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Record W2999603405 · doi:10.3390/ijms21020578

Pexophagy: A Model for Selective Autophagy

2020· review· en· W2999603405 on OpenAlexaff
Kyla Germain, Peter K. Kim

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAutophagyPeroxisomeOrganelleCell biologyCytosolBiologyVacuoleIntracellularBiochemistryEnzymeGeneCytoplasm

Abstract

fetched live from OpenAlex

The removal of damaged or superfluous organelles from the cytosol by selective autophagy is required to maintain organelle function, quality control and overall cellular homeostasis. Precisely how substrate selectivity is achieved, and how individual substrates are degraded during selective autophagy in response to both extracellular and intracellular cues is not well understood. The aim of this review is to highlight pexophagy, the autophagic degradation of peroxisomes, as a model for selective autophagy. Peroxisomes are dynamic organelles whose abundance is rapidly modulated in response to metabolic demands. Peroxisomes are routinely turned over by pexophagy for organelle quality control yet can also be degraded by pexophagy in response to external stimuli such as amino acid starvation or hypoxia. This review discusses the molecular machinery and regulatory mechanisms governing substrate selectivity during both quality-control pexophagy and pexophagy in response to external stimuli, in yeast and mammalian systems. We draw lessons from pexophagy to infer how the cell may coordinate the degradation of individual substrates by selective autophagy across different cellular cues.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.062
GPT teacher head0.417
Teacher spread0.355 · 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 designOther design
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

Citations132
Published2020
Admission routes1
Has abstractyes

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