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Record W2625418525 · doi:10.1111/imm.12777

Metabolic reprogramming in the tumour microenvironment: a hallmark shared by cancer cells and T lymphocytes

2017· review· en· W2625418525 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueImmunology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of Guelph
FundersOntario Veterinary College, University of GuelphTerry Fox Research Institute
KeywordsGlutaminolysisCancer cellImmune systemTumor microenvironmentBiologyCancer researchCancerGlycolysisReprogrammingOxidative phosphorylationCell biologyCancer immunotherapyMetabolic pathwayMetabolismImmunologyImmunotherapyCellBiochemistryGenetics

Abstract

fetched live from OpenAlex

Altered metabolism is a hallmark of cancers, including shifting oxidative phosphorylation to glycolysis and up-regulating glutaminolysis to divert carbon sources into biosynthetic pathways that promote proliferation and survival. Therefore, metabolic inhibitors represent promising anti-cancer drugs. However, T cells must rapidly divide and survive in harsh microenvironments to mediate anti-cancer effects. Metabolic profiles of cancer cells and activated T lymphocytes are similar, raising the risk of metabolic inhibitors impairing the immune system. Immune checkpoint blockade provides an example of how metabolism can be differentially impacted to impair cancer cells but support T cells. Implications for research with metabolic inhibitors are discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.303
Teacher spread0.277 · 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