Magnetic gold nanoparticles as a vehicle for fluorescein isothiocyanate and DNA delivery into plant cells
Bibliographic record
Abstract
Magnetic gold nanoparticles (mGNPs) with uniform size and morphology synthesized by our sonication treatment method were covalently bound with fluorescein isothiocyanate (FITC) molecules. Driven by an external magnetic field, FITC-labelled nanoparticles were delivered into plant cells with and without cell walls, evident from sectional transmission electron microscopy images. Confocal images further indicate that the green fluorescence in canola protoplasts and walled cells indeed came from the FITC molecules, instead of the chloroplasts’ autofluorescence. FITC-labelled nanoparticles had a delivery efficiency of 95% based on confocal images. In further study, plasmids were covalently bound with mGNPs, and delivered into canola cells with and without cell walls. After culturing for 48 h followed by staining with 5-bromo-4-chloro-3-indolyl-β-d-glucuronic acid (X-Gluc), blue colour appeared in the protoplasts, while the walled canola cells showed a green colour that can be interpreted as the combination of blue and yellow from the suspension cells themselves. The presence of the blue colour indicates the expression of the GUS gene; therefore, the plasmids were successfully delivered into the canola cells. Furthermore, on examination, mGNPs were considered to be noncytotoxic by fluorescein diacetate staining.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".