Development of a Simplified <scp>PCR</scp> ‐Nucleic Acid Lateral Flow Immunoassay ( <scp>PCR</scp> ‐ <scp>NALFIA</scp> ) for <i>Cryptostroma corticale</i> , the Causal Agent of Sooty Bark Disease
Bibliographic record
Abstract
ABSTRACT Sooty bark disease (SBD), caused by the fungus Cryptostroma corticale , is causing a widespread outbreak on sycamore maple in Europe and is presently emerging as a threat to urban and native maple trees in the Pacific Northwest. Rising temperatures and prolonged drought conditions probably exacerbate SBD disease severity. Current detection methods for C . corticale rely on laboratory‐based PCR and morphological identification, which require specialised equipment and are not suited for rapid field deployment. We developed a portable, species‐specific PCR‐nucleic acid lateral flow immunoassay (PCR‐NALFIA) for point‐of‐care detection of C . corticale . The assay can be performed in 90 min by incorporating a 5‐min crude DNA extraction using cellulose dipsticks, a species‐specific ITS1‐targeted PCR with internal probe labelling on a portable PCR machine, and a lateral flow dipstick for visual detection. The method yielded accurate detection from infected wood, bark and conidia, with detection thresholds as low as 10 conidia or 0.1 mg of stroma in 0.5 mL buffer. The PCR‐NALFIA achieved 100% specificity when tested on 87 fungal samples, outperforming other available PCR assays. Furthermore, lyophilised reaction mixes were stable for 60 days at room temperature, making the assay viable for field applications. This tool offers a rapid and reliable diagnostic solution for managing SBD in forestry and urban environments.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".