Extracellular vesicles isolated from adipose tissue-derived mesenchymal stromal cells as carriers for Paclitaxel delivery
Bibliographic record
Abstract
BACKGROUND: Mesenchymal Stromal Cells (MSC)-derived Extracellular Vesicles (EV) represent innovative tools for drug delivery systems. However, their clinical use is limited by the lack of standardized good manufacturing practice (GMP)-compliant isolation and conservation protocols. In this study, we developed a GMP-compliant protocol for the preparation of MSC-EVs and investigated the feasibility of producing EVs loaded with paclitaxel (PTX) for clinical application as drug products. METHODS: Adipose tissues from 13 donors were used to obtain MSC-EVs via culture supernatant ultracentrifugation. EVs loaded with PTX were manufactured by adding the drug to the culture medium of MSCs before supernatant collection. EV identity was verified in terms of concentration/size, protein content, morphology, and expression of EV surface markers. The anti-proliferative activity, accumulation ability in tumor cells and PTX content, as well as their stability over time, were also evaluated. RESULTS: High numbers of EV/EV-PTX compliant in terms of integrity/identity were obtained and can be successfully stored for up to one year at -80 °C. Cellular studies have shown that EVs are capable of accumulating in tumor cells and, when loaded with PTX, inhibiting the proliferation of a pleural mesothelioma cell line. CONCLUSIONS: These results support the potential future clinical use of EVs as carriers for drug delivery to improve cancer treatment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".