Authentication of Fruit Extracts of Embica officinalis Gaertn (Euphorbiaceae): Identification of Valid Biomarkers
Bibliographic record
Abstract
The fruit extract of Emblica officinalis Gaertn. (Euphorbiaceae), commonly known in India as amla (Indian gooseberry), has been popularized as a dietary supplement in the United States and elsewhere, with its antioxidant benefits being attributed to a high content of ascorbic acid. The presence of ascorbic acid in the extract was questioned by earlier researchers, and hydrolysable tannins, emblicanins A and B were identified [1] and structurally defined [2]. Our investigations on the emblicanins and ascorbic acid content of the fruit juice and extract, however revealed that ascorbic acid co-elutes with other compounds of similar spectral behavior. Additionally, the hydrolysable tannins, when evaluated were found to be structurally different from the previously reported structures. The earlier reported antioxidant hydrolysable tannins, emblicanins A and B, correspond to beta-glucogallin (1) and mucic acid 1,4-lactone 5-O-gallate (2), respectively. Only trace amounts of free ascorbic acid were detected. β-glucogallin is therefore a more relevant and optimal biomarker in Emblica officinalis extract, than ascorbic acid. References: [1] Ghosal S, et al. (1996) Indian J Chem 35B: 941–948. [2] Pozharitskava ON, et al. (2007) J Sep Sci 30: 1250–1254.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".