A rapid LAMP assay for the diagnosis of oak wilt with the naked eye
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Oak wilt disease, caused by Bretziella fagacearum is a significant threat to oak (Quercus spp.) tree health in the United States and Eastern Canada. The disease may cause dramatic damage to natural and urban ecosystems without management. Early and accurate diagnosis followed by timely treatment increases the level of disease control success. RESULTS: A rapid assay based on loop mediated isothermal amplification (LAMP) was first developed with fluorescence detection of B. fagacearum after 30-minute reaction time. Six different primers were designed to specifically bind and amplify the pathogen's DNA. To simplify the use of this assay in the field, gold nanoparticles (AuNPs) were designed to bind to the DNA amplicon obtained from the LAMP reaction. Upon inducing precipitation, the AuNP-amplicons settle as a red pellet visible to the naked eye, indicative of pathogen presence. Both infected and healthy red oak samples were tested using this visualization method. The assay was found to have high diagnostic sensitivity and specificity for the B. fagacearum isolate studied. Moreover, the developed assay was able to detect the pathogen in crude DNA extracts of diseased oak wood samples, which further reduced the time required to process samples. CONCLUSIONS: In summary, the LAMP assay coupled with oligonucleotide-conjugated gold nanoparticle visualization is a promising method for accurate and rapid molecular-based diagnosis of B. fagacearum in field settings. The new method can be adapted to other forest and plant diseases by simply designing new primers.
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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 | 0.001 | 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