Yarrow by Parts: An Ethnobotanical, Pharmacological, and Metabolomics Analysis of One of North America's Most Important Medicinal Plants
Bibliographic record
Abstract
Achillea millefolium, also known as Yarrow, is a flowering plant in the family Asteraceae with a global distribution and long history as a herbal medicine. Meta-analysis of ethnobotanical data reveals that Yarrow is highly selected by North American Indigenous groups for medicinal use, in general, and as treatment of pulmonary and orthopedic symptoms, in particular. These ethnobotanical applications are reflected by the presence of bioactive compounds with known anti-inflammatory, antimicrobial, and anxiolytic properties. However, while distinct plant parts appear preferentially selected for specific applications, the phytochemistry and bioactivity of different Yarrow tissues remains poorly studied. Accordingly, we tested extracts of Yarrow root, leaf, stem and flower in a battery of bioassays targeting inflammation, the endocannabinoid system, and glucose metabolism. Flower and root extracts were consistently identified as the most active and were respectively enriched in flavonoids and alkylamides. Mass spectrometry-based metabolomics was then used to investigate phytochemical differences of between root, leaf, stem and flower samples collected throughout the growing season. Multivariate statistical analysis showed separation between the plant parts and enabled the putative identification of metabolites selectively detected in each individual plant part were putatively identified. Supporting In support of ethnobotanical reports of distinct medicinal properties, the four structural parts of A. millefolium showed distinct pharmacological and chemical profiles, with flowers, roots, and their active metabolites warranting additional study.
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".