Bioconjugation of Ln<sup>3+</sup>-Doped LaF<sub>3</sub> Nanoparticles to Avidin
Bibliographic record
Abstract
The binding of Eu3+-doped LaF3 nanoparticles with biotin moieties at the surface of the stabilizing ligand layer to avidin, immobilized on cross-linked aragose beads, is described. The biotin moieties were attached to the nanoparticles by reaction of an activated ester with the amino groups on the surface of the nanoparticles resulting from the 2-aminoethyl phosphate ligands that were coordinated to the surface through the phosphate end. This strategy of employing the reactions of amines with activated esters provides a general platform to modify the surface of the 2-aminophosphate stabilized Ln3+-doped LaF3 nanoparticles with biologically relevant groups. Significant suppression of nonspecific binding to the avidin modified aragose beads has been realized by the incorporation of poly(ethylene glycol) units via the same reaction of a primary amine with an activated ester. The particle size distribution of the functionalized nanoparticles was within 10-50 nm, with a quantum yield of 19% in H2O for the LaF3 nanoparticles codoped with Ce3+ and Tb3+. A discreet, 4 unit poly(ethylene glycol) spaced heterobifunctional cross-linker, functionalized with biotin and N-hydroxysuccinimide at opposite termini, was covalently linked to the 2-aminoethyl phosphate ligand via the N-hydroxysuccinimide activated ester, making an amide bond, imparting biological activity to the particle. Modification of the remaining unreacted amino groups of the stabilizing ligands was done with Me(OCH2CH2)3CH2CH2(C=O)-NHS (NHS = N-hydroxysuccinimide).
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".