Vitex doniana, In-Vitro Antioxidant, Membrane Stabilization Potential and Protective Impact Against Plasmodium berghei-Passaged Mice
Bibliographic record
Abstract
Background and objectives: Vitex doniana Sweet (Lamiaceae) is used to treat various ailments, including respiratory infections, liver diseases, anaemia and jaundice. This study assessed the in vitro antioxidant and membrane stabilization potential, as well as the protective impact of semi-purified solvent fractions of V. doniana leaves against Plasmodium berghei-passaged mice. Methods: Dried leaves were extracted with ethanol, followed by fractionation using a solvent-gradient system of increasing polarity (hexane, ethyl acetate, and methanol), and the concentrated fractions were obtained. Forty-two mice were randomly divided into seven groups as: group 1 (normal control), group 2 (disease control, untreated), while groups 3 to 7 received the standard drugs (artequick and chloroquine) and combined V. doniana fraction (VDF, 100 mg/kg) at varying ratios. Results: Comparatively to V. doniana extract, the fractions (F6, F8) displayed considerable antioxidant activity by scavenging O2•–, OH• and DPPH radicals, and effectively reduced Fe3+ to Fe2+. VDF (1:1) at different concentrations (200, 400, 600 µg/mL) inhibited erythrocyte haemolysis by 91.29±3.61%, 80.52±0.13%, 75.68±1.45% and 80.57±0.94%, respectively. Also, the VDF in synergy with artequick and chloroquine decreased parasitaemia levels by 4.25±0.25% and 4.65±0.28% compared to the disease control (7.93±1.61%). The combined fractions significantly normalized the plasma calcium concentration (1.85±0.17 mg/dL, 1.65±0.21 mg/dL, 1.72±0.23 mg/dL, 1.65±0.22 mg/dL) for groups 3 to 6 compared to the disease control (1.30±0.09 mg/dL), while the bodyweights presented no significant change in all experimental groups. Conclusion: The results indicate the promising potential of V. doniana as a drug candidate in managing malarial infection.
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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) | 0.000 | 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 | 0.000 | 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".