Eu/Tb codoped spindle-shaped fluorinated hydroxyapatite nanoparticles for dual-color cell imaging
Bibliographic record
Abstract
Lanthanide doped fluorinated hydroxyapatite (FAp) nanoparticles are promising cell imaging nanomaterials but they are excited at wavelengths which do not match the light sources usually found in a commercial confocal laser scanning microscope (CLSM). In this work, we have successfully prepared spindle-shaped Eu/Tb codoped FAp nanoparticles by a hydrothermal method. Compared with single Eu doped FAp, Eu/Tb codoped FAp can be excited by a 488 nm laser, and exhibit both green and red light emission. By changing the amounts of Eu and Tb peaks, the emission in the green region (500-580 nm) can be decreased to the benefit of the emission in the red region (580-720 nm), thus reaching a balanced dual color emission. Using MC3T3-E1 cells co-cultured with Eu/Tb codoped FAp nanoparticles, it is observed that the nanoparticles are cytocompatible even at a concentration as high as 800 μg ml(-1). The Eu/Tb codoped FAp nanoparticles are located in the cytoplasm and can be monitored by dual color-green and red imaging with a single excitation light at 488 nm. At a concentration of 200 μg ml(-1), the cytoplasm is saturated in 8 hours, and Eu/Tb codoped FAp nanoparticles retain their fluorescence for at least 3 days. The cytocompatible Eu/Tb codoped FAp nanoparticles with unique dual color emission will be of great use for cell and tissue imaging.
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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 | 0.001 | 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 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".