Neurochemical Studies with St. John's WortInVitro
Bibliographic record
Abstract
The effect of extracts and constituents of St. John's wort, Hypericum perforatum, at various CNS receptors were studied by radioligand binding techniques in order to determine a profile of pharmacological activity in vitro. Binding inhibition was examined for the G-protein coupled opioid, serotonin (5-HT), histamine, neurokinin and corticotropin releasing factor (CRF) receptors, for the steroid estrogen-alpha receptor and for the ligand-gated ionchannel GABA(A) receptor. Hypericin showed the most potent binding inhibiton of all tested constituents to human CRF1 receptor with an IC50 value of 300 nM. Preliminary GTPgamma35S binding studies to CRF1 coupled G-protein indicated an antagonistic action for hypericin. The acylphloroglucinole hyperforin failed to inhibit 125I-astressin binding to hCRF, receptor up to 10 microM. Hyperforin inhibited binding to opioid and serotonin (5-HT) receptors at IC50 values between 0.4 and 3 microM, while hypericin and pseudohypericin inhibited with weaker potency. The biflavonoid I3,II8-biapigenin inhibited 3H-estradiol binding to the estrogen-alpha receptor with an IC50 value of 1 microM. The inhibition of 3H-muscimol binding to the GABA(A) receptor is likely to be exclusively due to GABA present in the extract. We therefore hypothesize that additive or synergistic actions of several ditsinct compounds may be responsible for the beneficial antidepressant effect of St. John's wort.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".