Phytochemicals from medicinal plants from African forests with potentials in rheumatoid arthritis management
Bibliographic record
Abstract
OBJECTIVES: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammation, pain, and cartilage and bone damage. There is currently no cure for RA. It is however managed using nonsteroidal anti-inflammatory drugs, corticosteroids and disease-modifying anti-rheumatic drugs, often with severe side effects. Hidden within Africa's lush vegetation are plants with diverse medicinal properties including anti-RA potentials. This paper reviews the scientific literature for medicinal plants, growing in Africa, with reported anti-RA activities and identifies the most abundant phytochemicals deserving research attention. A search of relevant published scientific literature, using the major search engines, such as Pubmed/Medline, Scopus, Google Scholar, etc. was conducted to identify medicinal plants, growing in Africa, with anti-RA potentials. KEY FINDINGS: Twenty plants belonging to 17 families were identified. The plants are rich in phytochemicals, predominantly quercetin, rutin, catechin, kaempferol, etc., known to affect some pathways relevant in RA initiation and progression, and therefore useful in its management. SUMMARY: Targeted research is needed to unlock the potentials of medicinal plants by developing easy-to-use technologies for preparing medicines from them. Research attention should focus on how best to exploit the major phytochemicals identified in this review for the development of anti-RA 'green pharmaceuticals'.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".