Toward a hybridization assay using fluorescence resonance energy transfer and quantum dots immobilized in microfluidic channels
Bibliographic record
Abstract
Quantum dots (QDs) have been widely adopted as integrated components of bioassays and biosensors. In particular, solid phase nucleic acid hybridization assays have been demonstrated to have several advantages and permit the detection of up to four DNA targets simultaneously using fluorescence resonance energy transfer (FRET). This work explores the potential for miniaturization of a solid-phase nucleic acid hybridization assay using QDs and FRET on a microfluidics platform. A method was developed for the immobilization of Streptavidin coated QDs and the preparation of QD-probe oligonucleotide conjugates within microfluidic channels using electrokinetic delivery. Proof-of-concept was demonstrated for the selective detection of target DNA using FRET-sensitized emission from a Cy3 acceptor paired with a green emitting QD donor. The microfluidic platform offered the advantages of smaller sample volumes, nearly undetectable non-specific adsorption, and hybridization within minutes. This work is an important first step toward the development of biochips that enable the multiplexed detection of nucleic acid targets.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".