Oxylipin concentration, but not fatty acid composition, is altered in human donor milk pasteurised using both thermal and non-thermal techniques
Bibliographic record
Abstract
Human donor milk (DM) is Holder pasteurised (62·5°C, 30 min) to ensure its microbiological safety for infant consumption. In low-resource settings, flash heating is used to pasteurise milk. Although there is considerable interest in non-thermal alternatives (high hydrostatic pressure processing (HHP) and UVC irradiation) for pasteurisation, their effect on the fatty acid composition is not well understood. Of particular interest is the effect of pasteurisation on the generation of oxylipins. DM from eight mothers containing bacteria >5 × 107 colony-forming units/l was used. In a paired design, each pool of milk underwent four pasteurisation techniques: Holder; flash heating; UVC (250 nm, 25 min) and HHP (500 MPa, 8 min). Fatty acids were quantified by GC-flame ionisation detection and oxylipins derived from arachidonic acid; 18-carbon PUFA (α-linolenic acid, linoleic acid and γ-linolenic acid) and EPA/DHA were measured by liquid chromatography-tandem MS in aliquots of raw and processed milk. There were no significant changes to the composition of fatty acids following all pasteurisation techniques compared with raw milk. The n-6:n-3 ratio remained constant ranging from 6·4 to 6·6. Several arachidonic acid-derived oxylipins were highest post-UVC and elevated post-HHP compared with raw milk. Several oxylipins derived from 18-carbon PUFA (linoleic and α-linolenic acids) were elevated in UVC-treated milk. EPA/DHA-derived oxylipins were on average, unaffected by pasteurisation. Although some PUFA-derived oxylipins were increased following UVC and HHP, no method affected the fatty acid composition of human DM. Further research is needed to determine if varying levels of oxylipins in human DM as a result of processing can potentially mediate cellular signalling; proliferation and apoptosis, especially important for preterm infant development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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".