A polymer–lipid membrane artificial cell nanocarrier containing enzyme–oxygen biotherapeutic inhibits the growth of B16F10 melanoma in 3D culture and in a mouse model
Bibliographic record
Abstract
Melanoma is a deadly skin cancer. Surgery is effective for early stages but there may be remnant cells. Treatments of later stages are associated with severe side effects. Moreover, a dangerous type of melanoma cannot be detected early enough for surgery. There is an urgent need for treatment with less severe side effects. We use a novel system of artificial cell polymer-lipid membrane nanocarrier containing a biomolecular nano-system of enzyme-oxygen biotherapeutic. In this report we show (1) its effectiveness and mechanisms in inhibiting the growth of melanoma in a 3D culture collagen medium that is more similar to that in the animal. (2) This allows us to design and carry out animal studies to successfully show that this can inhibit the growth of melanoma in an animal model. This includes following the tumour sizes and body weights every 2 days for 30 days followed by histology of the sites of injection and vital organs. We also analyze the action of the different components of the nanocarrier-nano-biotherapeutic complex. In conclusion, the results show the safety and clinical feasibility of this approach in the animal model and encourages further study towards clinical use.
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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) | 0.001 | 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".