Interaction of β-Lactoglobulin with Resveratrol and its Biological Implications
Bibliographic record
Abstract
Beta-lactoglobulin (beta-LG), the major whey protein in the milk of ruminants, has a high affinity for a wide range of compounds. Resveratrol (3,5,4'-trihydroxystilbene), a natural polyphenolic compound found in grapes and red wine, exhibits many physiological effects associated with health benefits. In this study, the interaction of resveratrol with beta-LG was investigated using circular dichroism, fluorescence and UV-vis absorbance. Self-association of resveratrol possibly occurs at high concentrations. Resveratrol interacts with beta-LG to form 1:1 complexes. Resveratrol is bound to the surface of the protein because beta-LG-bound polyphenol is in a weaker hydrophobic environment relative to 75% ethanol. The binding constant for the resveratrol-beta-LG interaction is between 10(4) and 10(6) M (-1), as determined by protein or polyphenol fluorescence. The beta-LG-resveratrol interaction may compete with self-association of both the polyphenol and the protein. It has no apparent influence on beta-LG secondary structure but partially disrupts tertiary structure. Complexing with beta-LG provides a slight increase in the photostability of resveratrol and a significant increase in its hydrosolubility.
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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 | 0.001 | 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".