| The task of sample preparation encompasses many challenges and demands for analytical techniques. Appropriate preparative steps can be the determining factor between successful measurements and failures. Too little preparation can lead to the inability to detect analytes due to low concentrations, insufficient extraction of analytes, and/or strong matrix effects; exhaustive preparation steps increases analysis times, the potential for analyte losses, and the difficulty to obtain consistent reproducible results. Discussed here are several examples of analytical techniques where sample preparation is critical and can be used to improve existing techniques. Capillary-channeled polymer (C-CP) fibers used for solid phase extraction (SPE) protein analysis techniques is described first. The C-CP fibers have several advantageous attributes stemming from the unique shape, wide chemical and pH stability ranges, predictable surface interactions, and overall low material costs. The fibers have been employed in micropipette tip and microcolumn SPE formats for the desalting of proteins from high salt content buffer, synthetic urine and synthetic saliva matrices. Micropipette tips were prepared and used for an off-line method prior to UV-VIS detection, and a microcolumn format was developed as an on-line SPE technique for ESI-MS detection. The characterization of isoflavones present in soy, kudzu, and red clover products by liquid chromatography-particle beam electron ionization mass spectrometry (LC-PB/EIMS) is also described. Here, NIST Standard Reference Materials (SRMs) were extracted using 80% methanol without a hydrolysis step. Samples were then analyzed using a chromatographic separation and analytes quantified by an internal standard (IS) method using 7-hydroxy-4-chromone as the IS compound. The particle beam allows for simple interfacing between LC separations and EIMS detection, giving ability to attain qualitative and quantitative information simultaneously. Isoflavones were quantified and compared to NIST certified values. |
