Phytochemical Profiles, Micromorphology, and Elemental Composition of Gomphocarpus fruticosus (L.) W.T. Aiton and Leonotis leonurus (L.) R.Br., Plants Used for Managing Antidepressant-like Conditions in Folk Medicine
Bibliographic record
Abstract
Medicinal plants have been used to treat mental health-related conditions among different ethic groups. Among the commonly used plants in South Africa are Gomphocarpus fruticosus (L.) W.T.Aiton and Leonotis leonurus (L.) R.Br. This study aimed at generating the phytochemical profiles, micromorphology, and elemental composition of the leaves of G. fruticosus and L. leonurus as possible means of explaining the basis for their utilisation for mental health-related conditions in folk medicine and consideration for further development. The plant parts were subjected to successive solvent extractions using an ultrasonic method with dichloromethane (DCM) and were chemically characterised using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS). Scanning electron microscopy (SEM) was used to examine the micromorphology of the fresh leaves and energy-dispersive X-ray Spectrometry (EDX) was utilised to perform mineral elemental analyses of G. fruticosus and L. leonurus using their leaf powder. We identified phytochemicals including rutin and marrubiin, which are known to alleviate depression-like symptoms. Glandular and non-glandular trichomes were present in the plants. A weight (%) of 1.32 and 0.82 for calcium, 1.16 and 1.99 for potassium, and 0.38 and 0.38 magnesium were present in G. fruticosus and L. leonurus, respectively. These minerals have been linked to mental health stability, with imbalances associated with various disorders. We established the chemical composition that could suggest potential therapeutic effects of these two medicinal plants, offering insights into their uses in folk medicine and potential modern applications in treating mental health issues.
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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 | 0.000 | 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 | 0.001 |
| 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".