Lamiophlomis rotata, an Orally Available Tibetan Herbal Painkiller, Specifically Reduces Pain Hypersensitivity States through the Activation of Spinal Glucagon-like Peptide-1 Receptors
Bibliographic record
Abstract
BACKGROUND: Lamiophlomis rotata is an orally available Tibetan herb prescribed for the management of pain, with shanzhiside methylester (SM) and 8-O-acetyl-SM as quality control ingredients. This study aimed to evaluate the antinociceptive properties of L. rotata, determine whether SM and 8-O-acetyl-SM are principle effective ingredients, and explore whether L. rotata produces antinociception through activation of spinal glucagon-like peptide-1 receptors (GLP-1Rs). METHODS: Formalin test, neuropathic pain, and bone cancer pain models were used, and the animal sample size was 5 to 6 in each group. Hydrogen peroxide-induced oxidative damage was also assayed. RESULTS: The L. rotata aqueous extract blocked formalin-induced tonic hyperalgesia and peripheral nerve injury- and bone cancer-induced mechanical allodynia by 50 to 80%, with half-effective doses of 130 to 250 mg/kg, close to the human dosage. The herb was not effective in alleviating acute nociceptive pain. A 7-day gavage with L. rotata aqueous extract did not lead to antiallodynic tolerance. Total iridoid glycosides, rather than total flavonoids, were identified by the activity-tracking method as effective ingredients for antihyperalgesia, whereas both SM and 8-O-acetyl-SM were principal components. Further demonstrations using the GLP-1R antagonist and gene silencer against GLP-1R at both the spinal and the cellular levels indicated that L. rotata inhibited pain hyperactivity by activation of spinal GLP-1Rs, and SM and 8-O-acetyl-SM appeared to be orthosteric, reversible, and fully intrinsic agonists of both rat and human GLP-1Rs. CONCLUSIONS: Results support the notion that the activation of spinal GLP-1Rs leads to specific antinociception in pain hypersensitivity and further suggest that GLP-1R is a human-validated target molecule for the treatment of chronic pain.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".