Selective Removal of Phenylalanine Impurities from Commercial κ-Casein Glycomacropeptide by Anion Exchange Chromatography
Bibliographic record
Abstract
Bovine κ-casein glycomacropeptide (GMP) found in sweet whey is a 64 amino acid residue phosphorylated glycopeptide. Because it lacks aromatic amino acids including phenylalanine, GMP is thought to be an important dietary source of amino acids for patients suffering from phenylketonuria. There is, however, very little information available concerning preparation of phenylalanine-free GMP for human consumption. This study was, therefore, undertaken to remove phenylalanine containing impurities from commercially available crude GMP by anion exchange chromatography on diethylaminoethyl (DEAE)-Sephacel. The results demonstrated that phenylalanine containing proteins or peptides do not bind to the column, while most GMP accounting for 93% of total recovered sialic acid can bind to the column. The purified GMP, which accounted for average 43% of dry weight of crude GMP, contained undetectable level of phenylalanine. Analyses and cellulose acetate electrophoresis showed that the purified GMP is a product with high sialic acid content (average 15.5% dry weight). Gel filtration chromatography on Sephacryl S-100 and size exclusion HPLC on Superdex 75 confirmed our previous findings that GMP monomers form aggregates and elute as a single peak with its elution volume close to the elution volume of dimeric β-lactoglobulin (36.6 kDa). It was concluded that the crude preparation of GMP can be highly refined by selectively removing phenylalanine impurities using DEAE-Sephacel chromatography.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".