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Nanoscale ; 13(31): 13353-13367, 2021 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-34477741


Despite the significance of surface absorbed proteins in determining the biological identity of nanoparticles (NPs) entering the human body, little is known about the surface corona and factors that shape their formation on dietary particles used as food additives. In this study, food grade NPs of silica and titania and their food additive counterparts (E551 and E171) were interacted with milk proteins or with skimmed milk and the levels of protein adsorption were quantified. Characteristics of proteins correlating with their level of adsorption to NPs were determined using partial least squares regression analysis. Results from individual protein-particle interactions revealed the significance of factors such as zeta potential, hydrophobicity and hydrodynamic size of particles, and protein characteristics such as the number of beta strands, isoelectric points, the number of amino acid units (Ile, Tyr, Ala, Gly, Pro, Asp, and Arg), and phosphorylation sites on their adsorption to particles. Similar regression analysis was performed to identify the characteristics of twenty abundant and enriched proteins (identified using LC-MS/MS analysis) for their association with the surface corona of milk-interacted particles. Contrary to individual protein-particle interactions, protein characteristics such as helices, turns, protein structures, disulfide bonds, the number of amino acid units (Cys, Met, Leu, and Trp), and Fe binding sites were significant for their association with the surface corona of milk interacted particles. This difference in factors identified from individual proteins and milk interacted particles suggested possible interactions of proteins with surface adsorbed biomolecules as revealed by scanning transmission X-ray microscopy and other biochemical assays.

Nanopartículas , Coroa de Proteína , Adsorção , Sequência de Aminoácidos , Cromatografia Líquida , Humanos , Proteoma , Espectrometria de Massas em Tandem
Foods ; 10(2)2021 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-33670588


Animal welfare status is assessed today through visual evaluations requiring an on-farm visit. A convenient alternative would be to detect cow welfare status directly in milk samples, already routinely collected for milk recording. The objective of this study was to propose a novel approach to demonstrate that Fourier transform infrared (FTIR) spectroscopy can detect changes in milk composition related to cows subjected to movement restriction at the tie stall with four tie-rail configurations varying in height and position (TR1, TR2, TR3 and TR4). Milk mid-infrared spectra were collected on weekly basis. Long-term average spectra were calculated for each cow using spectra collected in weeks 8-10 of treatment. Principal component analysis was applied to spectral averages and the scores of principal components (PCs) were tested for treatment effect by mixed modelling. PC7 revealed a significant treatment effect (p = 0.01), particularly for TR3 (configuration with restricted movement) vs. TR1 (recommended configuration) (p = 0.03). The loading spectrum of PC7 revealed high loadings at wavenumbers that could be assigned to biomarkers related to negative energy balance, such as ß-hydroxybutyrate, citrate and acetone. This observation suggests that TR3 might have been restrictive for cows to access feed. Milk FTIR spectroscopy showed promising results in detecting welfare status and housing conditions in dairy cows.