Biological Investigation of Amaryllidaceae Alkaloid Extracts from the Bulbs of Pancratium trianthum Collected in the Senegalese Flora
Bibliographic record
Abstract
Amaryllidaceae plants are rich in alkaloids with biological properties. Pancratium trianthum is an Amaryllidaceae species widely used in African folk medicine to treat several diseases such as central nervous system disorders, tumors, and microbial infections, and it is used to heal wounds. The current investigation explored the biological properties of alkaloid extracts from bulbs of P. trianthum collected in the Senegalese flora. Alkaloid extracts were analyzed and identified by chromatography and mass spectrometry. Alkaloid extracts from P. trianthum displayed pleiotropic biological properties. Cytotoxic activity of the extracts was determined on hepatocarcinoma Huh7 cells and on acute monocytic leukemia THP-1 cells, while agar diffusion and microdilution assays were used to evaluate antibacterial activity. Antiviral activity was measured by infection of extract-treated cells with dengue virus (DENVGFP) and human immunodeficiency virus-1 (HIV-1GFP) reporter vectors. Cytotoxicity and viral inhibition were the most striking of P. trianthum’s extract activities. Importantly, non-cytotoxic concentrations were highly effective in completely preventing DENVGFP replication and in reducing pseudotyped HIV-1GFP infection levels. Our results show that P. trianthum is a rich source of molecules for the potential discovery of new treatments against various diseases. Herein, we provide scientific evidence to rationalize the traditional uses of P. trianthum for wound treatment as an anti-dermatosis and antiseptic agent.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".