Synthesis of surface enhanced Raman scattering active magnetic nanoparticles for cell labeling and sorting
Bibliographic record
Abstract
Here we report the synthesis of the magnetic nanocomposite nanoparticles with Fe3O4 core and silver shell for cell imaging and separation. When the magnetic nanoparticles are decorated with surface enhanced Raman scattering (SERS) active molecules, they can be used for cell separation with unique optical signature. In this experiment, commercially available superparamagnetic nanoparticles (fluidMAG) with 50 nm diameter were used as the core. The shell layer was produced by the reduction of the silver salts. As a result of the reduction, nanocomposite magnetic nanoparticles with 60 nm diameter were obtained. To create unique SERS patterns for multiplexing, the surfaces of the nanoparticles were further modified with chloro-, bromo-, or fluorobenzenethiol. When these nanoparticles were incubated with 3T3 cells, it was found that the nanoparticles were located around the nucleus in the cytoplasm.
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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".