Acidity promotes the differentiation of immunosuppressive regulatory T cells
Bibliographic record
Abstract
Abstract The metabolic milieu is emerging as a major contributing factor in the maintenance of the immunosuppressive microenvironment within tumors. In particular, the presence of lactic acid produced by highly glycolytic cancer cells is known to suppress antitumor immune cell subsets while promoting immunosuppressive cell populations, such as regulatory T cells (Tregs). Unlike conventional T cells, Tregs have a unique, potent ability to take up lactic acid to fuel both mitochondrial metabolism and gluconeogenesis, thus supporting suppressive function and proliferation. In this issue of the European Journal of Immunology [ Eur. J. Immunol . 2023.53:2250258], Rao et al. uncover a novel mechanism by which lactic acid can support Treg accumulation within tumors in mice. This study shows that lactic acid, through a pH‐dependent mechanism rather than lactate itself, promotes TGFβ‐induced differentiation of Tregs from conventional CD4 + T cells. These findings build on the already multifaceted role of lactic acid in maintaining an immunosuppressive tumor microenvironment.
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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) | 0.003 | 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".