Detection of Cystic Fibrosis Transmembrane Conductance Regulator ∆F508 Gene Mutation Using a Paper-Based Nucleic Acid Hybridization Assay and a Smartphone Camera
Bibliographic record
Abstract
Diagnostic technology that utilizes paper substrates and device cameras offers opportunities for development of cost effective point-of-care technologies. The translation of assays operating in aqueous solution require further development for implementation in paper substrates. This report presents and compares two methods for determination of oligonucleotides that serve as indicators of Cystic Fibrosis, differentiating wild type and mutant type sequences containing a 3-base deletion. The transduction strategy operates by selective hybridization of dye-labelled oligonucleotides (target or reporters) to capture probes immobilized on quantum dots, and hybridization results in emission of dyes via resonance energy transfer. Detection is based on hybridization of fluorophore labelled target, or hybridization of unlabelled target and labelled reporter in a sandwich assay format. Selectivity to determine mismatched sequences required control of stringency conditions using formamide as a chaotrope. It was determined that both formats can distinguish between wild type and mutant type samples on paper substrates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".