Extracellular Vesicles as Natural Nanosized Delivery Systems for Small-Molecule Drugs and Genetic Material: Steps towards the Future Nanomedicines
Bibliographic record
Abstract
A new platform for drug, gene and peptide-protein delivery is emerging, under the common name of "extracellular vesicles". Extracellular vesicles (EVs) are 30-1000 nm-sized cell-derived, liposome-like vesicles. Current research on EVs as nano-delivery systems for small-molecule drugs and genetic material, reveal that these tiny, biologically-derived vesicles carry a great potential to boost the efficacy of many therapeutic protocols. Several features of EVs; from efficacy to safety, from passive to active targeting ability, the opportunity to be biologically or chemically labelled, and most importantly, their eobiotic origin make them promising candidate for development of the next generation personalized nanomedicines. The aim of this article is to provide a view on the current research in which EVs are used as drug/genetic material delivery systems. Their application areas, drug loading and targeting strategies, and biodistribution properties are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".