CRISPR/Cas12a-based approaches for efficient and accurate detection of Phytophthora ramorum
Bibliographic record
Abstract
Introduction Phytophthora ramorum is a quarantine pathogen that causes leaf blight and shoot dieback of the crown, bark cankers and death on a number of both ornamental and forest trees, especially in North America and northern Europe, where it has produced severe outbreaks. Symptoms caused by P. ramorum can be confused with those by other Phytophthora and fungal species. Early and accurate detection of the causal pathogen P. ramorum is crucial for effective prevention and control of Sudden Oak Death. Methods In this study, we developed a P. ramorum detection technique based on a combination of recombinase polymerase amplification (RPA) with CRISPR/Cas12a technology (termed RPACRISPR/ Cas12a). Results This novel method can be utilized for the molecular identification of P. ramorum under UV light and readout coming from fluorophores, and can specifically detect P. ramorum at DNA concentrations as low as 100 pg within 25 min at 37°C. Discussion We have developed a simple, rapid, sensitive, unaided-eye visualization, RPA CRISPR/Cas12a-based detection system for the molecular identification of P. ramorum that does not require technical expertise or expensive ancillary equipment. And this system is sensitive for both standard laboratory samples and samples from the field.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".