2 research outputs found
Rapid Differentiation of Commercial Juices and Blends by Using Sugar Profiles Obtained by Capillary Zone Electrophoresis with Indirect UV Detection
A method for the
determination of sugars in several fruit juices
and nectars by capillary zone electrophoresis with indirect UVāvis
detection has been developed. Under optimal conditions, commercial
fruit juices and nectars from several fruits were analyzed, and the
sugar and cyclamate contents were quantified in less than 6 min. A
study for the detection of blends of high-value juices (orange and
pineapple) with cheaper alternatives was also developed. For this
purpose, different chemometric techniques, based on sugar content
ratios, were applied. Linear discriminant analysis showed that fruit
juices can be distinguished according to the fruit type, juice blends
also being differentiated. Multiple linear regression models were
also constructed to predict the adulteration of orange and pineapple
juices with grape juice. This simple and reliable methodology provides
a rapid analysis of fruit juices of economic importance, which is
relevant for quality control purposes in food industries and regulatory
agencies
New In-Depth Analytical Approach of the Porcine Seminal Plasma Proteome Reveals Potential Fertility Biomarkers
A complete characterization of the
proteome of seminal plasma (SP)
is an essential step to understand how SP influences sperm function
and fertility after artificial insemination (AI). The purpose of this
study was to identify which among characterized proteins in boar SP
were differently expressed among AI boars with significantly different
fertility outcomes. A total of 872 SP proteins, 390 of them belonging
specifically to <i>Sus Scrofa</i> taxonomy, were identified
(Experiment 1) by using a novel proteomic approach that combined size
exclusion chromatography and solid-phase extraction as prefractionation
steps prior to Nano LCāESIāMS/MS analysis. The SP proteomes
of 26 boars showing significant differences in farrowing rate (<i>n</i> = 13) and litter size (<i>n</i> = 13) after
the AI of 10āÆ526 sows were further analyzed (Experiment 2).
A total of 679 SP proteins were then quantified by the SWATH approach,
where the penalized linear regression LASSO revealed differentially
expressed SP proteins for farrowing rate (FURIN, AKR1B1, UBA1, PIN1,
SPAM1, BLMH, SMPDL3A, KRT17, KRT10, TTC23, and AGT) and litter size
(PN-1, THBS1, DSC1, and CAT). This study extended our knowledge of
the SP proteome and revealed some SP proteins as potential biomarkers
of fertility in AI boars