Review of Medicinal uses, Phytochemistry and Biological Activities of Antidesma laciniatum and A. membranaceum
Bibliographic record
Abstract
Antidesma laciniatum and A. membranaceum are small trees used as traditional medicines in tropical Africa. This extensive literature review synthesizes the information currently available on the medicinal uses, phytochemistry and biological activities of A. laciniatum and A. membranaceum. The university library and electronic search engines such as Google Scholar, Scopus, Web of Science, ScienceDirect, and PubMed were searched for pertinent information on the medicinal uses, phytochemistry, and biological activities of A. laciniatum and A. membranaceum. Traditionally, the species have been used as aphrodisiac, and traditional medicine for cough, kwashiorkor, mouth ulcers, pneumonia, prevent miscarriage, snakebites, stomachache and wounds. Various phytochemicals such as essential oils, isoflavonoid glycosides, phytosterols, benzopyranones, lignin glucosides, megastigmane, phenolics, steroids, squalene, terpenoids, triterpenoids, and tetrahydroisoquinoline alkaloids have been isolated from A. laciniatum and A. membranaceum. In vitro studies have confirmed the biological activities of A. laciniatum and A. membranaceum which, include antimicrobial, antioxidant, antiplasmodial, antitrypanosomal, leishmanicidal, molluscicidal and cytotoxicity activities. More pharmacological studies including phytochemical, toxicological, in vitro and in vivo experiments are needed to provide evidence for the clinical effectiveness of remedies prepared from the species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".