Diagnosis and characterization of the ribosomal DNA-ITS of potato rot nematode (Ditylenchus destructor) populations from Chinese medicinal herbs
Bibliographic record
Abstract
The potato rot nematode (Ditylenchus destructor) is a very economically important nematode in agronomic and horticultural plants worldwide. In this study, 43 populations of D. destructor were collected from different hosts across China, including 37 populations from Chinese herbal medicine plants. Obtained sequences of ITS-rDNA and D2-D3 of 28S-rDNA genes of D. destructor were compared and analyzed. 9 types of significant length variations in ITS sequences were observed among all populations. The differences in ITS1 length were mainly caused by the presence of repetitive elements with substantial base substitutions. Reconstructions of ITS1 secondary structures showed that the minisatellites formed a stem structure. 10 haplotypes were observed in all populations based on mutations and variations of helix H9. Among them, 3 known haplotypes (A-C) were found in 7 populations isolated from potato, sweet potato, and Codonopsis pilosula, and 7 unique haplotypes were found in other 36 populations collected from C. pilosula and Angelica sinensis compared with 7 haplotypes (A-G) of Subbotin' system. These unique haplotypes were different from haplotypes A-G, and we named them as haplotypes H-N. The present results showed that a total of 14 haplotypes (A-N) of ITS-rDNA have been found in D. destructor. Phylogenetic analyses of ITS-rDNA and D2-D3 showed that all populations of D. destructor were clustered into two major clades: one clade only containing Haplotype A from sweet potato and the other containing haplotypes B-N from other plants. For further verification, PCR-ITS-RFLP profiles were conducted on 7 new haplotypes. Collectively, our study suggests that D. destructor populations on Chinese medicinal materials are very different from those on other hosts and this work provides a paradigm for relevant researches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".