Targeted projection NMR spectroscopy for unambiguous metabolic profiling of complex mixtures

2010 ◽  
Vol 48 (9) ◽  
pp. 727-733 ◽  
Author(s):  
Clément Pontoizeau ◽  
Torsten Herrmann ◽  
Pierre Toulhoat ◽  
Bénédicte Elena-Herrmann ◽  
Lyndon Emsley
2015 ◽  
Vol 14 (5) ◽  
pp. 2177-2189 ◽  
Author(s):  
Florence Fauvelle ◽  
Julien Boccard ◽  
Fanny Cavarec ◽  
Antoine Depaulis ◽  
Colin Deransart

2019 ◽  
Vol 92 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Jelena Parlov Vuković ◽  
Predrag Novak ◽  
Tomislav Jednačak

Asphaltenes are the most polar oil components with molecular weights between 500 and 1000 Da, which primarily consist of carbons and hydrogens, some heteroatoms, such as nitrogen, sulphur, oxygen and traces of nickel, vanadium and iron. Owing to their extreme complexity, it is almost impossible to completely identify all the compounds present in asphaltene samples. Various analytical techniques and approaches were used to characterize asphaltenes but their structure and composition are still a matter of thorough investigations. NMR spectroscopy can reveal useful information on asphaltene molecular architecture and aggregation process. In that respect, one- and two-dimensional NMR techniques have widely been employed. Although NMR spectra of these complex mixtures are difficult to interpret, they still can provide valuable data, especially in combination with statistical methods. Some distinctive examples of using NMR spectroscopy to study asphaltenes are given in this review.


2019 ◽  
Vol 58 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Liliana López-Garrido ◽  
Angel E. Bañuelos-Hernández ◽  
Elizabeth Pérez-Hernández ◽  
Romeo Tecualt-Gómez ◽  
Jorge Quiroz-Williams ◽  
...  

2015 ◽  
Vol 21 (21) ◽  
pp. 7682-7685 ◽  
Author(s):  
Laura Castañar ◽  
Raquel Roldán ◽  
Pere Clapés ◽  
Albert Virgili ◽  
Teodor Parella

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 22-22
Author(s):  
Angela W Chan ◽  
Pascal Mercier ◽  
Dan E. Schiller ◽  
Dean Eurich ◽  
David Broadhurst ◽  
...  

22 Background: Gastric cancer (GC) has 70-75% mortality, attributable to delayed diagnosis. There is no standard screening in North America. Metabolomics is a systems biology approach to measure low molecular weight chemicals (metabolites) in body fluids or tissues to provide a phenotypic “fingerprint” of disease etiology. In this preliminary study it was hypothesized that metabolic profiling of urine samples using 1H-NMR spectroscopy could discriminate between resectable gastric adenocarcinoma (GC), benign gastric disease (BN), and healthy (HE) patients (pts). Methods: Midstream urine samples were collected, processed, and biobanked at -80°C, from 30 BN, 30 HE and 16 of 29 GC pts visiting three Edmonton clinics from August 2013 – January 2014. Thirteen of 29 samples were retrieved from a 2009-13 GC biobank. Samples were matched on age, gender and BMI. Using a validated standard operating procedure each sample was analyzed using high resolution 1H-NMR spectroscopy. Resulting spectral traces were converted into annotated and quantified metabolite profiles of 58 metabolites. Univariate and multivariate statistical analysis uncovered a disease specific biomarker profile. Partial Least Squares Discriminant Analysis (PLS-DA) developed a GC vs. HE discriminative model. A Receiver Operator Characteristic (ROC) curve was constructed. Results: There was no significant difference in metabolite profiles between GC and BN pts. However, univariate analysis revealed 13 metabolites that differed significantly between GC and HE (p<0.05). Correlation analysis, followed by PLS-DA produced a discriminative model with an area under ROC curve of 0.996, such that for a specificity of 100% the corresponding sensitivity was 93%. Conclusions: GC pts have a distinct urinary metabolite profile compared to HE controls; however in this study metabolic profiling was unable to discriminate GC from BN pts. This was probably due to sample size and phenotypic heterogeneity of BN patients. This preliminary study shows clinical potential for metabolic profiling for early GC detection.


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