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Record W4229008120 · doi:10.1016/j.celrep.2022.110761

Caspase cleavage and nuclear retention of the energy sensor AMPK-α1 during apoptosis

2022· article· en· W4229008120 on OpenAlexfundno aff
Anees Rahman Cheratta, Faisal Thayyullathil, Simon A. Hawley, Fiona A. Ross, Abdelmajdid Atrih, Douglas J. Lamont, Siraj Pallichankandy, Karthikeyan Subburayan, Ameer Alakkal, Rachid Rezgui, D. Grahame Hardie, Sehamuddin Galadari

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsnot available
FundersSungkyunkwan UniversityYork UniversityNew York University Abu DhabiWellcome Trust
KeywordsAMPKProtein kinase ACell biologyHeterotrimeric G proteinChemistryAMP-activated protein kinaseApoptosisPhosphorylationKinaseSignal transductionBiologyBiochemistryG protein

Abstract

fetched live from OpenAlex

AMP-activated protein kinase (AMPK) coordinates energy homeostasis during metabolic and energy stress. We report that the catalytic subunit isoform AMPK-α1 (but not α2) is cleaved by caspase-3 at an early stage during induction of apoptosis. AMPK-α1 cleavage occurs following Asp529, generating an ∼58-kDa N-terminal fragment (cl-AMPK-α1) and leading to the precise excision of the nuclear export sequence (NES) from the C-terminal end. This cleavage does not affect (1) the stability of pre-formed heterotrimeric complexes, (2) the ability of cl-AMPK-α1 to become phosphorylated and activated by the upstream kinases LKB1 or CaMKK2, or (3) allosteric activation by AMP or A-769662. Importantly, cl-AMPK-α1 is only detectable in the nucleus, consistent with removal of the NES, and ectopic expression of cleavage-resistant D529A-mutant AMPK-α1 promotes cell death induced by cytotoxic agents. Thus, we have elucidated a non-canonical mechanism of AMPK activation within the nucleus, which protects cells against death induced by DNA damage.

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 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 score0.192
Threshold uncertainty score0.273

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations29
Published2022
Admission routes1
Has abstractyes

Explore more

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