Inhibitory Effects of Hydrolyzed Oat Bran Proteins on Human LDL Oxidation and Their Bile Acid Binding Capacity
Bibliographic record
Abstract
Free radicals attack to biological molecules can initiate their oxidation and contribute to the development of several chronic diseases.Oxidation of low density lipoprotein, as well as a higher concentration of cholesterol, have been implicated in the development of atherosclerotic lesions and increased risks of cardiovascular diseases.Strategies to decrease the risks then include scavenging of free radicals and the reduction of cholesterol (e.g.binding of bile acids).In this regard, the aim of this project was; 1) to produce and characterize various hydrolyzed proteins from oat brans; 2) determine their antioxidant, metal binding and bile chelating capacities as well as their ability to inhibit low density lipoprotein oxidation (LDL).Medium oat bran samples were treated with two cell wall polysaccharide degrading enzymes (cellulase and viscozyme) to generate two protein isolates named CPI and VPI respectively.Ten hydrolysates were subsequently prepared by treating CPI or VPI with five proteases protamex, alcalase, flavourzyme, pepsin and pepsin+pancreatin.The two highest degrees of hydrolysis (26.4 ± 0.5 and 22.0 ± 0.1%) were obtained under simulated gastrointestinal digestion with pepsin and pancreatin.Intrinsic absorbance showed that CPI-alcalase and CPI-pepsin/pancreatin had a higher content of aromatic amino acids.In the antioxidant oxidant assays, VPI-pepsin better scavenged ROO • radicals (496.77±5.83μM Trolox Equivalents (TE)/g) while VPI-flavourzyme and VPI-pepsin had better quenching for HO • (27.95 ±1.580 and and O2 •-(45.31±6.6%)radicals, respectively.In the metal
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.
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".