Assessment of Bioavailability after In Vitro Digestion and First Pass Metabolism of Bioactive Peptides from Collagen Hydrolysates
Bibliographic record
Abstract
Collagen hydrolysates (CHs) are composed of bioactive peptides (BAPs), which possess health enhancing properties. There is a knowledge gap regarding the bioavailability of these BAPs that involves intestinal transport and hepatic first pass effects. A simulated gastrointestinal model was used to generate digesta from two CHs (CH-GL and CH-OPT), which were applied to a novel transwell co-culture of human intestinal epithelium cell line-6 (HIEC-6) and hepatic (HepG2) cells to simulate in vivo conditions of absorption and first pass metabolism. Peptide transport, hepatic first pass effects, and bioavailability were determined by measuring BAPs (Gly-Pro, Hyp-Gly, Ala-Hyp, Pro-Hyp, Gly-Pro-Hyp) using an innovative capillary electrophoresis method. All peptides were transported across the intestinal cell layer to varying degrees with both CHs; however, Gly-Pro-Hyp was transported only with CH-GL, but not CH-OPT. Notable hepatic production was observed for Ala-Hyp with both CH treatments, and for Pro-Hyp and Gly-Pro with CH-GL only. All peptides were bioavailable (>10%), except for Gly-Pro-Hyp after CH-OPT. Overall, a high degree of transport and hepatic first pass effects on CH-derived BAPs were observed. Further research is needed to explore the hepatic mechanisms related to the production of BAPs and the bifunctional effects of the bioavailable BAPs noted in this study.
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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 | 0.001 |
| 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".