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Record W2802860523 · doi:10.4049/jimmunol.1701461

Canonical TGF-β Signaling Pathway Represses Human NK Cell Metabolism

2018· article· en· W2802860523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Immunology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsTrinity College
Fundersnot available
KeywordsOxidative phosphorylationmTORC1Cell biologySignal transductionBiologyMetabolic pathwayTransforming growth factorGlycolysisPhosphorylationCytokineRegulatorMetabolismBiochemistryImmunologyGenePI3K/AKT/mTOR pathway

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.016
GPT teacher head0.248
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it