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Record W3209500345 · doi:10.3389/fnmol.2021.767219

Mitochondrial Extracellular Vesicles – Origins and Roles

2021· review· en· W3209500345 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaFondation de l’UQTRUniversité du Québec à Trois-Rivières
KeywordsMitochondrionCell biologyExtracellularEndosomeBiologyExtracellular vesiclesReactive oxygen speciesInflammationMicrovesiclesCellNucleic acidBiochemistryIntracellularmicroRNAImmunologyGene

Abstract

fetched live from OpenAlex

Extracellular vesicles (EVs) have emerged in the last decade as critical cell-to-cell communication devices used to carry nucleic acids and proteins between cells. EV cargo includes plasma membrane and endosomal proteins, but EVs also contain material from other cellular compartments, including mitochondria. Within cells, mitochondria are responsible for a large range of metabolic reactions, but they can also produce damaging levels of reactive oxygen species and induce inflammation when damaged. Consistent with this, recent evidence suggests that EV-mediated transfer of mitochondrial content alters metabolic and inflammatory responses of recipient cells. As EV mitochondrial content is also altered in some pathologies, this could have important implications for their diagnosis and treatment. In this review, we will discuss the nature and roles of mitochondrial EVs, with a special emphasis on the nervous system.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.014
GPT teacher head0.280
Teacher spread0.265 · 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