Authentication of official Da-huang by sequencing and multiplex allele-specific PCR of a short maturase K gene
Bibliographic record
Abstract
Rhubarb (official Da-huang) is an important medicinal herb in Asia. Many adulterants of official Da-huang have been discovered in Chinese markets in recent years, which has resulted in adverse effects in medicinal treatment. Here, novel molecular markers based on a short maturase K (matK) gene were developed for authenticating official Da-huang. This study showed that all the species from official Da-huang were clustered together in one clade in the polygenetic trees based on short matK. Two highly conserved single nucleotide polymorphisms of short matK were mined in the species from official Da-huang. Based on these polymophisms, four improved specific primers of official Da-huang were successfully developed that generated reproducible specific bands. These results suggest that the short matK sequence can be considered as a favorable candidate for distinguishing official Da-huang from its adulterants. The established multiplex allele-specific PCR was determined to be simple and accurate and may serve as a preferable tool for authentication of official Da-huang. In addition, we suggest that short-sized specific bands be developed to authenticate materials used in traditional Chinese medicine.
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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 | 0.001 |
| 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) | 0.001 | 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".