Superparamagnetic Artificial Cells PLGA-Fe3O4 Micro/Nanocapsules for Cancer Targeted Delivery
Bibliographic record
Abstract
Artificial cells have been extensively used in many fields, such as nanomedicine, biotherapy, blood substitutes, drug delivery, enzyme/gene therapy, cancer therapy, and the COVID-19 vaccine. The unique properties of superparamagnetic Fe3O4 nanoparticles have contributed to increased interest in using superparamagnetic artificial cells (PLGA-Fe3O4 micro/nanocapsules) for targeted therapy. In this review, the preparation methods of Fe3O4 NPs and superparamagnetic artificial cell PLGA-drug-Fe3O4 micro/nanocapsules are discussed. This review also focuses on the recent progress of superparamagnetic PLGA-drug-Fe3O4 micro/nanocapsules as targeted therapeutics. We shall concentrate on the use of superparamagnetic artificial cells in the form of PLGA-drug-Fe3O4 nanocapsules for magnetic hyperthermia/photothermal therapy and cancer therapies, including lung breast cancer and glioblastoma.
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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".