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Record W2970122083 · doi:10.1088/1478-3975/ab3f5a

Glycolytic reprogramming in cancer cells: PKM2 dimer predominance induced by pulsatile PFK-1 activity

2019· article· en· W2970122083 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

VenuePhysical Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsMinistry of Agriculture
FundersNational Natural Science Foundation of China
KeywordsPhosphofructokinasePKM2TetramerGlycolysisAllosteric regulationDimerPyruvate kinaseChemistryBiochemistryHeLaCancer cellBiologyCell biologyEnzymeCancerCellGenetics

Abstract

fetched live from OpenAlex

The glycolytic enzyme pyruvate kinase M2 (PKM2) exists in both catalytically inactive dimeric and active tetrameric forms. In cancer cells, PKM2 dimer predominance contributes to tumor growth by triggering glycolytic reprogramming. However, the mechanism that promotes PKM2 dimer predominance over tetramer in cancer cells remains elusive. Here, we show that pulsatile phosphofructokinase (PFK-1) activity results in PKM2 dimer predominance. Mathematical simulations predict that pulsatile PFK-1 activity prevents the formation of PKM2 tetramer even under high levels of fructose-1,6-bisphosphate (FBP), a PKM2 tetramer-promoting metabolite produced by PFK-1. We experimentally confirm these predictions at the single-molecule level by providing evidence for pulsatile PFK-1 activity-induced synchronized dissociation of PKM2 tetramers and the subsequent accumulation of PKM2 dimers under high levels of FBP in HeLa cells. Moreover, we show that pulsatile PFK-1 activity-induced PKM2 dimer predominance also controls cell proliferation. Thus, our study reveals the significance of pulsatile PFK-1 activity in cancer cell metabolism.

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 categoriesnone
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 score0.239
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.288
Teacher spread0.278 · 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