Back

Effects of pasteurization on osteopontin levels in human breastmilk and pasteurized breastmilk products

McClanahan, K. G.; Reese, J.; Weitkemp, J.-H.; Olivares-Villagomez, D.

2023-02-26 physiology
10.1101/2023.02.24.529945 bioRxiv
Show abstract

BackgroundOsteopontin (OPN) is an important breastmilk protein involved in infant intestinal, immunological, and brain development. However, little is known about how common milk pasteurization and storage techniques affect this important bioactive protein. MethodsHuman milk osteopontin concentration was measured in single-donor fresh or frozen breastmilk, pooled Holder-pasteurized donor breastmilk, and a shelf-stable (retort pasteurized) breastmilk product by ELISA. Breastmilk samples were pasteurized and/or frozen before measuring osteopontin concentrations. ResultsHolder pasteurization of breastmilk resulted in an [~]50% decrease in osteopontin levels within single-donor samples, whereas pooled donor breastmilk had comparable osteopontin levels to non-pasteurized single-donor samples. Breastmilk from mothers of preterm infants trended toward higher osteopontin concentration than mothers of term infants; however, samples from preterm mothers experienced greater osteopontin degradation upon pasteurization. Finally, freezing breastmilk prior to Holder pasteurization resulted in less osteopontin degradation than Holder pasteurization prior to freezing. ConclusionCommonly used breastmilk pasteurization and storage techniques, including freezing, Holder and retort pasteurization, decrease the levels of the bioactive protein osteopontin in human breastmilk. ImpactO_LIPasteurization of human breastmilk significantly decreases the levels of the bioactive protein osteopontin C_LIO_LIUse of both pasteurization and freezing techniques for breastmilk preservation results in greater loss of osteopontin C_LIO_LIThis study presents for the first time an analysis of osteopontin levels in single-donor pasteurized milk samples C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.