40 research outputs found
A simple High Performance Liquid Chromatography-Mass spectrometry approach combined with Linear Discriminant Analysis for the characterization of top quality olive oils
No full textA Novel Liquid Chromatography/Mass Spectrometry Method for Analysis of Plasma Sterol Concentrations
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AN HPLC/APCI METHOD, USING PARTLY MISCIBLE SOLVENTS, FOR A SIMPLE SEPARATION AND DETERMINATION OF STEROLS IN BLOOD
No full textStudies in organic mass spectrometry. Part 27. Electron ionisation induced isomerisation of 3-aryl-4(3H)-quinazolinones
No full textThe comparison between 70 eV EI (electron ionisation) mass spectra, MIKE (mass analysed ion kinetic energy) and CID (collision induced dissociation) MIKE spectra, KER (kinetic energy release) and KERD (kinetic energy release distribution) data for 2-methyl-3-aryl-4(3H)-quinazolinones 1-4, with those of the corresponding 2-methyl-4-aryloxyquinazolines 1′-4′, indicates that aryloxy radical as well as hydrogen or methyl radical losses involve the formation of common intermediates. This suggests the occurrence of migrations of aryl groups from the N-3 atom to carboxylic oxygen in the molecular ions of 1-4. Copyright © 2001 John Wiley & Sons, Ltd
Characterization of glyceridic components of Sicilian extra virgin olive oils using LC/MS and L.D.A.
No full textMicroheterogeneity Characterization of a Trichorzianine-A Mixture from Trichoderma harzianum
No full textHigh performance liquid chromatography-mass spectrometry based chemometric characterization of olive oils
No full textIn this study the effective discrimination of extra virgin olive oils is described using HPLC–MS, combined with chemometric evaluation.
The presented method is simple since the diluted oil sample is directly injected into the system, without any preliminary chemical derivatization
or purification step. Separation of diacylglycerols, triacylglycerols and sterols occurs within 20 min and is achieved using an octadecyl-silica
column. Detection is performed by positive APCI mass spectrometry which provided sensitivity to detect over 50 compounds in the sample.
After extraction of data, stepwise discriminant function analysis is used to select the variables with the highest discriminative power. These
variables are used to perform linear discriminant analysis and classify/predict the samples. One-hundred per cent classification and 99%
prediction rate was achieved for olive oils obtained from Nocellara, Biancolilla and Cerausola cultivars. Reliability of prediction was tested
by cross validation.
© 2005 Elsevier B.V. All rights reserved
Analysis of sterols by high-performance liquid chromatography/mass spectrometry combined with chemometrics
No full textA newly developed high-performance liquid chromatography/mass spectrometry (HPLC/MS) method has been successfully used to analyze plasma concentrations of various phytosterols (cholestanol and beta-sitosterol) and cholesterol metabolites (desmosterol and lathosterol). This was based on an unusual solvent combination of water/methanol vs. methanol/acetone/n-hexane applied on a Purospher Star RP-18e (125 x 2 mm, 3 mu m) column, which proved excellent for the separation, identification and quantification of plasma sterols. Simple solid-phase extraction preparation of plasma samples was performed, followed by the developed fast and robust HPLC separation. Results on four groups of people were compared, those with low, normal and high plasma cholesterol levels and those with high cholesterol levels on statin therapy, and the results were evaluated using linear discriminant analysis (LDA). Variable selection for LDA was achieved using backward removal selection. Highly discriminatory variables were the ratios of desmosterol to sitosterol and of lathosterol to total plasma cholesterol. The latter ratio was also excellent for distinguishing subjects on statin therapy. The success rate of classification was 100%. The present pilot study shows the potential of HPLC/MS analysis and chemometrics for studying cholesterol-related disorders and warrants future full-scale medical study
