Antimicrobial activity and phytochemical screening of buchenavia tetraphylla (aubl.) R. A. Howard (combretaceae: combretoideae)
Bibliographic record
Abstract
This study evaluated the antimicrobial and hemolytic activities and phytochemical constituents of hydroalcoholic extract and its fractions from Buchenavia tetraphylla leaves. Cyclohexane (BTCF), ethyl acetate (BTEF), and n-butanol-soluble (BTSBF) and non-soluble (BTNBF) fractions were obtained from a liquid-liquid partition of hydroalcoholic extract (BTHE) from B. tetraphylla leaves. The hemolytic activity of active fractions was checked. The BTHE inhibited the growth of Micrococcus luteus (MIC: 0.10 mg/mL), Pseudomonas aeruginosa (MIC: 0.20 mg/mL), Mycobacterium smegmatis (MIC: 0.39 mg/mL), Proteus vulgaris, and Staphylococcus aureus(MIC: 0.78 mg/mL for both). The more active fractions were BTCF and BTBSF. BTCF showed better potential to inhibit M. luteus (0.10 mg/mL), P. aeruginosa (0.20 mg/mL), S. enteritidis (0.39 mg/mL), and S. aureus (1.56 mg/mL). BTBSF showed the best results for M. luteus (0.10 mg/mL), M. smegmatis, B. subtilis (0.39 mg/mL for both), and P. vulgaris (0.10 mg/mL). The HC50 were greater than observed MIC: 20.30, 4.70 and 2.53 mg/mL, respectively, to BTBF, BTHE and BTCF, which. The phytochemical analysis detected the presence of flavanoids, triterpene, carbohydrate, and tannin. Our work showed for the first time the broad-spread antimicrobial activity of B. tetraphylla, which has nonhemolytic action, creating a new perspective on the interesting association of traditional and scientific knowledge.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".