|Metabolomic profile of multiple sclerosis patients by means of 1H-NMR analysis|
Federica Murgia1, Lorena Lorefice 2 ,Eleonora Cocco2, Luigi Barberini2, Simone Poddighe1, Maria Rita Murru2, Raffaele Murru2, Jessica Frau2, MD Giuseppe Fenu2, MD, Giancarlo Coghe2, Francesco Del Carratore1, Luigi Atzori1, Maria Giovanna Marrosu3
Multiple sclerosis (MS) is a chronic disease characterized by a high level of heterogeneity. Metabolomics is an “-omics” approach with the potential to discover new biomarkers.
|Application of metabolomics in drug-resistant epilepsy research|
Federica Murgia1, Simone Poddighe1, Francesco Del Carratore1, Lorenzo Polizzi2, Antonella Muroni2, Luigi Barberini3, Monica Puligheddu3, Francesco Marrosu2 , Luigi Atzori1
Metabolomics represents an important tool for biomarker discovery in drug-resistant epilepsy and for the study of the pathophysiology of this disease.
|Changes in the metabolic profile of urine from mink during early pregnancy|
Mette Skou Hedemann
Metabolic profiling of urine from pregnant mink showed that ß-oxidation as well as protein metabolism is changed during pregnancy in mink and it is hypothesized that the changes occur to ensure optimal nutrition of the foetuses.
|A KNIME Pipeline for the Analysis of GC-MS Data in Metabolomics|
Sonia Liggi1, Maria Laura Santoru1, Cristina Piras1, Antonio Murgia2, Pierluigi Caboni2, Luigi Atzori1
A KNIME pipeline was developed to perform pre-processing of GC-MS data in an automated way and applied to a Inflammatory bowel diseases case study
|Metabolic response to everolimus in patient-derived xenografts of triple negative breast cancer|
Leslie R. Euceda1, Deborah K. Hill1,2, Endre Stokke1, Elisabetta Marangoni3, Tone F. Bathen1, Siver A. Moestue1,2
Everolimus treatment metabolic effects on TNBC PDX models were investigated using MR spectroscopy. PLS-DA successfully discriminated treated from controls and PDX expressing INPP4B and not. LMM revealed significant differences in 4/17 metabolites and two metabolite ratios between treated and controls.
|PredRet: Prediction of Retention Time by Direct Mapping between Multiple Chromatographic Systems|
Jan Stanstrup, Steffen Neumann, Urška Vrhovšek
Retention time (RT) information is under-utilized in LC-MS based metabolomics and sharing of RTs between systems is not currently possible. PredRet is a new system that allows highly accurate mapping and prediction of RTs between LC systems.
|Profiling of metabolomic changes induced by testosterone esters in pig plasma and urine|
Kamil Stastny, Martin Faldyna, Milan Franek
In this study, metabolic fingerprinting to discriminate between pigs treated with 17ß-testosteron esters and control animals has been investigated. Multivariate statistical analysis showed significant metabolic differences between test and control groups on day 28 after aplication of the testosterone hormonal preparation.
|The Challenges of Genetic Testing in Patients Diagnosed with Breast Cancer; The Kent Oncology Centre Experience|
Christos Mikropoulos1,2, Aaron Davies 1, Charlotte Abson1, Gill Sadler1, Gemma McCormick1, Questa Karlsson2, Julia Hall2
In this study we explore retrospective data to determine strategies for optimizing the genetic referral pathways for breast cancer.
|The Role of microRNAs in Memory Consolidation in Lymnaea|
György Kemenes1, Dimitris Vavoulis2, Sergei Korneev1
In this study we investigated the temporal dynamics of the post-training expression of miRNAs in the ‘learning ganglia’ of Lymnaea.
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