Assessment of protein and phospholipid bioaccessibility in ultrafiltered buttermilk cheese using TIM-1 in vitro gastrointestinal methods
Bibliographic record
Abstract
To meet the high consumer demand, butter production has increased over the last few years. As a result, the buttermilk (BM) co-produced volumes require new ways of adding value, such as in cheese manufacturing. However, BM use in cheese milk negatively influences the cheesemaking process (e.g., altered coagulation properties) and the product's final quality (e.g., high moisture content). The concentration of BM by ultrafiltration (UF) could potentially facilitate its use in cheese manufacturing through an increased protein content while maintaining the milk salt balance. Simultaneously, little is known about the digestion of UF BM cheese. Therefore, this study aimed to characterize the impact of UF BM on cheese manufacture, its structure, and its behavior during in vitro digestion. A 2-fold UF concentrated BM was used for cheese manufacture (skim milk [SM] - control). Compositional, textural, and microstructural analyses of cheeses were first conducted. In a second step, the cheeses were fed into an in vitro TNO gastrointestinal digestion model (TIM-1) of the stomach and small intestine and protein and phospholipid (PL) bioaccessibility was studied. The results showed that UF BM cheese significantly differed from SM cheese regarding its composition, hardness (p < 0.05) and microstructure. However, in TIM-1, UF BM and SM cheeses showed similar digestion behavior as a percentage of protein and PL intake. Despite relatively more non-digested and non-absorbed PL in the ileum efflux of UF BM cheese, the initially higher PL concentration contributes to an enhanced nutritional value compared to SM cheese. To our knowledge, this study is the first to compare the bioaccessibility of proteins and PL from UF BM and SM cheeses.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".