Pharmacological in vivo test to evaluate the bioavailability of some St. John's wort innovative oral preparations
Bibliographic record
Abstract
Preparations based on extracts of St. John's wort are widely marketed for treating mild to moderately severe depressive disorders and other health conditions such as anxiety and sleep disorders [1]. Active principles are not yet discovered and flavonols, based on quercetin aglycone, naphthodianthrones (hypericin and pseudohypericin) and phloroglucinols such as hyperforin, adhyperforin seems to be related to this action. Thus, flavonols and naphthodianthrones are polyphenols, quite polar derivatives but their water solubility is very scarce; phloroglucinols are lipophilic and completely not water-soluble constituents. In addition, hypericins and hyperforins are not stable with regard to heat and light [2]. In this study the optimisation of technological and pharmaceutical aspects of dried commercial extract of St. John's wort were evaluated by the in vivo “Porsolt test“. Solid dosage forms containing β-cyclodextrin and micellear systems (SDS, ASC-8) were compared in the “Porsolt test“ with the extract alone. The extract showed the antidepressant activity in the mice after 60 minutes and with the dosage of 100mg/kg. The same antidepressant activity appeared in 30min with a micellar solution of SDS 40mM containing the same quantity of extract (100mg/kg), while with micelles of ASC-8 40 mM the effect appeared at 15min and with a dosage of 30mg/kg. In the case of colyophilized with β-cyclodextrin the best results were obtained at 30min, administering 60mg/kg of the extract. Acknowledgements: The financial support of MIUR (PRIN 2004) and Ente Cassa di Risparmio di Firenze is gratefully acknowledged for financial support. References : 1. Chatterjee, S.S. et al. (1998), Pharmacopsychiatry 31: 7–15. 2 Bilia A.R. et al. (2001), Int. J. Pharm. 213: 199–208.
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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) | 0.003 | 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".