Effect of calcium on fatty acid bioaccessibility during in vitro digestion of Cheddar-type cheeses prepared with different milk fat fractions
Bibliographic record
Abstract
Calcium plays an important role in intestinal lipid digestion by increasing the lipolysis rate, but also limits fatty acid bioaccessibility by producing insoluble Ca soaps with long-chain fatty acids at intestinal pH conditions. The aim of this study was to better understand the effect of Ca on the bioaccessibility of milk fat from Cheddar-type cheeses. Three anhydrous milk fats (AMF) with different fatty acid profiles (olein, stearin, or control AMF) were used to prepare Cheddar-type cheeses, which were then enriched or not with Ca using CaCl 2 during the salting step. The cheeses were digested in vitro, and their disintegration and lipolysis rates were monitored during the process. At the end of digestion, lipids were extracted under neutral and acidic pH conditions to compare free fatty acids under intestinal conditions in relation to total fatty acids released during the digestion process. The cheeses prepared with the stearin (the AMF with the highest ratio of long-chain fatty acids) were more resistant to disintegration than the other cheeses, owing to the high melting temperature of that AMF. The Ca-enriched cheeses had faster lipolysis rates than the regular Ca cheeses. Chromatographic analysis of the digestion products showed that Ca interacted with long-chain fatty acids, producing Ca soaps, whereas no interaction with shorter fatty acids was detected. Although higher Ca levels resulted in faster lipolysis rates, driven by the depletion of reaction products as Ca soaps, such insoluble compounds are expected to reduce the bioavailability of fatty acids by hindering their absorption. These effects on lipid digestion and absorption are of interest for the design of food matrices for the controlled release of fat-soluble nutrients or bioactive molecules.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".