One-step synthesis of magnetic hollow silica and their application for nanomedicine
Bibliographic record
Abstract
Magnetic nanoparticles are usually present in the form of magnetic carriers and used in nanomedicine and biosystem. In this paper, magnetic hollow silica (MHS) nanoparticles were fabricated by a one-step synthesis of Fe3O4 nanoparticles and then coating of silica on nanosized spherical calcium carbonate under alkaline conditions, in which nanosized calcium carbonate (CaCO3, 25–60nm) was used as a scarified template, tetraethoxysilane as a precursor, and Fe3O4 nanoparticles (∼5nm), formed in the initial reaction stage, as magnetic agents. The as-synthesized nanoparticles were immersed in a weak acetic acidic solution to remove CaCO3, forming MHS carriers. The nanostructures of the MHS carriers were characterized by scanning electron microscope, transmission electron microscope, and x-ray diffraction. Superconducting quantum interference device measurement exhibited that the MHS nanoparticles were superparamagnetic. Toxicity was tested for MHS carriers using rat brain microvascular endothelial cells. The cells treated with concentration lower than 50μg∕ml of the MHS nanoparticles showed no significant toxicity. After modification by silane coupling agent, the MHS carriers have strong absorption for ibuprofen in nanomedicine field.
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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".