T reg–specific insulin receptor deletion prevents diet-induced and age-associated metabolic syndrome
Bibliographic record
Abstract
Adipose tissue (AT) regulatory T cells (T regs) control inflammation and metabolism. Diet-induced obesity causes hyperinsulinemia and diminishes visceral AT (VAT) T reg number and function, but whether these two phenomena were mechanistically linked was unknown. Using a T reg-specific insulin receptor (Insr) deletion model, we found that diet-induced T reg dysfunction is driven by T reg-intrinsic insulin signaling. Compared with Foxp3cre mice, after 13 wk of high-fat diet, Foxp3creInsrfl/fl mice exhibited improved glucose tolerance and insulin sensitivity, effects associated with lower AT inflammation and increased numbers of ST2+ T regs in brown AT, but not VAT. Similarly, Foxp3creInsrfl/fl mice were protected from the metabolic effects of aging, but surprisingly had reduced VAT T regs and increased VAT inflammation compared with Foxp3cre mice. Thus, in both diet- and aging-associated hyperinsulinemia, excessive Insr signaling in T regs leads to undesirable metabolic outcomes. Ablation of Insr signaling in T regs represents a novel approach to mitigate the detrimental effects of hyperinsulinemia on immunoregulation of metabolic syndrome.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".