Solid-Phase Covalent Immobilization of Upconverting Nanoparticles for Biosensing by Luminescence Resonance Energy Transfer
Bibliographic record
Abstract
Monodisperse water-soluble upconverting nanoparticles (UCNPs) were immobilized onto modified glass substrates for development of biosensing surfaces that operated using luminescence resonance energy transfer (LRET). Amine modified UCNPs were prepared from oleic acid capped UCNPs by ligand exchange using o-phosphorylethanolamine (PEA). PEA-UCNPs were covalently immobilized on aldehyde functionalized coverslips. Environmental scanning electron microscopy (ESEM) images indicated a homogeneous distribution of UCNPs on surfaces with a high immobilization density of approximately 1.3 × 10(11) UCNP cm(-2). This is the first account of covalent immobilization of UCNPs for bioassay and biosensor development where the density is on par with the high immobilization densities reported for other types of nanoparticles. The functionality and stability of the immobilized NPs were demonstrated by examining an LRET-based bioassay. The well-known sandwich assay for the detection of thrombin was selected as a model in which UCNPs were used as donors and quantum dots (QDs) as acceptors. The closely packed UCNPs on the glass surface showed a 2.5-fold enhancement in assay sensitivity compared to less-densely packed surfaces. In addition, a 1.5-fold enhancement in energy transfer efficiency was shown for solid-phase compared to solution-phase LRET.
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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".