Development of a Herbal Tea with Potential Antiglycation Effects using <em>Phyllanthus emblica</em> (Indian Gooseberry), <em>Zingiber officinale</em> (Ginger), and <em>Coriander sativum</em> (Coriander)
Bibliographic record
Abstract
The study was conducted to investigate the capability of developing a herbal tea using Phyllanthus emblica (PE) fruit, Zingiber officinale (ZO) rhizome, and Coriander sativum (CS) seeds and to assess its anti-glycation effects. Phyllanthus emblica, ZO, and CS are common and individually used materials in traditional medicine in Sri Lanka. No evidence is found in using combinations of these plant materials being used in commercial tea / herbal infusion production in Sri Lanka. The herbal tea was formulated with powdered form of PE fruits, ZO rhizome and CS seeds in three different formulations; PE-50% + ZO-25% + CS-25%; PE-25% + ZO-50% + CS-25%; and PE-25% + ZO-25% + CS-50%. The three formulated teas were subjected to a five-point hedonic scale sensory evaluation. The formula with PE fruits 50%, ZO rhizome 25%, and CS seeds 25% was selected for further analysis. The phytochemicals of the selected formulation were analyzed, and the results bared the presence of glycosides, alkaloids, terpenoids, saponins, and tannins, which ensures a high antioxidant quality of the formulated tea. The tested parameter for the shelf-life determination study concluded that the product is shelf-stable for 14 days under 0 °C temperature. An in vitro assay using Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis was used to test the antiglycation effects. Results showed that the herbal tea was able to inhibit glycation-induced protein cross-linking over prolonged incubation periods with strong glycating conditions. Therefore, this product could also have a potential to be used as a home remedy to prevent diabetic 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 | 0.000 | 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".