Study of antidiabetic properties and chemical composition of two Phyllanthus species usually consumed by Guadeloupean
Bibliographic record
Abstract
Many people worldwide use plants, alone or in combination with their antihyperglycemic drugs, to manage their type 2 diabetes mellitus [1][2]. Most researches on therapeutic properties of herbs are carrying out on methanolic or ethanolic extracts [3]. However, these studies are not representative of the population consumption habits. For the first time, a study was performed with specimens of the two mostly used species in Guadeloupe: Phyllanthus amarus and Phyllanthus debilis. The chemical composition of aqueous infusion of dried aerial parts were evaluated in relationship to antidiabetic mechanisms occurring at the level of glucose homeostasis in cultured hepatocytes (H4IIE) and muscle cells (C2C12). On the one hand, the extracts of P. amarus showed a significant activity in glucose uptake on muscle cells with an increase of 23.11 ± 3.84 % whereas it was no significant for P. debilis (13.4 ± 3.28 %). On the other hand, the same extracts of P. debilis showed stronger inhibition of hepatocellular G6Pase activity (65.88 ± 4.28 %), close to the action of insulin (64.29 ± 4.59 %), than P. amarus extracts (34.6 ± 1.45 %). The comparison of their chemical composition demonstrated the presence of polyphenols, especially hydrolyzable ellagitannins, involved in their antidiabetic effects. Only four molecules were common to both species, galactaric acid lactone, gallic acid, 5-O-(E)-caffeoyl galactaric acid, a new compound found for the first time in both species, and geraniin. The study of the antidiabetic activity of geraniin, which is predominant in P. debilis, showed a significant inhibition of G6Pase (60.67 ± 2.33 %) whereas no significant activity was observed for glucose uptake. These results suggest that this compound greatly influence the antidiabetic effects of the Phyllanthus crude extracts.[1] Genthon, L. (2014). Contribution à l’étude de la connaissance et de l’utilisation des plantes de la pharmacopée locale par la population guadeloupéenne. [2] Patel, J. R., Tripathi, P., Sharma, V., Chauhan, N. S., & Dixit, V. K. (2011b). Phyllanthus amarus: Ethnomedicinal uses, phytochemistry and pharmacology: A review. Journal of Ethnopharmacology, 138(2), 286-313. doi:http://dx.doi.org/10.1016/j.jep.2011.09.040[3] Kumaran, A., & Joel Karunakaran, R. (2007). In vitro antioxidant activities of methanol extracts of five Phyllanthus species from India. LWT - Food Science and Technology, 40(2), 344-352. doi:http://dx.doi.org/10.1016/j.lwt.2005.09.011
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".