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Pritchard Pagh posted an update a month ago
In Reversed-Phase Liquid Chromatography, Quantitative Structure-Retention Relationship (QSRR) models for retention prediction of peptides can be built, starting from large sets of theoretical molecular descriptors. Good predictive QSRR models can be obtained after selecting the most informative descriptors. Reliable retention prediction may be an aid in the correct identification of proteins/peptides in proteomics and in chromatographic method development. Traditionally, global QSRR models are built, using a calibration set containing a representative range of analytes. In this study, a strategy is presented to build individual local Partial Least Squares (PLS) models for peptides, based on selected local calibration samples, most similar to the specific query peptide to be predicted. Similar local calibration peptides are selected from a possible calibration set. The calibration samples with the lowest Euclidian distances to the query peptide are considered as most similar. Two Euclidian distances are investigated as similarity parameter, (i) in the autoscaled descriptor space and, (ii) in the PLS factor space of the global calibration samples, both after variable selection by the Final Complexity Adapted Models (FCAM) method. The predictive abilities of individual local QSRR PLS models for peptides, developed with both Euclidian distances, are found significantly better than those of two global models, i.e. Seladelpar in vivo before and after FCAM variable selection. The predictive abilities of the local models, developed with distances calculated in the PLS factor space, were best.Dynamic chemical labelling is a single-base specific method to enable detection and quantification of micro-Ribonucleic Acids in biological fluids without extraction and pre-amplification. In this study, dynamic chemical labelling was combined with the Luminex MAGPIX system to profile levels of microRNA-122 biomarker in serum from patients with Drug-Induced Liver Injury.Natural flavouring materials are in high demand, and a premium price is paid for all-natural flavourings, making them vulnerable to fraud. At present, compound-specific isotope analysis (CSIA) is perhaps the most sophisticated tool for determining flavour authenticity. Despite promising results, the method is not widely used, and the results are limited to the most common volatile organic compounds (VOCs). This paper describes a robust protocol for on-line measurements of δ13C and δ2H using HS-SPME coupled with GC-C-IRMS and GC-HTC-IRMS for common fruit VOCs. To achieve reproducible and accurate results, a combination of a peak size/linearity correction with drift correction were used. Finally, the results were normalised by multiple point linear regression using the known and measured values of reference materials. Special care was taken to avoid irreproducible isotopic fractionation and the effects of equilibration, adsorption, desorption times and temperatures on δ13C or δ2H values were examined. Method validation was performed, and the average combined measurement uncertainty (MU) was 0.42‰. All the δ13CVPDB values were below ±3*MU, regardless of analytical conditions. In contrast, for δ2HVSMOW-SLAP values, only low temperature (30 °C) with equilibration time (15 min) and shorter adsorption time (between 10 and 20 min) can produce an isotopic difference of less then 10‰. Therefore, method optimisation can minimise MU, and data normalisation and method validation are essential for obtaining meaningful data for use in flavour authenticity studies.This study evaluates zwitterionic-hydrophilic interaction capillary liquid chromatography (capZIC-HILIC) and capillary electrophoresis (CE) with ultraviolet (UV) and mass spectrometry (MS) detection for the direct, label-free and multiplex analysis of microribonucleic acids (miRNAs). CapZIC-HILIC-UV and CE-UV methods were first optimized, resulting in similar separations for a mixture of three miRNAs (hsa-iso-miR-16-5p, hsa-let-7g-5p, and hsa-miR-21-5p) but with reversal of elution/migration orders and small differences in repeatability, linearity, limit of detection (LOD) and separation efficiency. The established UV methods were transferred and validated in these terms with mass spectrometry (MS) detection, which allowed identifying the miRNAs and characterizing their post-transcriptional modifications. LOD by capZIC-HILIC-MS was 1 μM of miRNA, around 5 times lower than by CE-MS due to the analyte dilution with the sheathflow CE-MS interface and to the slightly increased abundance of alkali metals adducts in the CE-MS mass spectra. In addition, the suction effect promoted by the nebulizer gas in CE-MS negatively affected the already compromised separations. In contrast, CE-MS showed superior repeatabilities with spiked serum samples, as well as reduced costs, extended capillary column durabilities and shorter conditioning times. The comparison of the different methods allows disclosing the current advantages and disadvantages of capZIC-HILIC and CE for the analysis of miRNA biomarkers.Short peptides are of extreme interest in clinical and food research fields, nevertheless they still represent a crucial analytical issue. The main aim of this paper was the development of an analytical platform for a considerable advancement in short peptides identification. For the first time, short sequences presenting both natural and post-translationally modified amino acids were comprehensively studied thanks to the generation of specific databases. Short peptide databases had a dual purpose. First, they were employed as inclusion lists for a suspect screening mass-spectrometric analysis, overcoming the limits of data dependent acquisition mode and allowing the fragmentation of such low-abundance substances. Moreover, the databases were implemented in Compound Discoverer 3.0, a software dedicated to the analysis of short molecules, for the creation of a data processing workflow specifically dedicated to short peptide tentative identification. For this purpose, a detailed study of short peptide fragmentation pathways was carried out for the first time. The proposed method was applied to the study of short peptide sequences in enriched urine samples and led to the tentative identification more than 200 short natural and modified short peptides, the highest number ever reported.