Ultra-fast detection and quantification of nucleic acids by amplification-free fluorescence assay
Bibliographic record
Abstract
Two types of clinically important nucleic acid biomarkers, microRNA (miRNA) and circulating tumor DNA (ctDNA) were detected and quantified from human serum using an amplification-free fluorescence hybridization assay. Specifically, miRNAs hsa-miR-223-3p and hsa-miR-486-5p with relevance for rheumatoid arthritis and cancer related mutations BRAF and KRAS of ctDNA were directly measured. The required oligonucleotide probes for the assay were rationally designed and synthesized through a novel "clickable" approach which is time and cost-effective. With no need for isolating nucleic acid components from serum, the fluoresence-based assay took only 1 hour. Detection and absolute quantification of targets was successfully achieved despite their notoriously low abundance, with a precision down to individual nucleotides. Obtained miRNA and ctDNA amounts showed overall a good correlation with current techniques. With appropriate probes, our novel assay and signal boosting approach could become a useful tool for point-of-care measuring other low abundance nucleic acid biomarkers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".