Isolation and Analysis of Traceable and Functionalized Extracellular Vesicles from the Plasma and Solid Tissues
Bibliographic record
Abstract
Circulating and tissue-resident extracellular vesicles (EVs) represent promising targets as novel theranostic biomarkers, and they emerge as important players in the maintenance of organismal homeostasis and the progression of a wide spectrum of diseases. While the current research focuses on the characterization of endogenous exosomes with the endosomal origin, microvesicles blebbing from the plasma membrane have gained increasing attention in health and sickness, which are featured by an abundance of surface molecules recapitulating the membrane signature of parent cells. Here, a reproducible procedure is presented based on differential centrifugation for extracting and characterizing EVs from the plasma and solid tissues, such as the bone. The protocol further describes subsequent profiling of surface antigens and protein cargos of EVs, which are thus traceable for their derivations and identified with components related to potential function. This method will be useful for correlative, functional, and mechanistic analysis of EVs in biological, physiological, and pathological studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".