Epigallocatechin-3-gallate enhances sterilization of irradiated whole bovine casein and protects alpha and beta caseins from gamma radiation: depending on polyphenol/protein ratio
Bibliographic record
Abstract
The increasing use of milk proteins in medicine requires the development of effective processes for sterilization of milk formulations. We found that epigallocatechin-3-gallate (EGCG) was able to reduce bacterial flora in total casein, depending on the concentration of EGCG. Furthermore, the combination of EGCG and gamma radiation reduced the dose D10 to 0.88 kGy and 0.63 kGy with 250 and 500 µM EGCG, respectively, instead 2.01 kGy without EGCG. We also examined the effect of gamma radiation on alpha- and beta-casein in the absence and presence of epigallocatechin-3-gallate (EGCG). Milk proteins in solution were exposed to different doses of gamma radiation with and without EGCG. Unirradiated and irradiated samples were analyzed by SDS-PAGE and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-MS). Our results suggest that EGCG (10 µM) protects α- and β-casein from degradation and subsequent polymerization, possibly by scavenging oxygen and protein free radicals generated during irradiation. Although we used a ratio of polyphenols to protein that was higher for alpha-casein (1/5) than beta-casein (1/10), beta-casein was better protected with EGCG. According to previous studies, this result could be explained by differences in protein primary structure and its interaction with EGCG. The interaction of EGCG with casein is hydrophobic rather than hydrophilic, so the interaction with β-casein is stronger than with α-casein. In conclusion, we found that low EGCG concentrations enhances the sterilization of total casein by gamma radiation and it provided an excellent radioprotection of α- and β-casein, especially β-casein, against degradation and aggregation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".