Matthew Y. H. Tang

Asymmetric-detection time-stretch optical microscopy (ATOM) for ultrafast high-contrast cellular imaging in flow

Accelerating imaging speed in optical microscopy is often realized at the expense of image contrast, image resolution, and detection sensitivity – a common predicament for advancing high-speed and high-throughput cellular imaging. We here demonstrate a new imaging approach, called asymmetric-detection time-stretch optical microscopy (ATOM), which can deliver ultrafast label-free high-contrast flow imaging with well delineated cellular morphological resolution and in-line optical image amplification to overcome the compromised imaging sensitivity at high speed. We show that ATOM can separately reveal the enhanced phase-gradient and absorption contrast in microfluidic live-cell imaging at a flow speed as high as ~10 m/s, corresponding to an imaging throughput of ~100,000 cells/sec. ATOM could thus be the enabling platform to meet the pressing need for intercalating optical microscopy in cellular assay, e.g. imaging flow cytometry – permitting high-throughput access to the morphological information of the individual cells simultaneously with a multitude of parameters obtained in the standard assay.

One-step immunoassay of C-reactive protein using droplet microfluidics

We present a wash-free high-sensitivity immunoassay of C-reactive proteins with droplet microfluidics. Microbeads are encapsulated within droplets for the immunoassay, and the droplets are scanned by a fluorescence detection platform to quantify the amount of proteins captured on the microbeads. The limit of detection determined by our platform is 0.01 μg mL-1, which is ten times more sensitive than conventional high-sensitivity C-reactive protein assays. With the decrease in diffusion distance within droplets, the immunoassay requires only half of the time required for similar conventional approaches. This approach for carrying out immunoassays can potentially be applied to other biomarkers beyond C-reactive proteins.

Stemness and chemoresistance in epithelial ovarian carcinoma cells under shear stress

One of greatest challenges to the successful treatment of cancer is drug resistance. An exciting approach is the eradication of cancer stem cells (CSCs). However, little is known about key signals regulating the formation and expansion of CSCs. Moreover, lack of a reliable predictive preclinical model has been a major obstacle to discover new cancer drugs and predict their clinical activity. Here, in ovarian cancer, a highly chemoresistant tumor that is rapidly fatal, we provide the first evidence demonstrating the causal involvement of mechanical stimulus in the CSC phenotype using a customizable microfluidic platform and three-dimensional spheroids, which most closely mimic tumor behavior. We found that ovarian cancer cells significantly acquired the expression of epithelial-to-mesenchymal transition and CSC markers and a remarkable chemoresistance to clinically relevant doses of frontline chemotherapeutic drugs cisplatin and paclitaxel when grown under fluid shear stress, which corroborates with the physiological attainable levels in the malignant ascites, but not under static condition. Furthermore, we uncovered a new link of microRNA-199a-3p, phosphatidylinositol 3-kinase/Akt, and multidrug transporter activation in shear stress-induced CSC enrichment. Our findings shed new light on the significance of hydrodynamics in cancer progression, emphasizing the need of a flow-informed framework in the development of therapeutics.

Evaluating automated road extraction in different operational modes

From an operational standpoint, road extraction remains largely a manual process despite the existence of several commercially available automation tools. The problem of automated feature extraction (AFE) in general is a challenging task as it involves the recognition, delineation, and attribution of image features. The efficacy of AFE algorithms in operational settings is difficult to measure due to the inherent subjectivity involved. Ultimately, the most meaningful measures of an automation method are its effect on productivity and actual utility. Several quantitative and qualitative factors go into these measures including spatial accuracy and timed comparisons of extraction, different user training levels, and human-computer interface issues. In this paper we investigate methodologies for evaluating automated road extraction in different operational modes. Interactive and batch extraction modes of automation are considered. The specific algorithms investigated are the GeoEye Interactive Road Tracker®(IRT) and the GeoEye Automated Road Tracker®(ART) respectively. Both are commercially available from GeoEye. Analysis metrics collected are derived from timed comparisons and spatial delineation accuracy. Spatial delineation accuracy is measured by comparing algorithm output against a manually derived image reference. The effect of object-level fusion of multiple imaging modalities is also considered. The goal is to gain insight into measuring an automation algorithms utility on feature extraction productivity. Findings show sufficient evidence to demonstrate a potential gain in productivity when using an automation method when the situation is warranted. Fusion of feature layers from multiple images also demonstrates a potential for increased productivity compared to single or pair-wise combinations of feature layers.

