Screening of <scp><i>Bletilla striata</i></scp>, <i>Bletilla ochracea</i> and <i>Oreorchis foliosa</i> differential metabolites based on metabolomics
Bibliographic record
Abstract
Abstract As a representative medicinal plant in the Orchidaceae, Bletilla striata plays a variety of pharmacological roles in the clinic. However, the emergence of counterfeit species is affecting the basic medicinal materials source identification process, for which Bletilla ochracea and Oreorchis foliosa of the Orchidaceae are two representative species. For this study, 13 representative B. striata samples, three B. ochracea samples and three O. foliosa samples were selected for the systematic determination of polysaccharide yields and monosaccharide composition, and further detection of secondary metabolites by HPLC–MS. The results revealed that there was a significant difference in the yields of polysaccharides between B. striata and B. ochracea ( p = 0.006). Although the polysaccharides of both species were composed of glucose and mannose, the molar ratio of the two monosaccharides was different, suggesting that the structures of the polysaccharides were different. The metabolomics results showed that there were no differences in the types of metabolites between B. striata and B. ochracea ; however, there were differences in the contents of these metabolites. Although there was no significant difference in the polysaccharide yields of B. striata and O. foliosa ( p = 0.074) and the monosaccharide composition was the same (glucose and mannose), many different metabolites were screened out between them: six compounds such as C 36 H 34 O 11 existed only in B. striata , while substance C 39 H 54 O 22 was unique to O. foliosa . Therefore, based on the analysis of the polysaccharide content and monosaccharide composition, combined with phase metabolomics research, a preliminary distinction between B. striata , B. ochracea and O. foliosa was achieved.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".