Fractionation of Gallotannins from Mango (<i>Mangifera indica</i>L.) Kernels by High-Speed Counter-Current Chromatography and Determination of Their Antibacterial Activity
Bibliographic record
Abstract
High-speed counter-current chromatography was applied to the separation of gallotannins from mango (Mangifera indica L.) kernels. The kernels were defatted and subsequently extracted with aqueous acetone [80% (v/v)]. The crude extract was purified by being partitioned against ethyl acetate. A hexane/ethyl acetate/methanol/water solvent system [0.5:5:1:5 (v/v/v/v)] was used in the head-to-tail mode to elute tannins according to their degree of galloylation (tetra-O-galloylglucose to deca-O-galloylglucose). The compounds were characterized using liquid chromatography and mass spectrometry in the negative ionization mode. Purities ranged from 72% (tetra-O-galloylglucose) to 100% (octa-O-galloylglucose). The iron binding capacity of gallotannins was dependent on the number of galloyl groups in the molecule, with a larger capacity at lower degrees of galloylation. The minimum inhibitory concentration against Bacillus subtilis did not change among the different gallotannins tested and was in the range of 0.05-0.1 g/L in Luria-Bertani broth but up to 20 times higher in media containing more iron and divalent cations.
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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) | 0.001 | 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 | 0.000 | 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".