Modeling Ovarian Cancer Multicellular Spheroid Behavior in a Dynamic 3D Peritoneal Microdevice

Ovarian cancer is characterized by extensive peritoneal metastasis, with tumor spheres commonly found in the malignant ascites. This is associated with poor clinical outcomes and currently lacks effective treatment. Both the three-dimensional (3D) environment and the dynamic mechanical forces are very important factors in this metastatic cascade. However, traditional cell cultures fail to recapitulate this natural tumor microenvironment. Thus, in vivo-like models that can emulate the intraperitoneal environment are of obvious importance. In this study, a new microfluidic platform of the peritoneum was set up to mimic the situation of ovarian cancer spheroids in the peritoneal cavity during metastasis. Ovarian cancer spheroids generated under a non-adherent condition were cultured in microfluidic channels coated with peritoneal mesothelial cells subjected to physiologically relevant shear stress. In summary, this dynamic 3D ovarian cancer-mesothelium microfluidic platform can provide new knowledge on basic cancer biology and serve as a platform for potential drug screening and development.

Picoinjection-Enabled Multitarget Loop-Mediated Isothermal Amplification for Detection of Foodborne Pathogens

In this study, we develop a method to detect multiple DNAs of foodborne pathogens by encapsulating emulsion droplets for loop-mediated isothermal amplification (LAMP). In contrast to the traditional bulk-phase LAMP, which involves a labor-intensive mixing process, with our method, different primers are automatically mixed with DNA samples and LAMP buffers after picoinjection. By directly observing and analyzing the fluorescence intensity of the resultant droplets, one can detect DNA from different pathogens, with a detection limit 500 times lower than that obtained by bulk-phase LAMP. We further demonstrate the ability to quantify bacteria concentration by detecting bacterial DNA in practical samples, showing great potential in monitoring water resources and their contamination by pathogenic bacteria.

Asymmetric-detection time-stretch optical microscopy (ATOM) for high-contrast and high-speed microfluidic cellular imaging

High-throughput cellular imaging is acclaimed as captivating yet challenging in biomedical diagnostics. We have demonstrated a new imaging modality, asymmetric-detection time-stretch optical microscopy (ATOM), by incorporating a simple detection scheme which is a further advancement in time-stretch microscopy – a viable solution to achieve high-speed and high-throughput cellular imaging. Through the asymmetric-detection scheme in ATOM, the time-stretch image contrast is enhanced through accessing to the phase-gradient information. With the operation in the 1 μm wavelength range, we demonstrate high-resolution and high-contrast cellular imaging in ultrafast microfluidic flow (up to 10 m/s) by ATOM – achieving an imaging throughput equivalent to ~100,000 cells/sec.

Ultrafast flow imaging by 1 μm time-stretch microscopy

We demonstrate ultrafast flow imaging of micro-particles by optical time-stretch microscopy at 1 μm, with an ultrahigh imaging throughput up to ~100,000 particles/s - enabling this high-speed imaging technique for a wider scope of biophotonic applications.

Ultrafast high-contrast microfluidic cellular imaging by asymmetric-detection time-stretch optical microscopy (ATOM)

We demonstrate asymmetric-detection time-stretch optical microscopy which delivers high-contrast (simultaneous enhanced phase-gradient and absorption contrasts) microfluidic imaging with subcellular resolution and in-line optical image amplification (20dB), at a record imaging flow speed of 10 m/s.

Evaluation methods for curvilinear feature extraction

The application of quantitative performance evaluation methods can provide useful insights in determining the utility of computer-assisted methods for delineating geographic features from remotely sensed images. Evaluation concepts are demonstrated with road centerlines in particular, but are applicable to similar feature types such as paths, trails, or rivers. The two comparative measures used to differentiate conventional versus computer-assisted delineation are 1) user clock time, and 2) spatial consistency. Our evaluation results with road centerlines demonstrate how such quantitative analyses can be used to determine the utility of computer-assisted methods from both developmental and operational perspectives.