Current insights into cow's milk allergy in children: Microbiome, metabolome, and immune response-A systematic review.

The increasing prevalence of IgE-mediated cow's milk allergy (CMA) in childhood is a worldwide health concern. There is a growing awareness that the gut microbiome (GM) might play an important role in CMA development. Therefore, treatment with probiotics and prebiotics has gained popularity. This systematic review provides an overview of the alterations of the GM, metabolome, and immune response in CMA children and animal models, including post-treatment modifications. MEDLINE, PubMed, Scopus, and Web of Science were searched for studies on GM in CMA-diagnosed children, published before 1 March 2023. A total of 21 articles (13 on children and 8 on animal models) were included. The studies suggest that the GM, characterized by an enrichment of the Clostridia class and reductions in the Lactobacillales order and Bifidobacterium genus, is associated with CMA in early life. Additionally, reduced levels of short-chain fatty acids (SCFAs) and altered amino acid metabolism were reported in CMA children. Commonly used probiotic strains belong to the Bifidobacterium and Lactobacillus genera. However, only Bifidobacterium levels were consistently upregulated after the intervention, while alterations of other bacteria taxa remain inconclusive. These interventions appear to contribute to the restoration of SCFAs and amino acid metabolism balance. Mouse models indicate that these interventions tend to restore the Th 2/Th 1 balance, increase the Treg response, and/or silence the overall pro- and anti-inflammatory cytokine response. Overall, this systematic review highlights the need for multi-omics-related research in CMA children to gain a mechanistic understanding of this disease and to develop effective treatments and preventive strategies.

Improving retention-time prediction in supercritical-fluid chromatography by multivariate modelling.

The prediction of chromatographic retention under supercritical-fluid chromatography (SFC) conditions was studied, using established and novel theoretical models over ranges of modifier content, pressure and temperature. Whereas retention models used for liquid chromatography often only consider the modifier fraction, retention in SFC depends much more strongly on pressure and temperature. The viability of combining several retention models into surfaces that describe the effects of both modifier fraction and pressure was investigated. The ability of commonly used retention models to describe retention as a function of modifier fraction, expressed either as mass or volume fraction, pressure and density was assessed. Using the multivariate surfaces, retention-time prediction for isocratic separations at constant temperature improved significantly compared to univariate modelling when both pressure and modifier fractions were changed. The "mixed-mode" model with an additional exponential pressure or density parameter was able to predict retention times within 5%, with the majority of the predictions within 2%. The use of mass fraction and density further improves retention modelling compared to volume fraction and pressure. These variables however, do require extra computations.