Enhanced antihypertensive chicken by-product hydrolysate fraction after its separation by electrodialysis with ultrafiltration membrane (EDUF)
Bibliographic record
Abstract
• Valorization of a hydrolysate of chicken by-products by electromembrane process. • 39 peptides recovered amongst 164 in the positively charged peptide (PCC) fraction. • 6 bioactive peptides identified in PCC and 1 in negatively charged peptide (NCC) fraction. • PCC fraction showed the highest ACE inhibition. The environmental impact of poultry industry waste has led to the study of hydrolysates with potential health-promoting properties obtained from poultry by-products and their fractionation to increase the bioactivity of these hydrolysates. The aim of the present study was to separate a chicken by-product hydrolysate (CBH) by electrodialysis with ultrafiltration membranes (EDUF), providing peptide selective separation based on their charge and molecular weight, and to characterize the resulting fractions. Experimental results showed that during the peptide fractionation process the global peptide migration rate (MR) from CBH was 14.97 ± 0.14 g/m 2 •h with a relative energy consumption of 31.27 ± 2.61 Wh/g of total peptides. 164 peptides were identified in the initial CBH, and following EDUF, 39 migrated to the positively charged peptide fraction (PCC) and 9 to the negatively charge peptide fraction (NCC): 21 sequences were reported as bioactive for CBH, 6 for PCC and 1 for NCC. Analyses of ACE inhibition evidenced a 1.4 fold increase in antihypertensive activity of the PCC (IC 50 0.46 ± 0.04 mg peptides /mL) in comparison to CBH (IC 50 0.65 ± 0. 04 mg peptides /mL), despite the smaller number of bioactive sequences reported and the fact that it is possible to enhance the PCC recovery by modifying the EDUF configuration in further studies. These findings highlight the significance of EDUF as a sustainable method for obtaining specifically charged peptide fractions with enhanced bioactivity from the initial hydrolysate.
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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".