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Record W4385715456 · doi:10.1111/acel.13949

Oculopharyngeal muscular dystrophy mutations link the <scp>RNA</scp>‐binding protein <scp>HNRNPQ</scp> to autophagosome biogenesis

2023· article· en· W4385715456 on OpenAlexfundno aff
Hasan Ishtayeh, Margarita Galves, Tania Barnatan, Yevgeny Berdichevsky, Fatima Amer‐Sarsour, Metsada Pasmanik‐Chor, Itzhak Braverman, Sergiu C. Blumen, Avraham Ashkenazi

Bibliographic record

VenueAging Cell · 2023
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsnot available
FundersAzrieli Foundation
KeywordsAutophagyBiologyOculopharyngeal muscular dystrophyCell biologyRNA-binding proteinAutophagosomeBAG3RNAMuscular dystrophyGeneticsGene

Abstract

fetched live from OpenAlex

Autophagy is an intracellular degradative process with an important role in cellular homeostasis. Here, we show that the RNA binding protein (RBP), heterogeneous nuclear ribonucleoprotein Q (HNRNPQ)/SYNCRIP is required to stimulate early events in autophagosome biogenesis, in particular the induction of VPS34 kinase by ULK1-mediated beclin 1 phosphorylation. The RBPs HNRNPQ and poly(A) binding protein nuclear 1 (PABPN1) form a regulatory network that controls the turnover of distinct autophagy-related (ATG) proteins. We also show that oculopharyngeal muscular dystrophy (OPMD) mutations engender a switch from autophagosome stimulation to autophagosome inhibition by impairing PABPN1 and HNRNPQ control of the level of ULK1. The overexpression of HNRNPQ in OPMD patient-derived cells rescues the defective autophagy in these cells. Our data reveal a regulatory mechanism of autophagy induction that is compromised by PABPN1 disease mutations, and may thus further contribute to their deleterious effects.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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