Protein corona formation and its influence on biomimetic magnetite nanoparticles
Bibliographic record
Abstract
Biomimetic magnetite nanoparticles (BMNPs) synthesized in the presence of MamC, a magnetosome-associated protein from Magnetoccus marinus MC-1, have gained interest for biomedical applications because of their unique magnetic properties. However, their behavior in biological systems, like their interaction with proteins, still has to be evaluated prior to their use in clinics. In this study, doxorubicin (DOXO) as a model drug was adsorbed onto BMNPs to form nanoassemblies. These were incubated with human plasma to trigger protein corona (PC) formation. Proteins from the human plasma stably attached to either BMNPs or DOXO-BMNP nanoassemblies. In particular, fibrinogen was detected as the main component in the PC of DOXO-BMNPs that potentially provides advantages, e.g. protecting the particles from phagocytosis, thus prolonging their circulation time. Adsorption of PC to the BMNPs did not alter their magnetic properties but improved their colloidal stability, thus reducing their toxicity in human macrophages. In addition, PC formation enhanced cellular internalization and did not interfere with DOXO activity. Overall, our data indicate that the adsorption of PC onto DOXO-BMNPs in biological environment even increases their efficiency as drug carrier systems.
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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) | 0.000 | 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 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".