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Record W2098143217 · doi:10.1126/stke.3812007pe14

Metabolic Targeting as an Anticancer Strategy: Dawn of a New Era?

2007· article· en· W2098143217 on OpenAlexaff
James Pan, Tak W. Mak

Bibliographic record

VenueScience s STKE · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer Research
Fundersnot available
KeywordsCitric acid cyclePyruvate dehydrogenase complexPyruvate dehydrogenase kinaseGlycolysisWarburg effectPyruvate kinaseMitochondrionAdenosine triphosphateAnaerobic glycolysisBiochemistryCell biologyPyruvate decarboxylationBiologyChemistryMetabolismEnzyme

Abstract

fetched live from OpenAlex

As a result of a spectrum of mitochondrial defects, tumor cells often preferentially use glycolysis to generate adenosine triphosphate (ATP), even in the presence of oxygen, a phenomenon known as aerobic glycolysis, or the "Warburg effect." Dichloroacetate (DCA) is an inhibitor of mitochondrial pyruvate dehydrogenase kinase (PDK), which inhibits pyruvate dehydrogenase (PDH), a gatekeeping enzyme for the entry of pyruvate into the mitochondrial tricarboxylic acid (TCA) cycle. In mice, DCA treatment appears to reactivate mitochondrial respiration in tumor cells, induces their selective killing, and suppresses cancer growth. These observations provide intriguing insights into the plasticity of tumor metabolism that may offer new opportunities for therapeutic intervention.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0010.001
Research integrity0.0030.005
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 head0.014
GPT teacher head0.310
Teacher spread0.296 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

Quick stats

Citations129
Published2007
Admission routes1
Has abstractyes

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Same venueScience s STKESame topicCancer, Hypoxia, and MetabolismFrench-language works237,207