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Record W4387270164 · doi:10.1161/atvb.43.suppl_1.336

Abstract 336: Endothelial Cells Communicate with Surrounding Vascular Cells Via Bidirectional and Polarized Secretion of Extracellular Vesicular Cargo: Implications for Atherosclerotic Plaque Development

2023· article· en· W4387270164 on OpenAlexaff
Sneha Raju, Kamalben Prajapati, Mark C. Blaser, Steven R. Botts, Tse Wing Winnie Ho, Crizza Ching, Natalie J. Galant, Lindsey K. Fiddes, Ruilin Wu, Cassandra L. Clift, Tan Pham, Sasha A. Singh, Warren L. Lee, Elena Aïkawa, Jason E. Fish, Kathryn L. Howe

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity Health NetworkUniversity of TorontoSt. Michael's HospitalToronto General Hospital
Fundersnot available
KeywordsCell biologyMicrovesiclesSecretionCellExtracellular vesicleExosomeWestern blotExtracellularChemistryVascular smooth muscleIntracellularmicroRNABiologyBiochemistrySmooth muscle

Abstract

fetched live from OpenAlex

Introduction: Endothelial cells (EC) can release extracellular vesicle (EV)-encapsulated miRNAs and proteins to mediate cell-cell communication. We hypothesized that EC-EV release is altered by activation state and drives functional changes in surrounding cells via bidirectional release. Methods: EVs were isolated from supernatants of human aortic endothelial cells (HAECs; ± IL-1β, 100pg/ml) via serial ultracentrifugation and quantified as per MISEV2018 guidelines. Cargo was assessed (miRNA sequencing, proteomics). HAEC EVs were added to primary monocytes and vascular smooth muscle cells (VSMCs) at a physiological concentration and RNA-seq was performed. Bioinformatic analysis of EV contents and RNA-seq was performed. To assess polarized EV secretion, EVs were quantified from apical and basolateral compartments, and visualized with total internal reflection fluorescence (TIRF) and cryogenic transmission electron microscopy (cryo-TEM). Results: Activated HAECs have increased EV release (6.73±1.81X10 10 vs. 2.98±1.44 x10 11 particles/ml; p=0.028, N=3). In comparison to quiescent ECs, activated EC-EVs carry miRNA and protein cargo that play shared and distinct roles in several pro-atherogenic pathways. EC-EVs participate in cell-cell communication with circulating monocytes and resident VSMCs, and EVs from activated ECs lead to changes in pathways that are pro-inflammatory and atherogenic. Importantly, ECs are capable of bidirectional communication with luminal and abluminal cells via their unique ability to release EVs to the apical and basolateral compartments as determined by EV-quantification using nanoparticle tracking and western blot analysis, EV-visualization via cryo-TEM, and dynamic basolateral HAEC-EV release via TIRF microscopy. Intriguingly, ECs polarize and secrete compartment-specific cargo to the luminal and abluminal surfaces with in silico analysis implicating unique communication with circulating and resident vascular cells. Conclusions: ECs utilize EV contents to mediate cell-cell communication in quiescent and activated states. Importantly, they can polarize vesicle release bidirectionally, which may specifically govern functional changes in circulating and resident vascular cells.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.032
GPT teacher head0.270
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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