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Record W4390491728 · doi:10.1016/j.cmet.2023.11.014

Mitochondrial-derived vesicles in metabolism, disease, and aging

2024· article· en· W4390491728 on OpenAlexafffund
Tim König, Heidi M. McBride

Bibliographic record

VenueCell Metabolism · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanada Research ChairsCanadian Institutes of Health ResearchAligning Science Across Parkinson’sAlexander von Humboldt-Stiftung
KeywordsBiogenesisBiologyMitochondrionCell biologyOrganelleRetrograde signalingSignal transductionMitochondrial biogenesismitochondrial fusionNeurodegenerationMitochondrial DNAGeneticsDiseaseGene

Abstract

fetched live from OpenAlex

Mitochondria are central hubs of cellular metabolism and are tightly connected to signaling pathways. The dynamic plasticity of mitochondria to fuse, divide, and contact other organelles to flux metabolites is central to their function. To ensure bona fide functionality and signaling interconnectivity, diverse molecular mechanisms evolved. An ancient and long-overlooked mechanism is the generation of mitochondrial-derived vesicles (MDVs) that shuttle selected mitochondrial cargoes to target organelles. Just recently, we gained significant insight into the mechanisms and functions of MDV transport, ranging from their role in mitochondrial quality control to immune signaling, thus demonstrating unexpected and diverse physiological aspects of MDV transport. This review highlights the origin of MDVs, their biogenesis, and their cargo selection, with a specific focus on the contribution of MDV transport to signaling across cell and organ barriers. Additionally, the implications of MDVs in peroxisome biogenesis, neurodegeneration, metabolism, aging, and cancer are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.235
Teacher spread0.226 · 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

Citations157
Published2024
Admission routes2
Has abstractyes

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