Bioanalysis 

About: Bioanalysis is an academic journal published by Future Science Ltd. The journal publishes majorly in the area(s): Bioanalysis & Dried blood spot. It has an ISSN identifier of 1757-6180. Over the lifetime, 2791 publications have been published receiving 45466 citations. The journal is also known as: BIO.

The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans.

Abstract: The metabolic investigation of the human population is becoming increasingly important in the study of health and disease. The phenotypic variation can be investigated through the application of metabolomics; to provide a statistically robust investigation, the study of hundreds to thousands of individuals is required. In untargeted and MS-focused metabolomic studies this once provided significant hurdles. However, recent innovations have enabled the application of MS platforms in large-scale, untargeted studies of humans. Herein we describe the importance of experimental design, the separation of the biological study into multiple analytical experiments and the incorporation of QC samples to provide the ability to perform signal correction in order to reduce analytical variation and to quantitatively determine analytical precision. In addition, we describe how to apply this in quality assurance processes. These innovations have opened up the capabilities to perform routine, large-scale, untargeted, MS-focused studies.

The effect of hematocrit on assay bias when using DBS samples for the quantitative bioanalysis of drugs

Abstract: Background: As hematocrit levels are known to vary between individuals and with disease state, its effect on the physical characteristics of dried blood spot (DBS) samples and on the accurate quantification of analytes within these samples is examined. Results: The area of DBS samples decreases with increasing hematocrit levels in a linear manner on the three cellulose paper substrates tested. Furthermore, a bias was observed in the concentrations of two analytes determined in DBS samples at different hematocrits, which in some cases exceeded acceptable values, particularly for hematocrits outside normal values. Conclusion: If it is expected that the hematocrit of study samples will vary from values considered normal, then its effect on the quantitative determination of an analyte in DBS samples should be investigated as part of the method development and validation. If an unacceptable effect is observed, then this will need to be addressed, by modification of the analytical method, or the inclusion of qu...

Microfluidic 3D cell culture: potential application for tissue-based bioassays.

Abstract: Current fundamental investigations of human biology and the development of therapeutic drugs commonly rely on 2D monolayer cell culture systems. However, 2D cell culture systems do not accurately recapitulate the structure, function or physiology of living tissues, nor the highly complex and dynamic 3D environments in vivo. Microfluidic technology can provide microscale complex structures and well-controlled parameters to mimic the in vivo environment of cells. The combination of microfluidic technology with 3D cell culture offers great potential for in vivo-like tissue-based applications, such as the emerging organ-on-a-chip system. This article will review recent advances in the microfluidic technology for 3D cell culture and their biological applications.

Advances in metabolite identification

Abstract: One of the central challenges to metabolomics is metabolite identification. Regardless of whether one uses so-called 'targeted' or 'untargeted' metabolomics, eventually all paths lead to the requirement of identifying (and quantifying) certain key metabolites. Indeed, without metabolite identification, the results of any metabolomic analysis are biologically and chemically uninterpretable. Given the chemical diversity of most metabolomes and the character of most metabolomic data, metabolite identification is intrinsically difficult. Consequently a great deal of effort in metabolomics over the past decade has been focused on making metabolite identification better, faster and cheaper. This review describes some of the newly emerging techniques or technologies in metabolomics that are making metabolite identification easier and more robust. In particular, it focuses on advances in metabolite identification that have occurred over the past 2 to 3 years concerning the technologies, methodologies and software as applied to NMR, MS and separation science. The strengths and limitations of some of these approaches are discussed along with some of the important trends in metabolite identification.