Removing Cross-Linked Telopeptides Enhances the Production of Low-Molecular-Weight Collagen Peptides from Spent Hens
Bibliographic record
Abstract
The low-molecular-weight (LMW) peptides derived from collagen have shown a potential for various nutritional and pharmaceutical applications. However, production of LMW peptides from vertebrate collagen remains a challenge. Herein, we report a new method to produce LMW collagen peptides using pepsin pretreatment that removed cross-linked telopeptides in collagen molecules. After the pretreatment, the proportion of LMW collagen peptides (<1.4 kDa) that were obtained from pepsin-soluble collagen increased to 32.59% compared to heat-soluble collagen peptides (16.10%). Fourier transform infrared spectroscopy results indicated that telopeptide cleavage retained the triple-helical conformation of collagen. Liquid chromatography-tandem mass spectrometry analysis suggested that Gly-X-Y (X is often proline, while Y is either hydroxyproline or hydroxylysine) repeats were not the main factors that hindered the enzymatic hydrolysis of collagen molecules. However, cross-link quantification demonstrated that trivalent cross-links that included pyridinolines and pyrroles were the primary obstacles to producing small peptides from collagen of spent hens. This study demonstrated for the first time that removing cross-linked telopeptides could enhance the production of LMW peptides from spent hen collagen, which is also of interest to manufacturers who produce LMW collagen peptides from other vertebrate animals, such as bovids and porcids.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".