Graphene/graphene oxide and their derivatives in the separation/isolation and preconcentration of protein species: A review

The distinctive/unique electrical, chemical and optical properties make graphene/graphene oxide-based materials popular in the field of analytical chemistry. Its large surface offers excellent capacity to anchor target analyte, making it an powerful sorbent in the adsorption and preconcentration of trace level analyte of interest in the field of sample preparation. The large delocalized π-electron system of graphene framework provides strong affinity to species containing aromatic rings, such as proteins, and the abundant active sites on its surface offers the chance to modulate adsorption tendency towards specific protein via functional modification/decoration. This review provides an overview of the current research on graphene/graphene oxide-based materials as attractive and powerful adsorption media in the separation/isolation and preconcentration of protein species from biological sample matrixes. These practices are aiming at providing protein sample of high purity for further investigations and applications, or to achieve certain extent of enrichment prior to quantitative assay. In addition, the challenges and future perspectives in the related research fields have been discussed.     

An algorithm for thorough background subtraction from high-resolution LC/MS data: application to the detection of troglitazone metabolites in rat plasma, bile, and urine

Interferences from biological matrices remain a major challenge to the in vivo detection of drug metabolites. For the last few decades, predicted metabolite masses and fragmentation patterns have been employed to aid in the detection of drug metabolites in liquid chromatography/mass spectrometry (LC/MS) data. Here we report the application of an accurate mass-based background-subtraction approach for comprehensive detection of metabolites formed in vivo using troglitazone as an example. A novel algorithm was applied to check all ions in the spectra of control scans within a specified time window around an analyte scan for potential background subtraction from that analyte spectrum. In this way, chromatographic fluctuations between control and analyte samples were dealt with, and background and matrix-related signals could be effectively subtracted from the data of the analyte sample. Using this algorithm with a +/- 1.0 min control scan time window, a +/- 10 ppm mass error tolerance, and respective predose samples as controls, troglitazone metabolites were reliably identified in rat plasma and bile samples. Identified metabolites included those reported in the literature as well as some that had not previously been reported, including a novel sulfate conjugate in bile. In combination with mass defect filtering, this algorithm also allowed for identification of troglitazone metabolites in rat urine samples. With a generic data acquisition method and a simple algorithm that requires no presumptions of metabolite masses or fragmentation patterns, this high-resolution LC/MS-based background-subtraction approach provides an efficient alternative for comprehensive metabolite identification in complex biological matrices. Copyright (c) 2008 John Wiley & Sons, Ltd.