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Record W4415589898 · doi:10.1101/2025.10.26.684630

AMPK Repositions Early Endosomes via Gapex-5 to Promote Delivery of Iron to Mitochondria

2025· preprint· W4415589898 on OpenAlexafffund
Ayshin Mehrabi, Laura A. Orofiamma, Alyona Ivanova, Natalie Uzynski, Maria Narciso, Roberto J. Botelho, Eden Fussner-Dupas, Costin N. Antonescu

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of British ColumbiaToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEndosomeAMPKMitochondrionOrganelleAMP-activated protein kinaseRegulatorTransport proteinAutophagyProtein kinase A

Abstract

fetched live from OpenAlex

Abstract The regulation of the spatial organization of organelles within cells is critical for coordinating signaling, membrane traffic, and metabolite exchange. Metabolic cues regulate the position and function of lysosomes, yet whether and how metabolic signals may similarly regulate other organelles such as early endosomes (EEs) remains unclear. We find that AMP-activated protein kinase (AMPK), a key regulator of metabolic homeostasis activated in response to nutrient scarcity, triggers movement of EEs to the perinuclear region of cells, leading to enhanced proximity of endosomes to mitochondria and increased delivery of iron to mitochondria. The movement of EEs and increased mitochondrial iron content elicited by AMPK activation requires Gapex-5, a GEF for the early endosome Rab5 previously shown to be an AMPK substrate. These findings reveal a mechanism by which AMPK reprograms endosome positioning to facilitate inter-organelle communication and iron delivery to mitochondria to support metabolic adaptation under conditions of nutrient scarcity.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicMetabolism, Diabetes, and Cancer→French-language works237,207→