System Integration - A Major Step toward Lab on a Chip

Microfluidics holds great promise to revolutionize various areas of biological engineering, such as single cell analysis, environmental monitoring, regenerative medicine, and point-of-care diagnostics. Despite the fact that intensive efforts have been devoted into the field in the past decades, microfluidics has not yet been adopted widely. It is increasingly realized that an effective system integration strategy that is low cost and broadly applicable to various biological engineering situations is required to fully realize the potential of microfluidics. In this article, we review several promising system integration approaches for microfluidics and discuss their advantages, limitations, and applications. Future advancements of these microfluidic strategies will lead toward translational lab-on-a-chip systems for a wide spectrum of biological engineering applications

Chemically functionalized multi-walled carbon nanotubes sensors for ultra-low-power alcohol vapour detection

We have successfully chemically functionatized the multi-walled carbon nanotubes (MWCNTs) with COOH group by the method of oxidation and used AC electrophoresis to formed these bundles MWCNTs between Au electrodes on the Si substrate. We then demonstrated that these resistive elements are capable of detecting alcohol vapor using an ultra-low input power of only ∼0.01μW. The sensors exhibit fast, repeatable, highly sensitive, and reversible response. Our results show that the resistances of the sensors vary linearly with alcohol vapor concentration from Sppth to 100ppth (ppth = part per thousand). We can also easily reverse the initial resistance of the sensors by annealing them in real time at 100-250/JA current within 1-6 minutes. We have experimental proof that the functionatized MWCNTs have a much higher sensitivity towards the alcohol vapor than the bare MWCNTs. Based on our experimental results, we prove that MWCNTs sensors, especially for those with proper functionatized groups, are sensitive to a wide range of alcohol vapor and potentially other volatile organic compounds, and are very attractive for commercialization due to their extreme low-power requirements for activation. " 2006 IEEE

Constant-power operation of functionalized carbon nanotube sensors for alcohol vapor detection

A constant-power control circuit has been built successfully for the digital operation of CNT-based alcohol vapor sensors. The sensors, which are based on bundles of chemically functionalized multi-walled carbon nanotubes (f-CNTs), have been proven to be sensitive towards alcohol molecules. The resistance of the sensors increases upon exposure to alcohol vapors. The constant-power configuration is developed to avoid the self-heating effect, which is a significant factor in affecting the sensor performance. On the other hand, we also utilized the selfheating effect to clean up the alcohol molecules on the f-CNTs between measurements. The comparison experiments between constant-power and constant-current configurations were conducted. The results demonstrated larger response under constant-power mode, especially when operating power was low or alcohol concentration was relatively high. The responsivity and the sensitivity of alcohol vapor sensors under different mode and operating powers are also discussed

Deep Sequencing of Urinary RNAs for Bladder Cancer Molecular Diagnostics

Purpose: The majority of bladder cancer patients present with localized disease and are managed by transurethral resection. However, the high rate of recurrence necessitates lifetime cystoscopic surveillance. Developing a sensitive and specific urine-based test would significantly improve bladder cancer screening, detection, and surveillance.Experimental Design: RNA-seq was used for biomarker discovery to directly assess the gene expression profile of exfoliated urothelial cells in urine derived from bladder cancer patients (n = 13) and controls (n = 10). Eight bladder cancer specific and 3 reference genes identified by RNA-seq were quantitated by qPCR in a training cohort of 102 urine samples. A diagnostic model based on the training cohort was constructed using multiple logistic regression. The model was further validated in an independent cohort of 101 urines.Results: A total of 418 genes were found to be differentially expressed between bladder cancer and controls. Validation of a subset of these genes was used to construct an equation for computing a probability of bladder cancer score (PBC) based on expression of three markers (ROBO1, WNT5A, and CDC42BPB). Setting PBC = 0.45 as the cutoff for a positive test, urine testing using the three-marker panel had overall 88% sensitivity and 92% specificity in the training cohort. The accuracy of the three-marker panel in the independent validation cohort yielded an AUC of 0.87 and overall 83% sensitivity and 89% specificity.Conclusions: Urine-based molecular diagnostics using this three-marker signature could provide a valuable adjunct to cystoscopy and may lead to a reduction of unnecessary procedures for bladder cancer diagnosis. Clin Cancer Res; 23(14); 3700-10. ©2017 AACR