Production of Demineralized Antibacterial, Antifungal and Antioxidant Peptides from Bovine Hemoglobin Using an Optimized Multiple-Step System: Electrodialysis with Bipolar Membrane
Bibliographic record
Abstract
Numerous studies have shown that bovine hemoglobin, a protein from slaughterhouse waste, has important biological potential after conventional enzymatic hydrolysis. However, the active peptides could not be considered pure since they contained mineral salts. Therefore, an optimized multi-step process of electrodialysis with bipolar membranes (EDBM) was carried out to produce discolored and demineralized peptides without the addition of chemical agents. The aim of this study was to test the antibacterial, antifungal and antioxidant activities of discolored and demineralized bovine hemoglobin hydrolysates recovered by EDBM and to compare them with raw and discolored hydrolysates derived from conventional hydrolysis. The results demonstrate that discolored–demineralized hydrolysates recovered from EDBM had significant antimicrobial activity against many bacterial (gram-positive and gram-negative) and fungal (molds and yeast) strains. Concerning antibacterial activity, lower MIC values for hydrolysates were registered against Staphylococcus aureus, Kocuria rhizophila and Listeria monocytogenes. For antifungal activity, lower MIC values for hydrolysates were registered against Paecilomyces spp., Rhodotorula mucilaginosa and Mucor racemosus. Hemoglobin hydrolysates showed fungicidal mechanisms towards these fungal strains since the MFC/MIC ratio was ≤4. The hydrolysates also showed a potent antioxidant effect in four different antioxidant tests. Consequently, they can be considered promising natural, low-salt food preservatives. To the best of our knowledge, no previous studies have identified the biological properties of discolored and demineralized bovine hemoglobin hydrolysates.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".