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Record W2401815452 · doi:10.7150/jca.14274

Warburg Effect - a Consequence or the Cause of Carcinogenesis?

2016· review· en· W2401815452 on OpenAlexafffund
Slobodan Dević

Bibliographic record

VenueJournal of Cancer · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWarburg effectGlycolysisCarcinogenesisAnaerobic glycolysisCancerCitric acid cycleCarbohydrate metabolismCancer cellLactic acidCancer researchBiologyChemistryBiochemistryCell biologyEnzymeGenetics

Abstract

fetched live from OpenAlex

Ever since its discovery (1924) the Warburg effect (aerobic glycolysis) remains an unresolved puzzle: why the aggressive cancer cells "prefer" to use the energetically highly inefficient method of burning the glucose at the cellular level? While in the course of the last 90 years several hypotheses have been suggested, to this date there is no clear explanation of this rather unusual effect. Even though it is commonly assumed that Warburg effect is a consequence of carcinogenesis, yet another hypothesis could be brought up that the cellular switch to aerobic glycolysis may represent the very point in time when a normal cell becomes cancerous. Furthermore, this switch may happen at the point where the fate of pyruvic acid is determined, caused by the inadequate supply of enzymes that promote citric as opposed to lactic acid cycle. Currently, few clinical observations, like low cancer incidence in Type 1 diabetes mellitus and increased cancer incidence in people on high carbohydrate diets might be called upon to support such hypothesis.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.037
GPT teacher head0.370
Teacher spread0.333 · 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 designNot applicable
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

Citations141
Published2016
Admission routes2
Has abstractyes

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