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Record W2912505459 · doi:10.1002/pros.23764

Nanoscale flow cytometry to distinguish subpopulations of prostate extracellular vesicles in patient plasma

2019· article· en· W2912505459 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Prostate · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsLawson Health Research InstituteWestern University
FundersProstate Cancer Canada
KeywordsMicrovesiclesProstate cancerCD63ExosomeFlow cytometryProstateMicrovesiclePCA3MedicineExtracellular vesicleCancer researchPathologyCancerChemistryInternal medicineImmunologymicroRNA

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine if prostate-derived extracellular vesicles (EVs) present in patient plasma samples are of exocytotic origin (exosomes) or released by the cell membrane (microparticles/microvesicles). Both malignant and normal prostate cells release two types of EVs into the circulation, exosomes, and microparticles/microvesicles which differ in size, origin, and mode of release. Determining what proportion of prostate-derived EVs are of exosomal versus microparticle/microvesicle EV subtype is of potential diagnostic significance. MATERIALS AND METHODS: Multi-parametric analytical platforms such as nanoscale flow cytometry (nFC) were used to analyze prostate derived extracellular vesicles. Plasmas from prostate cancer (PCa) patient plasmas representing benign prostatic hyperplasia (BPH), low grade prostate cancer (Gleason Score 3 + 3) and high grade prostate cancer (Gleason Score ≥4 + 4) were analyzed for various exosome markers (CD9, CD63, CD81) and a prostate specific tissue marker (prostate specific membrane antigen/PSMA). RESULTS: By using nanoscale flow cytometry, we determine that prostate derived EVs are primarily of cell membrane origin, microparticles/microvesicles, and not all PSMA expressing EVs co-express exosomal markers such as CD9, CD63, and CD81. CD9 was the most abundant exosomal marker on prostate derived EVs (12-19%). There was no trend observed in terms of more PSMA + CD9 or PSMA + CD63 co-expressing EVs versus increasing grade of prostate cancer. CONCLUSION: The majority of prostate derived EVs present in plasmas are from the cell membrane as evidenced by their size and most importantly, lack of co-expression of exosomal markers such as CD9/CD63/CD81. In fact, CD81 was not present on any prostate derived EVs in patient plasmas whereas CD9 was present on a minority of prostate derived EVs. The addition of an exosomal marker for detection of prostate-derived EVs does not provide greater clarity in distinguishing EVs released by the prostate.

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 score0.024
Threshold uncertainty score0.591

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 head0.006
GPT teacher head0.231
Teacher spread0.224 · 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