Bioactivity-guided isolation of the active compounds from Rosa nutkana and quantitative analysis of ascorbic acid by HPLCThis article is one of a selection of papers published in this special issue (part 1 of 2) on the Safety and Efficacy of Natural Health Products.
Bibliographic record
Abstract
Rosa nutkana Presl. (Rosaceae) is distributed abundantly throughout central and southern areas of British Columbia, Canada. Aboriginal people in the Pacific Northwest have traditionally used R. nutkana as a food, medicine, and source of cultural material. The methanolic extract of the fruits of R. nutkana was previously found to have inhibitory activity against methicillin-resistant Staphylococcus aureus (MRSA). In our study, bioactivity-guided fractionation of the methanol extract from R. nutkana led to the isolation of the following 10 compounds: (i) tormentic acid, (ii) euscaphic acid, (iii) ursolic acid, (iv) maslinic acid, (v) quercetin, (vi) catechin gallate, (vii) quercetin-3-O-glucoside, (viii) 1,2,3,4,6-penta-O-galloyl-beta-D-glucoside, (ix) L-ascorbic acid (vitamin C), and (x) 1,6-digalloyl-beta-D-glucoside. Structures were elucidated by ultraviolet, infrared, mass spectrometry, and nuclear magnetic resonance data, as well as by comparison with those of the literature. The compounds quercetin, catechin gallate, quercetin-3-O-glucoside, 1,2,3,4,6-penta-O-galloyl-beta-D-glucoside, and 1,6-digalloyl-beta-D-glucoside exhibited weak antibacterial activity against MRSA. Our research demonstrates the value of traditional knowledge held by Aboriginal people in the Pacific Northwest with respect to uses of R. nutkana. Some described uses in the ethnobotanical literature correspond to activities observed under laboratory conditions. Further work on British Columbia Rosa spp. may contribute to identifying other potential therapeutic uses.
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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) | 0.001 | 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 | 0.001 |
| 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".