Antioxidant and Glucose Lowering Effects of Hydroethanolic Extract of Baillonella toxisperma Pulp
Bibliographic record
Abstract
Hyperglycemia and oxidative stress play an important role in the pathogenesis of diabetes. Their management is a key point in the prevention and treatment of this disease which is a potential cause of mortality in the world. We evaluated the antioxidant and glucose lowering effects of hydroethanolic extract of Baillonella toxisperma pulp. The total polyphenol and flavonoid contents were determined and the antioxidant activity was evaluated by 3 mechanisms: scavenging by DPPH•, ABTS• and NO• radicals; reducing property by MoO42+ and Fe3+ reduction; metal chelation by Cu2+ and Fe2+. Glucose adsorption capacity was evaluated followed by the capacity to promote insulino-sensitivity through glucose uptake by yeast and muscle cell assays. The hydroethanolic extract of B. toxisperma pulp possessed high total polyphenols and flavonoids; 459.55 µg Equivalent Gallic Acid/mg and 252.15 µg of Equivalent Catechin /mg respectively. This showed their ability to scavenge DPPH•, ABTS• and NO• radicals with SC50 of 3.49, 3.24 and 4.28 mg/ml respectively. The extract also reduced MoO42+ and Fe3+ and chelated Cu2+ through inhibiting their capacity to induce hemolysis with the IC50 of 3.49 mg/ml. The extract showed a high glucose binding capacity with a glucose binding percentage rise of 60 %. It increased yeast cell absorption of glucose with the increasing percentage varying from 42.97 to 56.62 %. In the muscle cells, after 30 min of administration of the extract, we also noted an increased glucose absorption with the percentage glucose reducing to 22 %. We demonstrated that hydroethanolic extract of B. toxisperma pulp possess antiradical, reducing, metal chelating, glucose binding and insulino-sensitivity promoting properties. These mechanisms imply that B. toxisperma pulp is both a good antioxidant and an antihyperglycemiant, thus a potential agent in the management of diabetes and its complications.
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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 | 0.001 | 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 | 0.000 |
| 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".