Naturally Occurring Exosome Vesicles as Potential Delivery Vehicle for Bioactive Compounds
Bibliographic record
Abstract
Various kinds of vesicles have been produced from plant, animal and inorganic materials for use as delivery vehicles especially in functional food formulation. However, major drawbacks associated with most of them include issues with sustainability, safety, biocompatibility, biorecognition, stability, bioavailability, bioadhesion, generation of reactive species, inefficient encapsulation and protection, and inability to release the bioactive compounds at target regions of the gastrointestinal tract. The use of vesicles innately formed in plant and animal cells as delivery agents would potentially solve most problems associated with the existing nanodelivery systems. Underutilized vesicles, known as exosomes, exist in plant and animal cells, where they play roles in cell communication and nutrient delivery. To date, exosomes have proven to be stable, biocompatible and able to withstand the activity of digestive enzymes until they reach their target locations. However, there is a need to explore better ways of inducing exosome production, to elucidate their physiological roles, and understand their biogenesis in plants, to discover sustainable methods of isolation of high yields of the vesicles. There is also a need to clarify the digestibility and interaction of the exosomes with blood and gastrointestinal fluids. This review highlights the isolation techniques and delivery potential of exosomes, and equally presents research gaps for enhancing the use of the natural vesicles for delivery purposes.
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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 | 0.001 | 0.001 |
| 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".