Detection of Large Genomic RNA via DNAzyme‐Mediated RNA Cleavage and Rolling Circle Amplification: SARS‐CoV‐2 as a Model
Bibliographic record
Abstract
A new method for the detection of genomic RNA combines RNA cleavage by the 10-23 DNAzyme and use of the cleavage fragments as primers to initiate rolling circle amplification (RCA). 230 different 10-23 DNAzyme variants were screened to identify those that target accessible RNA sites within the highly structured RNA transcripts of SARS-CoV-2. A total of 28 DNAzymes were identified with >20 % cleavage, 5 with >40 % cleavage and one with >60 % in 10 min. The cleavage fragments from these reactions were then screened for coupling to an RCA reaction, leading to the identification of several cleavage fragments that could efficiently initiate RCA. Using a newly developed quasi-exponential RCA method with a detection limit of 500 aM of RNA, 14 RT-PCR positive and 15 RT-PCR negative patient saliva samples were evaluated for SARS-CoV-2 genomic RNA, achieving a clinical sensitivity of 86 % and specificity of 100 % for detection of the virus in <2.5 h.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".