Interactions of Echinacea spp. Root Extracts and Alkylamides With the Endocannabinoid System and Peripheral Inflammatory Pain
Bibliographic record
Abstract
Historical ethnobotanies of indigenous peoples of the North American prairies reveal treatment of many painful conditions by Echinacea spp. Recent evidence suggests a pharmacological basis for such use as the bioactivity of E. angustifolia and E. purpurea is mediated, in part, through activation of the endocannabinoid system (ECS). Whereas the cannabimimetic effects of individual echinacea products and alkylamides have been described, the activity of crude extracts has not been compared between cannabinoid (CB) receptors or across species or genotypes. Moreover, few studies have explored echinacea’s engagement of the ECS for historic treatments or new therapeutic applications in peripheral inflammatory pain. We hypothesized that 1) the in vitro effects of root extracts on CB receptor internalization would vary with species and phytochemistry, and that echinacea root extracts would reduce inflammatory pain in vivo through activation of the ECS. Root extracts of different E. angustifolia and E. purpurea accessions were prepared, analyzed by HPLC-DAD to quantify caffeic acid derivatives and alkylamides (AKA), and tested for agonist and antagonist activities using receptor redistribution assays. Linear regression of activity relative to phytochemistry identified predictive compounds that were assessed individually in redistribution assays. Extracts were evaluated in the Hargreaves model of chronic inflammatory pain in rats with co-administration of selective CB1/2 antagonists to gauge involvement of the ECS. CB receptor agonist activity varied among accessions of both species with linear regression revealing a significant relationship between CB1 activity and AKA2 for E angustifolia , and AKA 9 + 10 for E purpurea . CB2 activity was positively related with AKA 9 + 10 and total AKAs in E. angustifolia . Four isolated AKA demonstrated agonist activity in the CB2, but not CB1, assay. In the inflammatory pain model, oral administration of either E angustifolia or E. purpurea root extract produced dose-dependent analgesic effects that were partially reversed by co-administration of CB receptor antagonists. This study demonstrates that in vitro effects of crude echinacea root extracts on CB receptors is predicted by phytochemistry. In vivo, echinacea has potential applications for peripheral inflammatory pain such as arthritis and burns, reflecting the traditional uses of Indigenous North Americans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".