Casein and Cheese Peptide Degradation by<i>Enterococcus durans</i>FC12 Isolated from Feta Cheese
Bibliographic record
Abstract
The growth of Enterococcus durans FC12 isolated from Feta cheese in broths containing casein, casein hydrolysate or cheese water-soluble extract as sole nitrogen source was studied. FC12 assimilated casein hydrolysate and casein, the former at a higher extent, while it also grew in the presence of 4% NaCl. It assimilated at a similar extent cow, ewe or goat casein, and it grew rapidly using cheese soluble nitrogenous materials. The cell-envelope enzyme preparation of E. durans FC12 hydrolysed both α-casein and β-caseins, the latter more rapidly, producing three main peptides. It also hydrolysed two peptides analog to the cheese peptide αs1-CNf1-23 that is a key peptide in the first steps of cheese proteolysis. FC12 cell-envelope enzyme preparation degraded the above caseins and peptides in the presence of 4% NaCl. The ability of E. durans FC12 to assimilate casein and cheese soluble nitrogenous materials along with the ability of its cell-envelope enzyme preparation to hydrolyse caseins and peptides analog to the αs1-CNf1-23 indicates that the FC12 strain may be useful in cheese proteolysis as an adjunct culture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".