New Biotransformation Prediction Engine Integrated into a Metabolite Identification Solution
Poster Mar 02, 2018
Richard Lee, Rytis Kubilius, Vitaly Lashin, Alexandre Sakarov
In the analysis of xenobiotic metabolism, the main analytical platform for studying experiments is liquid chromatography coupled to a high resolution mass spectrometer. There have been a number of advancements in the hardware used, as well as the software that processes these data. However, bottlenecks remain in the workflow and especially in the structure elucidation phase. A new prediction algorithm was developed to aid in the identification of possible metabolites within an LC/MS dataset. The work presented here describes the integration of new prediction methods that determine the likelihood of biotransformation reactions, and subsequent metabolite identification within an automated processing routine.
C1 Complement mediates human cord blood serum derived APP α-secretase cleavage activity in vitroPoster
Our results indicate that CBS contains proteins that promote α-secretase like enzymatic activity. LC-MS/MS analysis in CBSF and AgBSF revealed the presence of 142 proteins of which C1 subunits and alpha-2-macroglobulin showed significantly greater levels in αCBSF compared with αAgBSF. further study showed,C1 subunits can enhance sAPPα production and Aβ reduction in cell culture conditionREAD MORE
A Computational Model of Mood and Future ProspectsPoster
Mood disorders are characterized by changes in reaction to positive events, but studies examining mood in gambling have suggested these changes may not be different from control. Interrogating mood changes with a computational model may give insight into disorders like depression.READ MORE
Fingerprinting the Terpene Profiles of Various Cannabis Strains using GC and GCxGC with High Performance TOFMSPoster
The Pegasus BT 4D facilitates fast and confident cannabis product “fingerprinting” through enhanced two-dimensional chromatographic resolution and high performance TOFMS.
Robust compound identification was achieved through spectral similarity searches of large, well-established databases, mass D determinations, and retention index filtering.
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9th International Conference on Mass Spectrometry and Chromatography
Sep 21 - Sep 22, 2018