High Hydrostatic Pressure Pretreatment of Whey Protein Isolates Improves Their Digestibility and Antioxidant Capacity
Bibliographic record
Abstract
Whey proteins have well-established antioxidant and anti-inflammatory bioactivities. High hydrostatic pressure processing of whey protein isolates increases their in vitro digestibility resulting in enhanced antioxidant and anti-inflammatory effects. This study compared the effects of different digestion protocols on the digestibility of pressurized (pWPI) and native (nWPI) whey protein isolates and the antioxidant and anti-inflammatory properties of the hydrolysates. The pepsin-pancreatin digestion protocol was modified to better simulate human digestion by adjusting temperature and pH conditions, incubation times, enzymes utilized, enzyme-to-substrate ratio and ultrafiltration membrane molecular weight cut-off. pWPI showed a significantly greater proteolysis rate and rate of peptide appearance regardless of digestion protocol. Both digestion methods generated a greater relative abundance of eluting peptides and the appearance of new peptide peaks in association with pWPI digestion in comparison to nWPI hydrolysates. Hydrolysates of pWPI from both digestion conditions showed enhanced ferric-reducing antioxidant power relative to nWPI hydrolysates. Likewise, pWPI hydrolysates from both digestion protocols showed similar enhanced antioxidant and anti-inflammatory effects in a respiratory epithelial cell line as compared to nWPI hydrolysates. These findings indicate that regardless of considerable variations of in vitro digestion protocols, pressurization of WPI leads to more efficient digestion that improves its antioxidant and anti-inflammatory properties.
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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".