Cell Uptake and <i>in Vitro</i> Toxicity of Magnetic Nanoparticles Suitable for Drug Delivery
Bibliographic record
Abstract
Magnetic targeting is useful for intravascular or intracavitary drug delivery, including tumor chemotherapy or intraocular antiangiogenic therapy. For all such in vivo applications, the magnetic drug carrier must be biocompatible and nontoxic. In this work, we investigated the toxic properties of magnetic nanoparticles coated with polyethylenoxide (PEO) triblock copolymers. Such coatings prevent the aggregation of magnetic nanoparticles and guarantee consistent magnetic and nonmagnetic flow properties. It was found that the PEO tail block length inversely correlates with toxicity. The nanoparticles with the shortest 0.75 kDa PEO tails were the most toxic, while particles coated with the 15 kDa PEO tail block copolymers were the least toxic. Toxicity responses of the tested prostate cancer cell lines (PC3 and C4-2), human umbilical vein endothelial cells (HUVECs), and human retinal pigment epithelial cells (HRPEs) were similar. Furthermore, all cell types took up the coated magnetic nanoparticles. It is concluded that magnetite nanoparticles coated with triblock copolymers containing PEO tail lengths of above 2 kDa are biocompatible and appropriate for in vivo application.
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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".