Continuously manufactured magnetic polymersomes – a versatile tool (not only) for targeted cancer therapy
Bibliographic record
Abstract
Micromixer technology was used to prepare polymeric vesicles (Pluronic® L-121) dual loaded with the anti-cancer drug camptothecin and magnetic nanoparticles. Successful incorporation of the magnetic nanoparticles was confirmed by transmission electron microscopy. Dynamic light scattering measurements showed a relatively narrow size distribution of the hybrid polymersomes. Camptothecin polymersomes reduced the cell viability of prostate cancer cells (PC-3) measured after 72 h significantly, while drug-free polymersomes showed no cytotoxic effects. Covalent attachment of a cancer targeting peptide (bombesin) as well as a fluorescent label (Alexa Fluor® 647) to the hybrid polymersomes was performed and specific cell binding and internalization were shown by flow cytometry and confocal microscopy. Relaxometry measurements clearly demonstrated the capacity of magnetic polymersomes to generate significant T2-weighted MRI contrast and potentially allow for direct monitoring of the biodistribution of the polymersomes. Micromixer technology as an easy, fast and efficient way to manufacture hybrid polymersomes as theranostic drug delivery devices is a further step from basic research to personalized medicine.
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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 | 0.001 |
| 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".