Integrating multi‐index determination coupled with hierarchical cluster analysis to evaluate the quality consistency of PVE30, an anti‐HSV “glycoprotein” macromolecule of Prunellae Spica
Bibliographic record
Abstract
INTRODUCTION: Prunellae Spica (PS), derived from the dried fruit spikes of Prunella vulgaris L., is a traditional Chinese medicinal herb. Our previous studies found that PVE30, a water-extracting ethanol-precipitating "glycoprotein" macromolecule of PS, was a potential anti-herpes simplex virus (HSV) candidate. However, due to the complex structure and diverse bioactivity of the "glycoprotein", ensuring its quality consistency across different batches of PVE30 becomes particularly challenging. This poses a significant hurdle for new drug development based on PVE30. OBJECTIVE: Our study aimed to integrate multi-index determination coupled with hierarchical cluster analysis (HCA) to holistically profile the quality consistency of "glycoprotein" in PVE30. METHODS: High-performance gel permeation chromatography with refractive index detector (HPGPC-RID) was used to characterise the molecular weight (Mw) distribution, HPLC-PDA was used to quantitatively analyse the composed monosaccharides and amino acids, and UV-VIS was used to quantify the contents of polysaccharides and proteins. Qualitative and quantitative consistency was analysed for each single index in 16 batches of PVE30, and a 16 × 38 data matrix, coupled with HCA, was used to evaluate the holistic quality consistency of PVE30. RESULTS: The newly developed and validated methods were exclusive, linear, precise, accurate, and stable enough to quantify multi-indexes in PVE30. Single-index analysis revealed that 16 batches of PVE30 were qualitatively consistent in Mw distribution, polysaccharides and proteins, and the composition of composed monosaccharides and amino acids but quantitatively inconsistent in the relative contents of some "glycoprotein" macromolecules, as well as the composed monosaccharides/amino acids. HCA showed that the holistic quality of PVE30 was inconsistent, the inconsistency was uncorrelated with the regions where PS was commercially collected, and the contents of 17 amino acids and 2 monosaccharides contributed most to the holistic quality inconsistency. CONCLUSION: Multi-index determination coupled with HCA was successful in evaluating the quality consistency of PVE30, and the significant difference in quantitative indices was not caused by the origin of PS. The cultivating basis should be confirmed for PVE30-based new drug development.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".