High hydrostatic pressure enhances whey protein digestibility to generate whey peptides that improve glutathione status in CFTR‐deficient lung epithelial cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Whey protein isolates (WPI) may provide anti-inflammatory benefits to cystic fibrosis (CF), which could be mediated via peptides, as proteolytic digests of WPI enhance intracellular glutathione (GSH) concentrations. The objectives of this study were to investigate whether high hydrostatic pressure can (i) improve the in vitro digestibility of WPI; and (ii) generate low molecular weight (< 1 kDa) peptides from WPI hydrolysates that exert GSH-enhancing and anti-inflammatory properties in wild type and mutant CF transmembrane conductance regulator (CFTR) tracheal epithelial cells. Hydrostatic pressure processing enhanced the in vitro digestibility of WPI to proteolytic enzymes resulting in altered peptide profiles as assessed by CZE and GC-MS. The exposure of mutant CFTR cells to low molecular weight (< 1 kDa) peptides isolated from WPI hydrolysates exposed to pressure processing (pressurized WPI hydrolysates, pWPH), showed increased intracellular levels of reduced GSH and total GSH relative to treatment with peptides obtained from native WPI hydrolysates (nWPH). A tendency for decreased interleukin-8 secretion was associated with the pWPH and nWPH treatments in mutant CFTR cells, which was not observed in wild type cells. Hydrostatic pressure processing of whey proteins appears to enhance their impact on cellular GSH status in cells with the mutant CFTR condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it