There are numerous detection methods available for methods are being put to use for detection on these miniaturized systems, with the analyte of interest driving the choice of detection method. In this article, we summarize microfluidic 2 years. More focus is given to unconventional approaches to detection routes and novel strategies for performing high-sensitivity detection.Microfluidic devices are becoming a common fixture in many laboratories. Besides the wellknown advantages of reduced sample volumes and decreased analysis times when compared with macro-sized components, these devices also offer significant advantages in other ways. For instance, the ability to couple multiple channels together with minimal dead volume allows for easy handling of low mass samples. Also, the ability to easily and accurately control fluid flow has prompted researchers in other areas, such as biology or biochemistry, to use these devices.Regardless of the nature of the analysis, the end result of the reactions, separations and other processes that occur on these miniaturized devices must be detected. In this article, we aim to provide a review of detection methods for use with microfluidic devices. Due to the evergrowing popularity of microfluidic devices, we have limited the timeframe of this review to papers published after 2007. We refer the readers to previous reviews on detection schemes used in microfluidic systems for earlier time-frames and more specific applications [1-3]. We have not attempted a comprehensive review of the literature, but have selectively chosen a sample of the articles that we believe present unique approaches to the three most common detection methods (optical, electrochemical and mass spectrometric). Optical detection methodsThe most predominant detection method in microfluidic analyses by far has been with optical means. Within this broad class, fluorescence-based detection can be considered routine. The popularity of this technique is mostlikely due to the simplicity with which microfluidic devices can be coupled to fluorescence excitation and detection schemes, as well as their ability to detect from low volume samples. There have been multiple examples of advances in detection using fluorescence-based methods as applied to microfluidic devices. Recent advances have included fluorescence lifetime-imaging (FLIM), high-

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Tumor clonal heterogeneity drives treatment resistance. But robust models are lacking that permit eavesdropping on the basic interaction network of tumor clones. We developed an in vitro, functional model of clonal cooperation using U87MG glioblastoma cells, which isolates fundamental clonal interactions. In this model pre-labeled clones are co-cultured to track changes in their individual motility, growth, and drug resistance behavior while mixed. This highly reproducible system allowed us to address a new class of fundamental questions about clonal interactions. We demonstrate that (i) a single clone can switch off the motility of the entire multiclonal U87MG cell line in 3D culture, (ii) maintenance of clonal heterogeneity is an intrinsic and influential cancer cell property, where clones coordinate growth rates to protect slow growing clones, and (iii) two drug sensitive clones can develop resistance de novo when cooperating. Furthermore, clonal communication for these specific types of interaction did not require diffusible factors, but appears to depend on cell-cell contact. This model constitutes a straightforward but highly reliable tool for isolating the complex clonal interactions that make up the fundamental “hive mind” of the tumor. It uniquely exposes clonal interactions for future pharmacological and biochemical studies.

Free fatty acid (FFA) compositions are examined in feedstock for biodiesel production, as source-specific markers in soil, and because of their role in cellular signaling. However, sample preparation of FFAs for gas chromatography-mass spectrometry (GC-MS) analysis can be time and labor intensive. Therefore, to increase sample preparation throughput, a glass microfluidic device was developed to automate derivatization of FFAs to fatty acid methyl esters (FAMEs). FFAs were delivered to one input of the device and methanolic-HCl was delivered to a second input. FAME products were produced as the reagents traversed a 29 μL reaction channel held at 55 °C. A Design of Experiment protocol was used to determine the combination of derivatization time (T(der)) and ratio of methanolic-HCl:FFA (R(der)) that maximized the derivatization efficiencies of tridecanoic acid and stearic acid to their methyl ester forms. The combination of T(der) = 0.8 min and R(der) = 4.9 that produced optimal derivatization conditions for both FFAs within a 5 min total sample preparation time was determined. This combination of T(der) and R(der) was used to derivatize 12 FFAs with a range of derivatization efficiencies from 18% to 93% with efficiencies of 61% for tridecanoic acid and 84% for stearic acid. As compared to a conventional macroscale derivatization of FFA to FAME, the microfluidic device decreased the volume of methanolic-HCl and FFA by 20- and 1300-fold, respectively. The developed microfluidic device can be used for automated preparation of FAMEs to analyze the FFA compositions of volume-limited samples.