Effect of simulated gastrointestinal digestion on antioxidant, and anti-inflammatory activities of bioactive peptides generated in sausages fermented with <i>Staphylococcus simulans</i> QB7
Bibliographic record
Abstract
Dry-fermented sausages are a good source of bioactive peptides, whose stability against gastrointestinal (GI) digestion determines their bioaccessibility. This study focused on evaluating the effect of peptide extracts from sausages fermented with Staphylococcus simulans QB7 during in vitro simulated GI digestion, including peptide profiles and antioxidant and anti-inflammatory activities. Peptides present in sausages were degraded during digestion, with molecular weight reduced from > 12 kDa to < 1.5 kDa. Besides, the content of amino acids increased from 381.15 to 527.07 mg/g, especially tyrosine being found only after GI digestion. The anti-inflammatory activities were increased after GI digestion, however, the changes in antioxidant activities were the opposite. A total number of 255, 252 and 386 peptide sequences were identified in undigested, peptic-digested and GI-digested samples, respectively. PeptideRanker, BIOPEP-UWM and admetSAR were used to further predict the functional properties and intestinal absorption of the identified peptide sequences from GI digestion. Finally, 18 peptides were discovered to possess either antioxidant or anti-inflammatory capacities.
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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".