140 research outputs found
Novel technologies for metabolomics: More for less
The human metabolome provides a direct physiological read-out of an individual's actual health state and includes biomarkers that may predict disease or response to a treatment. The discovery and validation of these metabolomic biomarkers requires large-scale cohort studies, typically involving thousands of samples. This analytical challenge drives novel technological developments to enable faster, cheaper, and more comprehensive metabolomic analysis: more for less.This review summarises recent (2012–2018) developments towards this goal in all aspects of the analytical workflow, in relation to NMR but primarily to mass spectrometry (MS). Recent trends include miniaturisation and automation of extraction techniques, online coupling to fast analysis methods including direct infusion ion mobility MS, integrated microfluidic devices, and sharing and standardizing metabolomics software and data.The technological advances in metabolomics support its widespread application, integration with other -omics fields, and ultimately disease prediction and precision medicine.Pharmacolog
Site-specific and bulk-phase generation of hydroxyl radicals in the presence of cupric ions and thiol compounds
Potentiation of thermal inactivation of glyceraldehyde-3-phosphate dehydrogenase by photodynamic treatment. A possible model for the synergistic interaction between photodynamic therapy and hyperthermia
Toxic effects of ozone on murine L929 fibroblasts. Damaging action on transmembrane transport systems
Potentiation of hyperthermia-induced haemolysis of human erythrocytes by photodynamic treatment. Evidence for the involvement of the anion transporter in this synergistic interaction
Non-invasive measurements of the dynamic changes in the ciliary muscle, crystalline lens morphology, and anterior chamber during accommodation with a high-resolution OCT
Flavor profiling using comprehensive mass spectrometry analysis of metabolites in tomato soups
Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having "garlic-like" and "onion-like" attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.Analytical BioScience
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