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Record W4417361587 · doi:10.1002/jev2.70189

Calibration of Flow Cytometers Enables Reproducible Measurements of Extracellular Vesicle Concentrations and Reference Range Establishment

2025· article· en· W4417361587 on OpenAlex
Britta Bettin, Bo Li, Kim Falkena, Ton G. van Leeuwen, Christian Gollwitzer, Zoltán Varga, Nadine Ajzenberg, Jovan P. Antović, Pascale Berckmans, Edit I. Buzás, Randy P. Carney, Sean Cook, Françoise Dignat‐George, Dorothée Faille, Bernd Giebel, Jennifer Jones, Yohan Kim, Romaric Lacroix, Joanne Lannigan, Fabrice Lucien, Katariina Maaninka, Erika G. Marques de Menezes, Annette Meyer, Rachel R. Mizenko, Inge Nelissen, John P. Nolan, Philip J. Norris, Desmond Pink, Sumeet Poudel, Stéphane Robert, Pia Siljander, Vera A. Tang, Tobias Tertel, Tina Van Den Broeck, Lili Wang, Joshua A Welsh, Rienk Nieuwland, Edwin van der Pol

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.

Bibliographic record

VenueJournal of Extracellular Vesicles · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsAlberta Oil Sands Technology and Research Authority
FundersEuropean Metrology Programme for Innovation and ResearchNational Cancer InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekEuropean Commission
KeywordsCalibrationExtracellular vesiclesReference valuesRange (aeronautics)Extracellular vesicleCalibration curveBiomarkerBlood flow

Abstract

fetched live from OpenAlex

The concentration of cells is a key component of modern blood tests. Given the biomarker potential of extracellular vesicles (EVs) in blood, we aimed to establish reference ranges for blood cell-derived EVs using flow cytometry. To address the orders-of-magnitude variability in reported EV concentrations between different flow cytometers (FCMs), we first validated a calibration methodology to enable reproducible EV concentration measurements. The methodology was evaluated in an interlaboratory comparison study and shows that calibration reduces the median absolute deviation of EV concentrations measured on 25 different FCMs from 67 % to 25 %-31 %. The calibration methodology was then used to determine reference ranges of erythrocyte-, leukocyte-, and platelet-derived EVs in human blood plasma in a cohort of healthy individuals (n = 224). This study demonstrates that calibration enables comparable concentration measurements of blood cell-derived EVs, thereby bringing EVs one step closer to clinical applications.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.270
Teacher spread0.243 · 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