. In a model of diet-induced obesity, Tregs from the visceral adipose tissue of hyperinsulinemic, obese mice showed a similar specific decrease in IL-10 production, as well as a parallel increase in production of IFN-γ. These data suggest that hyperinsulinemia may contribute to the development of obesity-associated inflammation via a previously unknown effect of insulin on the IL-10-mediated function of Tregs.
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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".