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Processing methods and storage duration impact extracellular vesicle counts in red blood cell units

2020· article· en· W3098767142 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.

Bibliographic record

VenueBlood Advances · 2020
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPlateletRed blood cellExtracellular vesicleExtracellular vesiclesWhole bloodFlow cytometryBlood cellAndrologyChemistryImmunologyMedicineBiologyBiochemistryMicrovesicles

Abstract

fetched live from OpenAlex

Extracellular vesicles (EVs) are active components of red blood cell (RBC) concentrates and may be associated with beneficial and adverse effects of transfusion. Elucidating controllable factors associated with EV release in RBC products is thus important to better manage the quality and properties of RBC units. Erythrocyte-derived EVs (EEVs) and platelet-derived EVs (PEVs) were counted in 1226 RBC units (administered to 280 patients) using a standardized cytometry-based method. EV size and CD47 and annexin V expression were also measured. The effects of donor characteristics, processing methods, and storage duration on EV counts were analyzed by using standard comparison tests, and analysis of covariance was used to determine factors independently associated with EV counts. PEV as well as EEV counts were higher in whole-blood-filtered RBC units compared with RBC-filtered units; PEV counts were associated with filter type (higher with filters associated with higher residual platelets), and CD47 expression was higher on EEVs in RBC units stored longer. Multivariate analysis showed that EEV counts were strongly associated with filter type (P < .0001), preparation, and storage time (+25.4 EEV/µL per day [P = .01] and +42.4 EEV/µL per day [P < .0001], respectively). The only independent factor associated with PEV counts was the residual platelet count in the unit (+67.1 PEV/µL; P < .0001). Overall, processing methods have an impact on EV counts and characteristics, leading to large variations in EV quantities transfused into patients. RBC unit processing methods might be standardized to control the EV content of RBC units if any impacts on patient outcomes can be confirmed. The IMIB (Impact of Microparticles in Blood) study is ancillary to the French ABLE (Age of Transfused Blood in Critically Ill Adults) trial (ISRCTN44878718).

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 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 score0.224
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.029
GPT teacher head0.325
Teacher spread0.296 · 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