|Platform Agnostic Data Processing Routine for Targeted and Untargeted Metabolite Identification in Drug Discovery |
Richard Lee,1 Vitaly Lashin,2 Andrey Paramonov,2 Alexandr Sakharov,2 Alexey Aminov2
A discussion of a new informatics solution that addresses common challenges in metabolite identification and characterization--from LC/MS data processing and metabolites prediction to reporting and databasing of assembled biotransformation knowledge.
|Accurate Mass Spectral Database: Harnessing the Power of High Performance Mass Spectrometry at Long Last|
Lorne Fell, Viatcheslav Artaev, Kevin McNitt, Steve Robles, Albert Lebedev
Standard mixtures comprising of alkanes, PAHs, semivolatiles, and pesticides were analyzed using a high resolution time-of-flight (HRTOF) mass spectrometer—Pegasus GC-HRT (LECO Corporation, Saint Joseph,MI)—at 10 spectra-per-second (m/z40–300) in high resolution mode (25,000 at FWHH). The resulting chromatographic peaks were automatically found, deconvoluted, and curated into an Accurate Mass Library (AML).
|Automated Sample Preparation of Whole Blood for Therapeutic Drug Monitoring and Diagnostics by LC-MS using a Commercial Autosampler|
Christian Berchtold1, Irene Wegner1,Timm Hettich1, Reto Bolliger2, Guenter Boehm2, Goetz Schlotterbeck1
In this poster the parameters necessary to automatically prepare whole blood samples for online LC-MS applications in the field of diagnostics and TDM have been investigated. A strategy and the most important parameters are shown for the optimization of a PAL RTC autosampler
for the preparation of whole blood samples.
|Development and Application of Quantitative Immunoassays for Major Milk Allergens Bos d 5 (ß-lactoglobulin) and Bos d 11 (ß-casein)|
1Ross A. R. Yarham, 1Anna Kuklinska-Pijanka MSc, 1David Gillick, 1Elizabeth Young, 2Karine Adel Patient PhD, 2Hervé Bernard PhD, 1Martin D. Chapman PhD, 1James P. Hindley PhD
In this study, we sought to develop accurate, sensitive and reliable assays that would enable quantification of multiple milk allergens.
|A Unified Software Platform for Laboratory Informatics|
Graham A. McGibbon, Hans de Bie, David Hardy, Ryan Sasaki, Patrick Wheeler, Carol Preisig
Reported here are capabilities in automated workflows involving analytical data with chemical structures. Specifically described is automated homogenization of data from a set of instruments, including NMR structure verification, as one solution.
|Determination of C2-C12 Aldehydes in Water by SPME Arrow On-Fiber Derivatization and GC/MS|
Peter Egli, Beat Schilling, Guenter Boehm, Kai Schueler
A method applying SPME Arrow extraction and on-fiber derivatization for the quantitation of C2-C12 aldehydes in water by GC/MS is described.
|Assessing Diversity in Cassava through the Application of Metabolomics|
Margit Drapala, Elisabete Carvalhoa, Laura Perez-Fonsa, Elliott Pricea, L. Augusto Becerra Lopez-Lavalleb, Paul D. Frasera
In the present study metabolomic platforms have been established for Cassava and used to assess the biodiversity present in Cassava germplasm collections and elucidate underlying biochemical mechanisms associated with traits of interest.
|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
|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.
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