Engineering Gene-Specific DNAzymes for Accessible and Multiplexed Nucleic Acid Testing
Why this work is in the frame
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The accurate and timely detection of disease biomarkers at the point-of-care is essential to ensuring effective treatment and epidemiological surveillance. Here, we report the selection and engineering of RNA-cleaving DNAzymes that respond to specific genetic markers and amplify detection signals. Because the target-specific activation of gene-specific DNAzymes (gDz) is like the trans-cleavage activity of clustered regularly interspaced short palindromic repeats (CRISPR) CRISPR-associated (Cas) machinery, we further developed a CRISPR-like assay using RNA-cleaving DNAzyme coupled with isothermal sequence and signal amplification (CLARISSA) for nucleic acid detection in clinical samples. Building on the high sequence specificity and orthogonality of gDzs, CLARISSA is highly versatile and expandable for multiplex testing. Upon integration with an isothermal recombinase polymerase amplification, CLARISSA enabled the detection of human papillomavirus (HPV) 16 in 189 cervical samples collected from cervical cancer screening participants ( n = 189) with 100% sensitivity and 97.4% specificity, respectively. A multiplexed CLARISSA further allowed the simultaneous analyses of HPV16 and HPV18 in 46 cervical samples, which returned clinical sensitivity of 96.3% for HPV16 and 83.3% for HPV18, respectively. No false positives were found throughout our tests. Besides the fluorescence readout using fluorogenic reporter probes, CLARISSA is also demonstrated to be fully compatible with a visual lateral flow readout. Because of the high sensitivity, accessibility, and multiplexity, we believe CLARISSA is an ideal CRISPR-Dx alternative for clinical diagnosis in field-based and point-of-care applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it