<i>In Vivo</i> Cancer Cells Elimination Guided by Aptamer-Functionalized Gold-Coated Magnetic Nanoparticles and Controlled with Low Frequency Alternating Magnetic Field
Bibliographic record
Abstract
Biomedical applications of magnetic nanoparticles under the influence of a magnetic field have been proved useful beyond expectations in cancer therapy. Magnetic nanoparticles are effective heat mediators, drug nanocarriers, and contrast agents; various strategies have been suggested to selectively target tumor cancer cells. Our study presents magnetodynamic nanotherapy using DNA aptamer-functionalized 50 nm gold-coated magnetic nanoparticles exposed to a low frequency alternating magnetic field for selective elimination of tumor cells in vivo. The cell specific DNA aptamer AS-14 binds to the fibronectin protein in Ehrlich carcinoma hence helps deliver the gold-coated magnetic nanoparticles to the mouse tumor. Applying an alternating magnetic field of 50 Hz at the tumor site causes the nanoparticles to oscillate and pull the fibronectin proteins and integrins to the surface of the cell membrane. This results in apoptosis followed by necrosis of tumor cells without heating the tumor, adjacent healthy cells and tissues. The aptamer-guided nanoparticles and the low frequency alternating magnetic field demonstrates a unique non-invasive nanoscalpel technology for precise cancer surgery at the single cell level.
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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".