A Review of Medicinal Uses, Phytochemistry and Biological Activities of Markhamia tomentosa
Bibliographic record
Abstract
Markhamia tomentosa (Benth.) K. Schum. ex Engl. is a shrub or small tree widely used as traditional medicine throughout its distributional range in west Africa. This study was aimed at providing a critical review of medicinal uses, phytochemistry and biological activities of M. tomentosa. Documented information on medicinal uses, phytochemistry and biological activities of M. tomentosa was collected from several online sources such as Scopus, Google Scholar, PubMed and Science Direct, and pre-electronic sources such as book chapters, books, journal articles and scientific publications obtained from the University library. This study revealed that the bark, leaf, root and stem bark decoction and/or infusion of M. tomentosa are mainly used as traditional medicine for elephantiasis, infertility, skin infections, rheumatism, eye problems, pain, diabetes and fever. Phytochemical compounds identified from the species include alkaloids, anthraquinones, cardiac glycosides, flavonoids, phenolics, saponins, sterols, tannins and triterpenoids. Markhamia tomentosa crude extracts and compounds isolated from the species exhibited analgesic, acetylcholinesterase and butyrylcholinesterase inhibitory, anti-amnesic, antibacterial, antifungal, antifeedant, anti-inflammatory, antioxidant, antiplasmodial, antitrypanosomal, antiulcer, larvicidal, leishmanicidal and cytotoxicity activities. Markhamia tomentosa should be subjected to detailed phytochemical, pharmacological and toxicological evaluations aimed at correlating its medicinal uses with its phytochemistry and pharmacological activities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.005 | 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".