1,721,036 research outputs found
Editorial to the special issue “lipidomics and neurodegenerative diseases”
Full text linkThe contribution of dysregulation of lipid signaling and metabolism to neurodegenerative diseases including Alzheimer’s and Parkinson’s is the focus of this special issue. Here, the matter of three reviews and one research article is summarized
Characterization of caffeic acid enzymatic oxidation by-products by liquid chromatography coupled to electrospray ionization tandem mass spectrometry
No full textX-ray photoelectron spectroscopy characterization of poly(2,3-diaminophenazine) films electrosynthesised on platinum
No full textAcylated glucosinolates with diverse acyl groups investigated by high resolution mass spectrometry and infrared multiphoton dissociation
No full textApplicability of chemical derivatization - x-ray photoelectron spectroscopy (CD-XPS) to the characterization of complex matrixes: case of electrosynthesized polypyrroles
No full textSolid-phase microextraction coupled to gas chromatography-mass spectrometry for the study of soil adsorption coefficients of organophosphorous pesticides
No full textA solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) method for the
simultaneous determination of the organophosphorus pesticides (OPPs), phorate, diazinon, methyl-parathion,
fenitrothion, malathion, fenthion, ethyl-parathion and methidathion, has been developed to study their soil/
water distribution. The method was used in conjunction with a conventional ‘batch equilibrium method’ to
assess the soil adsorption coefficients (Koc) of the target compounds in different soil samples with known
organic carbon content. Contrary to traditional techniques, the present method is fast, solvent-free and highly
sensitive, thus permitting the assessment of the Koc values of the target compounds even at low soil
concentration levels, close to those encountered in real field contamination, where the Freundlich adsorption
isotherms can be considered to be linear. The estimated Koc values were found to be in good agreement with
those reported in the literature
Needle-Type Glucose Microbiosensor Based on Glucose Oxidase Immobilised in an Overoxidised Polypyrrole Film (an in vitro study)
No full textDetermination of hidden milk allergens in meat-based foodstuffs by liquid chromatography coupled to electrospray ionization and high-resolution tandem mass spectrometry
Full text linkThe issue of deliberate addition of antigenic proteins to foodstuffs for ameliorating bulk properties or the unintentional cross-contamination poses potentially life-threatening health problems to susceptible subjects. Even the intake of food products declaring the absence of allergens on their labels could lead to severe risks for sensitive consumers due to the presence of the so-called "hidden allergens". Thus, the quantification of low-abundant proteins as putative allergens has become mandatory. Herein, we present a sensitive and selective analytical method based on reversed-phase liquid chromatography coupled to electrospray ionization and hybrid orbitrap high-resolution mass spectrometry (RPLC-ESI-HRMS) and tandem MS, identifying, and quantifying allergenic milk proteins in complex meat-based foodstuffs from direct measurement of tryptic peptides. Two signature peptides of alpha-S1-casein and beta-lactoglobulin, i.e., FFVAPFPEVFGK (m/z 692.868(2+)) and TPEVDDEALEK (m/z 623.295(2+)), respectively, were chosen to search for hidden allergens in meat-based samples such as cooked meat, sausages, and sterilised pate. The marker peptides were identified and were exploited for method validation including recovery, matrix effect, precision, linearity, method variation, limit of detection, and limit of quantification. The undeclared occurrence of milk allergens as total milk protein content (TCMP) was verified in commercial meat products; beef and pork pate were meat-based products which require a major alert because up to 22 mu g(TCMP)/g of matrix i.e. more than 10 times the action level was determined
Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS
No full textThis review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability
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