Canonical TGF-β Signaling Pathway Represses Human NK Cell Metabolism
Bibliographic record
Abstract
Cytokines stimulate rapid metabolic changes in human NK cells, including increases in both glycolysis and oxidative phosphorylation pathways. However, how these are subsequently regulated is not known. In this study, we demonstrate that TGF-β can inhibit many of these metabolic changes, including oxidative phosphorylation, glycolytic capacity, and respiratory capacity. TGF-β also inhibited cytokine-induced expression of the transferrin nutrient receptor CD71. In contrast to a recent report on murine NK cells, TGF-β-mediated suppression of these metabolic responses did not involve the inhibition of the metabolic regulator mTORC1. Inhibition of the canonical TGF-β signaling pathway was able to restore almost all metabolic and functional responses that were inhibited by TGF-β. These data suggest that pharmacological inhibition of TGF-β could provide a metabolic advantage to NK cells that is likely to result in improved functional responses. This has important implications for NK cell-based cancer immunotherapies.
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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) | 0.001 | 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".