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Results: 5

1.
Figure 1

Figure 1. From: Highly-parallel metabolomics approaches using LC-MS2 for pharmaceutical and environmental analysis.

A simple reversed phase method for simultaneous analysis of 16 anti-HIV drugs in human plasma (Reproduced with permission from [30]; © 2005 Elsevier B.V.).

Sunil Bajad, et al. Trends Analyt Chem. ;26(6):625-636.
2.
Figure 2

Figure 2. From: Highly-parallel metabolomics approaches using LC-MS2 for pharmaceutical and environmental analysis.

Targeted LC-MS2-based metabolomics-type approach for analysis of 17 glucocorticoids in commercial milk and eggs. The selected reaction monitoring (SRM) chromatograms shown were obtained by reversed phase ultra-performance liquid chromatography (UPLC) analysis of an egg sample spiked with standards (Reproduced with permission from [14]; © 2006 John Wiley & Sons Limited).

Sunil Bajad, et al. Trends Analyt Chem. ;26(6):625-636.
3.
Figure 4

Figure 4. From: Highly-parallel metabolomics approaches using LC-MS2 for pharmaceutical and environmental analysis.

A non-targeted capillary LC-MS metabolomics approach used for analysis of hundreds of components in a plant-tissue extract. The profile obtained can be used for quality control and standardization of phytopharmaceuticals. The separation of the Arabidopsis tissue extract was performed on a 450×0.1-mm RP-18 capillary monolithic column using ThermoFisher LTQ mass spectrometer operated in the ESI mode with constant positive/negative switching. Data were processed with the ACD MS Manager software using CODA algorithm. A total of 730 components were detected in positive-ion mode (A) and 411 components in negative-ion mode (B).

Sunil Bajad, et al. Trends Analyt Chem. ;26(6):625-636.
4.
Figure 5

Figure 5. From: Highly-parallel metabolomics approaches using LC-MS2 for pharmaceutical and environmental analysis.

Metabolomics-type approach for the analysis of drug metabolites in bio-fluids. The data shown here was obtained by applying principle component analysis to the LC-MS data obtained from urine of both control rats and rats dosed (with GSK-X). The paired numbers for each data point represent retention time (top smaller number) and mass (bottom higher number). The bold cross in the circle indicates the metabolite (retention time 6.2 min and mass of 319.13) responsible for the clustering of control and dosed groups (Reproduced with permission from [51]; © 2003, John Wiley & Sons Limited).

Sunil Bajad, et al. Trends Analyt Chem. ;26(6):625-636.
5.
Figure 3

Figure 3. From: Highly-parallel metabolomics approaches using LC-MS2 for pharmaceutical and environmental analysis.

Schematics showing comparison of conventional versus metabolomics type approach for analysis of a large number of analytes in a single liquid chromatography (LC) run using triple-quadrupole instrument. A. Conventional analysis of one or few analytes does not require complex LC-MS2 method set-up. B. Metabolomics type approach with poor separation results in limitations with regard to the number of data scans per peak and the number of compounds that can be analyzed. C. Optimal LC-MS2 method that allows simultaneous analysis of hundreds of compounds. Chromatographic run is divided into a number of time segments. Each segment can have a number of scan events, typically 1–10 and each scan event can include number of selected ion monitoring (SIM) or selected reaction monitoring (SRM) scans, typically 1–10. Peaks on the boundary of segments need to be included in both the segments. The number of SRM scans per segment is limited to about 60 in order to obtain sufficient number of data points per peak and to obtain reproducible peak shapes (with scan time of 0.1 sec, each peak will get one data point per 6 s). For details of this approach, readers are directed to [36].

Sunil Bajad, et al. Trends Analyt Chem. ;26(6):625-636.

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