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  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
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  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
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Untargeted Metabolomics Pilot Study Using UHPLC-qTOF MS Profile in Sows’ Urine Reveals Metabolites of Bladder Inflammation

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Autor
Pousinis P., Virgiliou C., Mouskeftara T., Chalvatzi S., Kroustallas F., Panteris E., Papadopoulos G.A., Fortomaris P., Cernat M., Leontides L., Begou O.
Datum
2022
Language
en
DOI
10.3390/metabo12121186
Schlagwort
1 methylguanosine
3 methyloxyindole
4 hydroxybenzoic acid
adenosine
amino acid
caffeic acid
carboxylic acid
cytosine
daidzein
genistein
glycylproline
guanosine
guanosine derivative
indole derivative
n2 methylguanosine
phenylalanine
piscidic acid
salicylaldehyde
tryptophanol
unclassified drug
xanthosine
amino acid metabolism
Article
controlled study
cystitis
diagnostic accuracy
diagnostic test accuracy study
female
liquid chromatography-mass spectrometry
metabolomics
nonhuman
predictive model
predictive value
quadrupole mass spectrometry
receiver operating characteristic
sow (swine)
swine disease
time of flight mass spectrometry
ultra performance liquid chromatography
urinalysis
urinary tract infection
urine sampling
MDPI
Zur Langanzeige
Zusammenfassung
Urinary tract infections (UTI) of sows (characterized by ascending infections of the urinary bladder (cyst), ureters, and renal pelvis), are major health issues with a significant economic impact to the swine industry. The current detection of UTI incidents lacks sensitivity; thus, UTIs remain largely under-diagnosed. The value of metabolomics in unraveling the mechanisms of sow UTI has not yet been established. This study aims to investigate the urine metabolome of sows for UTI biomarkers. Urine samples were collected from 58 culled sows from a farrow-to-finish herd in Greece. Urine metabolomic profiles in 31 healthy controls and in 27 inflammatory ones were evaluated. UHPLC-qTOF MS/MS was applied for the analysis with a combination of multivariate and univariate statistical analysis. Eighteen potential markers were found. The changes in several urine metabolites classes (nucleosides, indoles, isoflavones, and dipeptides), as well as amino-acids allowed for an adequate discrimination between the study groups. Identified metabolites were involved in purine metabolism; phenylalanine; tyrosine and tryptophan biosynthesis; and phenylalanine metabolism. Through ROC analysis it was shown that the 18 identified metabolite biomarkers exhibited good predictive accuracy. In summary, our study provided new information on the potential targets for predicting early and accurate diagnosis of UTI. Further, this information also sheds light on how it could be applied in live animals. © 2022 by the authors.
URI
http://hdl.handle.net/11615/78354
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19743]
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