Scalable Purification, Storage, and Release of Plant-Derived Nanovesicles for Local Therapy Using Nanostructured All-Cellulose Composite Membranes
Bibliographic record
Abstract
Plant-derived nanovesicles such as bilberries nanovesicles (BNVs) show immense promise as next-generation biotherapeutics and functional food ingredients; however, their isolation, purification, and storage on a large scale remain a challenge. In this study, biocompatible and nanostructured composite all-cellulose membranes are introduced as a scalable and straightforward approach to the isolation of BNV. The membranes consisting of a cellulose acetate matrix infused with anionic or cationic nanocelluloses promoted selective capture of BNVs through electrostatic and size-exclusion-mediated depth filtration. Furthermore, the surface of the composite membrane acted as a storage matrix for BNVs, ensuring their prolonged stability at 4 °C. The BNVs stored in the membrane could be promptly released through elution assisted by low-pressure vacuum filtration or diffusion in liquid media. The morphology, bioactivity, and stability of the extracted BNVs were preserved, and the release rate of BNVs in different cell cultures could be regulated, facilitating their use for local therapy. Consequently, this approach paves the way for the scalable production, purification, and storage of nanovesicles and advances their use in biotherapeutics and functional foods.
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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) | 0.000 | 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".