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Record W2596974594 · doi:10.1002/cpps.23

Characterization of Protein Content Present in Exosomes Isolated from Conditioned Media and Urine

2017· article· en· W2596974594 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

VenueCurrent Protocols in Protein Science · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMicrovesiclesUrineCharacterization (materials science)ChemistryChromatographyBiochemistryNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

Cells secrete biomolecules into the extracellular space as a way of intercellular communication. Secreted proteins can act as ligands that engage specific receptors-on the same cell, nearby cells, or distant cells-and induce defined signaling pathways. Proteins and other biomolecules can also be packaged as cargo molecules within vesicles that are released to the extracellular space (termed extracellular vesicles or EVs). A subclass of such EVs, exosomes have been shown to horizontally transfer information. In recent years, exosomes have sparked tremendous interest in biological research, both for the discovery of novel biomarkers and for the identification of signaling molecules, as part of their cargo. Although multiple methods have been described for the isolation of exosomes, described here is a simple differential centrifugation approach that is well suited for the isolation of exosomes from conditioned cell culture media and urine. Mass spectrometry provides an ideal method to comprehensively analyze the protein cargo of exosomes. © 2017 by John Wiley & Sons, Inc.

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)0.001
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 score0.135
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.049
GPT teacher head0.335
Teacher spread0.286 · 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