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The morphology of erythrocytes reveals differences in the mechanisms of erythrocyte derived extracellular vesicle formation

2025· article· ru· W4416308942 on OpenAlexaff
E. Yu. Parshina, Liubov Frolova, G. V. Маximov

Bibliographic record

VenueVestnik Moskovskogo universiteta Seria 16 Biologia · 2025
Typearticle
Languageru
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersRussian Science Foundation
KeywordsMorphology (biology)ExtracellularVesicleExtracellular vesiclesIn vitroEchinocyteIncubation

Abstract

fetched live from OpenAlex

Erythrocyte-derived extracellular vesicles (EDEVs) are a promising tool for “targeted drug delivery,” and this study aimed to compare several methods of obtaining EDEVs from erythrocytes in vitro . Scanning electron microscopy revealed that under certain treatments (calcium ionophore A23187, SDS, LPA, and incubation at 50°C), erythrocytes shed EDEVs. The differences in the morphology of erythrocytes subjected to EDEVs-stimulating treatments suggest distinct mechanisms of EDEVs formation. Raman spectroscopy showed that EDEVs obtained by heat treatment may contain hemoglobin, while SDS-induced treatment produces hemoglobin-free vesicles. The data obtained will allow for a targeted selection of EDEVs production methods based on their required composition.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.238
Teacher spread0.218 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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