Supplementary Material for: Evaluation of Antidepressant-Like Activity of Novel Water-Soluble Curcumin Formulations and St. John's Wort in Behavioral Paradigms of Despair
Bibliographic record
Abstract
Background: Curcumin is the active principle of Curcuma longa, one of the widely used components in the traditional system of medicine in India. Despite its efficacy in experimental studies aiming at neuronal disorders like depression, curcu-min's poor water solubility challenges the production of therapeutic formulations. This study investigates the antidepressant-like activity of novel water-soluble curcumin formulations, dispensed in three different concentrations. Further, the study comparatively evaluates St. John's wort (SJW), another herbal preparation. Methods: These compounds were evaluated in the forced swimming test in mice, and the corresponding changes in the neurotransmitter levels were measured. Results: Three water-soluble curcumin formulations, C-5, C-20 and C-50 (50-200 mg/kg p.o.) decreased the immobility period, and increased serotonin and dopamine levels in the brain tissues. A subeffective dose (50 mg/kg) of these formulations enhanced the antidepressant-like effect of classical antidepressants with varied mechanisms of action. In addition, an SJW dose of 25 mg/kg showed a significant antidepressant-like effect in all the behavioral studies and also significantly increased brain neurotransmitter levels, especially that of serotonin. The effects produced by C-5 were comparable with those of SJW and fluoxetine, respectively. Conclusion: In all these observations, the water-soluble formulations showed a significant antidepressant-like effect, including enhancement of neurotransmitter levels as compared to the similar dose of a conventional curcumin preparation. Thus, these formulations may be used as a novel treatment option in the management of mental depression.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.752 | 0.228 |
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".