Assembly of near infra-red emitting upconverting nanoparticles and multiple Gd(<scp>iii</scp>)-chelates as a potential bimodal contrast agent for MRI and optical imaging
Bibliographic record
Abstract
Linking multiple paramagnetic gadolinium(III)-chelates based on the 2-[4,7,10-tris(carboxymethyl)-1,4,7,10-tetraazacyclododec-1-yl]acetate (DOTA) ligand to the surface of NaGdF4:Yb(3+),Tm(3+) upconverting nanoparticles with an average particle size of 20 nm resulted in an assembly that has favorable properties for bimodal Magnetic Resonance Imaging (MRI) and Optical Imaging (OI). An improved synthetic pathway was used to couple the paramagnetic precursor to the nanoparticles. The nanoparticles were rendered water dispersible via citrate capping, leaving one acid group free for amide coupling with the mono-amino precursor of the DOTA ligand. Luminescence spectroscopy measurements have shown that the excitation of the nanoconstruct at 980 nm resulted in intense upconverted emission of thulium(III) at 800 nm. The assembly of several paramagnetic centers on the nanoparticle scaffold reduces the overall tumbling rate, resulting in enhanced longitudinal relaxation times and improved relaxivity. The proton NMRD profiles show a characteristic hump at higher frequencies, which is caused by the slow rotation of the nanoconstruct, resulting in r1 values of 25 mM(-1) s(-1) per gadolinium(III)-ion at 60 MHz and 310 K. This is a significant improvement compared to the Gd-DO3A-ethylamine precursor (4) for which a value of r1 of 3.23 mM(-1) s(-1) was observed under the same conditions. Theoretical fitting by two different approaches showed an increase of τR from 57.3 ps for the Gd-DO3A-ethylamine precursor (4) to 392.0 ps for the nanoconstruct, which is responsible for the overall substantial increase in relaxivity.
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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".