Development and validation of a rapid loop-mediated isothermal amplification assay for the detection of Chrysomyxa and characterization of Chrysomyxa woroninii overwintering on Picea in China
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
Chrysomyxa rusts cause significant damage to spruce in both natural forests and plantations. Particularly, Three Chrysomyxa species, Chrysomyxa deformans, Chrysomyxa qilianensis, and Chrysomyxa rhododendri, listed as National Forest Dangerous Pests in China, have severely affected many economically and ecologically important spruce native species in China. Also, Chrysomyxa arctostaphyli, an important plant quarantine fungus, causes a damaging broom rust disease on spruce. Therefore, rapid, and efficient detection tools are urgently needed for proper rust disease detection and management. In this study, a sensitive, genus-specific loop-mediated isothermal amplification (LAMP) assay targeting the ITS-28S rRNA region was developed to detect the presence of Chrysomyxa in spruce needle and bud samples. After optimization and validation, the LAMP assay was found to be sensitive to detect as low as 5.2 fg/µL DNA, making it suitable for rapid on-site testing for rust infection. The assay was also specific to Chrysomyxa species, with no positive signals from other rust genus/species. The application of LAMP in the early detection of rust infections in spruce needles and buds was investigated, and spatial colonization profiles as well as the means of overwintering of Chrysomyxa woroninii in infected buds and branches were verified using the LAMP assay. This LAMP detection method will facilitate further studies on the characteristics of the life cycle and inoculation of other systemic rusts.
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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