Follicular regulatory helper T cells control the response of regulatory B cells to a high-cholesterol diet
Bibliographic record
Abstract
AIMS: B cell functions in the process of atherogenesis have been investigated but several aspects remain to be clarified. METHODS AND RESULTS: In this study, we show that follicular regulatory helper T cells (TFR) control regulatory B cell (BREG) populations in Apoe-/- mice models on a high-cholesterol diet (HCD). Feeding mice with HCD resulted in up-regulation of TFR and BREG cell populations, causing the suppression of proatherogenic follicular helper T cell (TFH) response. TFH cell modulation is correlated with the growth of atherosclerotic plaque size in thoracoabdominal aortas and aortic root plaques, suggesting that TFR cells are atheroprotective. During adoptive transfer experiments, TFR cells transferred into HCD mice decreased TFH cell populations, atherosclerotic plaque size, while BREG cell population and lymphangiogenesis are significantly increased. CONCLUSION: Our results demonstrate that, through different strategies, both TFR and TFH cells modulate anti- and pro-atherosclerotic immune processes in an Apoe-/- mice model since TFR cells are able to regulate both TFH and BREG cell populations as well as lymphangiogenesis and lipoprotein metabolism.
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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) | 0.002 | 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".