MétaCan
Menu
Back to cohort
Record W2885609324 · doi:10.1242/jcs.215210

The interplay between exosomes and autophagy – partners in crime

2018· review· en· W2885609324 on OpenAlexafffund
Jing Xu, Robert Camfield, Sharon M. Gorski

Bibliographic record

VenueJournal of Cell Science · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAvon Foundation for Women
KeywordsAutophagyMicrovesiclesBiologyCell biologyBiogenesisExosomeEndomembrane systemEndosomeCrosstalkProteostasisContext (archaeology)AutophagosomeBAG3Exosome complexIntracellularmicroRNAGolgi apparatusRNAGeneticsEndoplasmic reticulumGeneRNase P

Abstract

fetched live from OpenAlex

The eukaryotic endomembrane system is a complex series of interconnected membranous organelles that play important roles in responding to stress and maintaining cell homeostasis during health and disease. Two components of this system, exosome biogenesis and autophagy, are linked by the endolysosomal pathway. Exosomes are cargo-laden extracellular vesicles that arise from endosome-derived multivesicular bodies, and autophagy is a lysosomal-dependent degradation and recycling pathway. Recent studies have revealed shared molecular machinery between exosome biogenesis and autophagy, as well as substantial crosstalk between these two processes. In this Review, we first describe the classic view of exosome biogenesis and autophagy, including their links to the endolysosomal pathway. We then present the evidence for autophagy-related proteins in exosome biogenesis, the emerging roles of amphisomes and the evolving models of exosome-autophagy pathway interactions. Finally, we discuss the implications of exosome and autophagy interplay in the context of neurodegeneration and cancer.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.024
GPT teacher head0.382
Teacher spread0.358 · 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 designNot applicable
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

Citations303
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Cell ScienceSame topicExtracellular vesicles in diseaseFrench-language works237,207