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Record W2620594759 · doi:10.1160/th16-12-0943

Microvesicles in vascular homeostasis and diseases

2017· review· en· W2620594759 on OpenAlexafffund
Victoria Ridger, Chantal M. Boulanger, Anne Angelillo‐Scherrer, Lina Badimón, Olivier Blanc‐Brude, Marie‐Luce Bochaton‐Piallat, Éric Boilard, Edit I. Buzás, Andreas Caporali, Françoise Dignat‐George, Paul C. Evans, Romaric Lacroix, Esther Lutgens, Daniel F.J. Ketelhuth, Rienk Nieuwland, Florence Toti, José Tuñón, Christian Weber, Imo E. Hoefer, Gregory Y.H. Lip, Nikos Werner, Eduard Shantsila, Hugo Ten Cate, Mark Thomas, Paul Harrison

Bibliographic record

VenueThrombosis and Haemostasis · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health ResearchUniversité Sorbonne Paris CitéFondation de FranceInstitut National de la Santé et de la Recherche MédicaleKarolinska InstitutetHjärt-LungfondenHungarian Scientific Research FundCHIST-ERANederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftMedInProt Protein Science Research Synergy ProgramBritish Heart Foundation
KeywordsMicrovesiclesHemostasisMicrovesicleCell biologyExtracellular vesiclesHomeostasisBiologyIntracellularImmunologyMedicinemicroRNABiochemistryInternal medicine

Abstract

fetched live from OpenAlex

Microvesicles are members of the family of extracellular vesicles shed from the plasma membrane of activated or apoptotic cells. Microvesicles were initially characterised by their pro-coagulant activity and described as "microparticles". There is mounting evidence revealing a role for microvesicles in intercellular communication, with particular relevance to hemostasis and vascular biology. Coupled with this, the potential of microvesicles as meaningful biomarkers is under intense investigation. This Position Paper will summarise the current knowledge on the mechanisms of formation and composition of microvesicles of endothelial, platelet, red blood cell and leukocyte origin. This paper will also review and discuss the different methods used for their analysis and quantification, will underline the potential biological roles of these vesicles with respect to vascular homeostasis and thrombosis and define important themes for future research.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.096
GPT teacher head0.379
Teacher spread0.283 · 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

Citations230
Published2017
Admission routes2
Has abstractyes

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