Development of biocompatible NaGdF<sub>4</sub>: Er<sup>3+</sup>, Yb<sup>3+</sup> upconversion nanoparticles used as contrast agents for bio‐imaging
Bibliographic record
Abstract
Upconversion nanoparticles with special fluorescence and magnetic properties have been considered an alternative contrast agent for multiple bio ‐ imaging techniques. It is important to understand the effects of the surface properties and dosage of upconversion nanoparticles on both the magnetic resonance (MRI) image and the photoluminescence spectrum. Here, NaGdF 4 : Er 3+ , Yb 3+ upconversion nanoparticles (UCNPs) modified with amine functional group were produced through a one‐pot thermal decomposition. The average length of the cubic UCNPs is estimated at 53 ±13 nm. The effect of the dosage of amine modified UCNPs on the MRI image is investigated. The T 1 and T 2 relaxivities of the amine modified UCNPs in agarose gel at 3 T are r 1 = 6.79 ±0.14 and r 2 = 17.0 ±0.18 (mmol/L) −1 s −1 , which are comparable to the relaxivities of commercially available MRI contrast agents. In addition, the photoluminescence of the amine modified UCNPs at low concentrations < 150 µg/mL are further investigated with the excitation wavelength (λ ex ) at 980 nm. The internalization of the amine modified UCNPs cultured with human umbilical vascular endothelial cells (HUVEC) is observed by the fluorescence imaging. Meanwhile, T 1 ‐weighted MRI imaging of HUVEC cells treated with amine modified UCNPs at 10 µg/mL can be obtained. No significant toxic effect on cells is found when the concentration of the amine modified UCNPs is < 300 µg/mL. This study indicates that a low concentration of amine‐modified NaGdF 4 : Er 3+ , Yb 3+ UCNPs can be used as the contrast agent for both fluorescence imaging and magnetic resonance imaging.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".