Paper-Based Solid-Phase Nucleic Acid Hybridization Assay Using Immobilized Quantum Dots as Donors in Fluorescence Resonance Energy Transfer
Bibliographic record
Abstract
A paper-based solid-phase assay is presented for transduction of nucleic acid hybridization using immobilized quantum dots (QDs) as donors in fluorescence resonance energy transfer (FRET). The surface of paper was modified with imidazole groups to immobilize QD-probe oligonucleotide conjugates that were assembled in solution. Green-emitting QDs (gQDs) were FRET-paired with Cy3 acceptor. Hybridization of Cy3-labeled oligonucleotide targets provided the proximity required for FRET-sensitized emission from Cy3, which served as an analytical signal. The assay exhibited rapid transduction of nucleic acid hybridization within minutes. Without any amplification steps, the limit of detection of the assay was found to be 300 fmol with the upper limit of the dynamic range at 5 pmol. The implementation of glutathione-coated QDs for the development of nucleic acid hybridization assay integrated on a paper-based platform exhibited excellent resistance to nonspecific adsorption of oligonucleotides and showed no reduction in the performance of the assay in the presence of large quantities of noncomplementary DNA. The selectivity of nucleic acid hybridization was demonstrated by single-nucleotide polymorphism (SNP) detection at a contrast ratio of 19 to 1. The reuse of paper over multiple cycles of hybridization and dehybridization was possible, with less than 20% reduction in the performance of the assay in five cycles. This work provides an important framework for the development of paper-based solid-phase QD-FRET nucleic acid hybridization assays that make use of a ratiometric approach for detection and analysis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".