Ex vivo expanded human regulatory T cells promote cholesterol efflux and PON1 expression in oxLDL-exposed macrophages via gap junction-mediated cAMP transfer
Bibliographic record
Abstract
Lipid-driven inflammation contributes to the development of atherosclerosis, and regulatory T cells (Tregs) have been proposed to influence macrophage responses to lipid stress. While adoptive Treg transfer has been shown to be safe in clinical studies, the mechanisms by which Tregs modulate macrophage lipid handling remain incompletely understood. In this study, we investigated the effects of ex vivo–expanded human Tregs on primary monocyte-derived M2-like macrophages exposed to oxidized low-density lipoprotein (oxLDL) in an in vitro coculture system. We assessed macrophage phenotype, gene expression, and cholesterol accumulation using flow cytometry, RNA sequencing, and western blotting. Our data show that coculture with Tregs attenuated oxLDL-induced pro-inflammatory responses and reduced intracellular lipid accumulation in macrophages. Mechanistically, we found evidence that Tregs transfer cyclic AMP (cAMP) into macrophages, which enhanced the ABCA1-mediated cholesterol efflux pathway and increased expression of paraoxonase-1 (PON1). These findings provide mechanistic insight into how Tregs modulate macrophage responses to oxLDL under controlled in vitro conditions. They highlight potential pathways through which Tregs may regulate macrophage lipid metabolism and inflammatory activity. Further in vivo studies will be essential to determine the physiological significance and therapeutic potential of these mechanisms.
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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) | 0.002 | 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".