Biocompatible Carbon-Coated Ferrite Nanodot-Based Magnetoliposomes for Magnetic-Induced Multimodal Theragnostic
Bibliographic record
Abstract
Magnetoliposomes are hybrid nanostructures that integrate superparamagnetic ultrasmall carbon-coated ferrite nanodots (MNCDs) within liposomes (Lipo) composed of egg yolk-derived phospholipids and stabilized with an environmentally benign potato peel extract (PPE), enabling enhanced magnetic resonance imaging (MRI) and optical imaging. The hydrothermally synthesized MNCDs were entrapped in liposomes prepared by thin-film hydration, and physicochemical properties were established at each stage of engineering. These magnetoresponsive vesicles (MNCDs+Lipo@PPE) serve as a triple-mode medical imaging contrast for T1 & T2-weighted MRI, while simultaneously enabling optical tracking of liposome degradation under an external magnetic field. They exhibited long-term enhanced fluorescence intensity and colloidal stability over 30 days, with hydrodynamic diameters ranging from 190 to 331 nm and an improved surface charge following PPE coating. In vitro cytotoxicity assays (MTT and Live/Dead staining) demonstrated over 87% cell viability for MNCDs+Lipo@PPE up to 2.7 mM concentration in A549 cells, indicating considerable toxicity. This multimodality engineering facilitates precise image-guided anticancer doxorubicin delivery and magnetic-responsive controlled release. The theoretical model shows that the release profile follows the Korsmeyer-Peppas profile. The externally applied magnetic field enhances the release by 1.4-fold. To demonstrate the anticancer efficiency in vitro with minimum off-target cytotoxicity, MTT and live/dead cell assay were performed against A549 cells. The reported study is a validated demonstration of magnetic-responsive nanocarrier systems for anticancer therapy and multimodal MRI and optical imaging-based diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".