Adapting Fluorescence Resonance Energy Transfer with Quantum Dot Donors for Solid-Phase Hybridization Assays in Microtiter Plate Format
Bibliographic record
Abstract
Methods have been developed for the solid-phase detection of nucleic acids using mixed films of quantum dots (QDs) and oligonucleotide probes in microtiter plates. Polystyrene microwells were functionalized with multidentate imidazole ligands to immobilize QDs. Oligonucleotide hybridization was transduced using QDs as donors in fluorescence resonance energy transfer (FRET). One detection channel paired green-emitting QD donors with Cy3 acceptors and served as an internal standard. A second detection channel paired red-emitting QDs with Alexa Fluor 647 acceptors and served as the primary detection channel. A selective assay for multiple targets was demonstrated using a 96-well plate format, which combined the advantages of two-plex QD-FRET with the high-throughput capability and convenience of microtiter plates. The assay had excellent resistance to the nonspecific adsorption of DNA and discriminated between fully complementary and single base-pair mismatched sequences with a contrast ratio >2. Under optimal conditions for a single color (green QD) assay format, the limit of detection (LOD) was 4 nM, and the dynamic range was from 20 to 300 nM. In a two-color assay, the detection channel (red QD) exhibited linear response between 4 and 100 nM and a LOD of 4 nM.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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".