Reduced inflammatory responses of follicular helper T cell promote the development of regulatory B cells after Roux‐en‐Y gastric bypass
Bibliographic record
Abstract
Bariatric surgery is currently the most effective strategy in treating severe obesity and its comorbidities, such as type 2 diabetes (T2D). However, the mechanism through which bariatric surgery mediates its benefits is not completely understood. Since obesity and T2D represent yet another inflammatory disease, and follicular helper T (Tfh) cells play important roles in inflammatory disorders, we investigated whether the Tfh activity was altered after Roux-en-Y gastric bypass (RYGB), one of the most common bariatric surgery procedures. We found that the Tfh cells after RYGB were not significantly changed in number, but presented altered cytokine secretion profile, including lower interferon (IFN)-γ, interleukin (IL)-2, IL-4, and IL-17 secretion. Tfh cells after RYGB also downregulated inducible co-stimulator and programmed death-1. Interestingly, after Tfh cell-naive B cell coculture, Tfh cells after RYGB secreted more IL-10 than autologous Tfh cells before RYGB. The frequencies of IL-10-expressing and transforming growth factor (TGF)-β-expressing regulatory B cells after Tfh cell-naive B cell coculture were directly correlated with the frequency of IL-10-expressing Tfh cells. Depletion of IL-10 in the coculture, however, resulted in fewer regulatory B cells. Finally, patients with greater increase in IL-10-expressing Tfh cells presented further reductions in body mass index, glycaemia, and body fat percentage. Together, these data demonstrated that the Tfh cells after RYGB presented lower inflammatory status and secreted higher IL-10, through which these Tfh cells promoted the development of regulatory B cells. Higher IL-10-expressing Tfh cell level also predicted better patient response to RYGB.
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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) | 0.001 | 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".