A long-wavelength quantum dot-concentric FRET configuration: characterization and application in a multiplexed hybridization assay
Bibliographic record
Abstract
Quantum dot-based concentric Förster resonance energy transfer (cFRET) is a promising modality for the development of multifunctional fluorescent probes for bioanalysis and bioimaging. To date, the scope of cFRET has been largely limited to a prototypical configuration with a particular combination of quantum dot (QD) and fluorescent dyes linked through peptides. Expansion of the scope of cFRET is critical for its further development. Here, we expand the scope of cFRET in two capacities. First, we design and characterize a new long-wavelength cFRET configuration that combines red- and deep-red fluorescent dyes, Alexa Fluor 633 and Alexa Fluor 680, with an orange-emitting QD. Sequential and competitive energy transfer pathways are characterized through a rate analysis, where the balance of these rates more strongly favours competitive energy transfer in the new long-wavelength configuration versus sequential energy transfer in the previous prototypical configuration. Although the new cFRET configuration is more susceptible to photobleaching, its superior brightness and longer-wavelength excitation and emission provide an order of magnitude higher signal-to-background ratios in biological matrices (e.g., serum, blood) than the previous prototypical configuration. Second, we demonstrate that an oligonucleotide-linked, long-wavelength cFRET configuration has energy transfer similar to an analogous peptide-linked configuration, where the oligonucleotide-linked cFRET configuration can be combined with toehold-mediated strand displacement for the multiplexed detection of unlabeled nucleic acid targets as a single vector. Overall, this work establishes the general applicability of cFRET and introduces new strategies for its bioanalytical application.
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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".