High hydrostatic pressure pre-treatment of whey proteins enhances whey protein hydrolysate inhibition of oxidative stress and IL-8 secretion in intestinal epithelial cells
Bibliographic record
Abstract
BACKGROUND: High hyperbaric pressure treatment of whey protein isolate (WPI) causes changes in the protein structure that enhances the anti-oxidant and anti-inflammatory effects of WPI. OBJECTIVE: The aim of this study was to compare the anti-oxidant and anti-inflammatory effects of pressurized whey protein isolate (pWPI) vs. native WPI (nWPI) hydrolysates in Caco-2 cells exposed to hydrogen peroxide (H(2)O(2)). DESIGN: Cells were cultured with different concentrations of pWPI or nWPI hydrolysates either 1 h before or 1 h after H(2)O(2). Cell viability, IL-8 secretion, intracellular reactive oxygen species (ROS), and the medium anti-oxidant capacity (FRAP assay) were measured. RESULTS: Prior to and after H(2)O(2) exposure, pWPI and nWPI hydrolysates inhibited IL-8 secretion and ROS generation, and increased FRAP activity in a dose-dependent manner. The maximal inhibition of H(2)O(2)-induced IL-8 secretion was greater with 2000 µg mL(-1) of pWPI (50%) vs. nWPI (30%) hydrolysates. At the latter concentration, inhibition of H(2)O(2)-induced ROS formation reached 76% for pWPI, which was greater than for nWPI hydrolysates (32.5%). CONCLUSIONS: These results suggest that WPI hydrolysates can alleviate inflammation and oxidative stress in intestinal cells exposed to oxidative injury, which is further enhanced by hyperbaric pressure pre-treatment of WPI.
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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".