This dissertation details the development of a portable, low cost lab-on-a-chip flow cytometer and/or fluorescence- activated cell sorter [Mu]FACS), in which microfluidics, micro-acoustics, on-chip optics and electronics are integrated into one tiny polydimethylsiloxane (PDMS) chip creating novel functionalities. This work demonstrates a compact, high-speed sorter, integrated optofluidic waveguides, and a novel color-space-time coding technique for low-cost fluorescence detection. The microfluidic fluorescence-activated cell sorter employs fast-response piezoelectric actuators in conjunction with a high-speed, low timing jitter closed loop control system ensures high purity sorting of targeted biological samples with single- cell manipulation capabilities. By deflecting the entire sub-nanoliter volume of fluid, the [Mu]FACS can sort various biological samples regardless of their physical or chemical properties. A high enrichment factor (>230 fold) is demonstrated at a sorting throughput of greater than 1, 000 cells/sec. By integrating the entire sorting system onto the chip, this technology holds great promise to rapidly become competitive with commercial benchtop sorters. Teflon AF coated optofluidic waveguides demonstrated in this work enhance the coupling efficiency of photons to fluorescent samples, thus increasing sensitivity and permitting multi-spot illumination. The waveguides also enable the space-time coding technology, which works in conjunction with a specially designed spatial filter and the finite-impulse-response (FIR) match filter algorithm in order to further enhance detection sensitivity. The multi-color fluorescence detection technology with an on-chip color filter waveguide array, known as Color-Space-Time (COST) coding, enables the discrimination of up to 11 fluorescent wavelengths using a single photodetector. This novel technology holds great promise for compactness by fundamentally altering the scaling rule; that is the number of bulky optical components required for detection will no longer scale linearly with the number of detection parameters. In this way, the technique can significantly lower the cost and the volume of the whole system in addition to miniaturization of the device. Such a low-cost, compact, portable flow cytometer and [Mu]FACS system can be readily afforded by individual clinics and research labs, providing point-of-care diagnosis and analysis. The development of the microfluidic flow cytometer/[Mu]FACS can improve global quality of life; and while the technology is not fully ready today, great strides have been made towards achieving this goal, as demonstrated in this dissertation

We demonstrate a low-power (<0.1 mW), low-voltage (<10 Vp-p) on-chip piezoelectrically actuated micro-sorter that can deflect single particles and cells at high-speed. With rhodamine in the stream, switching of flow between channels can be visualized at high actuation frequency (~1.7 kHz). The magnitude of the cell deflection can be precisely controlled by the magnitude and waveform of input voltage. Both simulation and experimental results indicate that the drag force imposed on the suspended particle/cell by the instantaneous fluid displacement can alter the trajectory of the particle/cell of any size, shape, and density of interest in a controlled manner. The open-loop E. Coli cell deflection experiment demonstrates that the sorting mechanism can produce a throughput of at least 330 cells/s, with a promise of a significantly higher throughput for an optimized design. To achieve close-loop sorting operation, fluorescence detection, real-time signal processing, and field-programmable-gate-array (FPGA) implementation of the control algorithms were developed to perform automated sorting of fluorescent beads. The preliminary results show error-free sorting at a sorting efficiency of ~70%. Since the piezoelectric actuator has an intrinsic response time of 0.1–1 ms and the sorting can be performed under high flowrate (particle speed of ~1–10 cm/s), the system can achieve a throughput of >1,000 particles/s with high purity.

Although a flow cytometer, being one of the most popular research and clinical tools for biomedicine, can analyze cells based on the cell size, internal structures such as granularity, and molecular markers, it provides little information about the physical properties of cells such as cell stiffness and physical interactions between the cell membrane and fluid. In this paper, we propose a computational cell analysis technique using cells' different equilibrium positions in a laminar flow. This method utilizes a spatial coding technique to acquire the spatial position of the cell in a microfluidic channel and then uses mathematical algorithms to calculate the ratio of cell mixtures. Most uniquely, the invented computational cell analysis technique can unequivocally detect the subpopulation of each cell type without labeling even when the cell type shows a substantial overlap in the distribution plot with other cell types, a scenario limiting the use of conventional flow cytometers and machine learning techniques. To prove this concept, we have applied the computation method to distinguish live and fixed cancer cells without labeling, count neutrophils from human blood, and distinguish drug treated cells from untreated cells. Our work paves the way for using computation algorithms and fluidic dynamic properties for cell classification, a label-free method that can potentially classify over 200 types of human cells. Being a highly cost-effective cell analysis method complementary to flow cytometers, our method can offer orthogonal tests in companion with flow cytometers to provide crucial information for biomedical samples.

Background

Hemodynamic optimization improves postoperative outcomes in high-risk surgery patients. The monitoring of cardiac output (CO) and dynamic parameters of fluid responsiveness can guide hemodynamic optimization. We conducted a survey to assess the current hemodynamic monitoring and management practices of Korean anesthesiologists during high-risk surgery.

Methods

E-mails containing a link to our survey, which consisted of 33 questions relating to hemodynamic monitoring during high-risk surgery, were sent to 3,943 members of the Korean Society of Anesthesiologists (KSA). The survey web page was open from December 30, 2011 to March 31, 2012.

Results

A total of 139 anesthesiologists responded during the survey period. Invasive arterial pressure (97.2%) and central venous pressure (93.4%) were routinely monitored. CO was monitored in 58.5% of patients; stroke volume variations were monitored in 50.9% of patients. However, CO was consistently optimized by < 20% of anesthesiologists. An arterial pressure waveform-derived CO monitor was the most frequently used device to monitor CO (79.0%). Blood pressure, urine output, central venous pressure, and clinical experience were considered to be the best indicators of volume expansion than CO or dynamic parameters of fluid responsiveness.

Conclusions

The survey revealed that KSA members frequently monitor CO and dynamic parameters of fluid responsiveness during high-risk surgery. However, static indices were used more often to judge volume expansion. The current study reveals that CO is not frequently optimized despite the relatively high incidence of CO monitoring during high-risk surgery in Korea.

We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their positions in a solid tissue do not apply. Our design consists of two parts, as follows: recording 3D cell images at high throughput (500 to 1,000 cells/s) using a custom 3D imaging flow cytometer (3D-IFC) and dispensing cells in a first-in-first-out (FIFO) manner using a robotic cell placement platform (CPP). To prevent errors due to violations of the FIFO principle, we invented a method that uses marker beads and DNA sequencing software to detect errors. Experiments with human cancer cell lines demonstrate the feasibility of mapping 3D side scattering and fluorescent images, as well as two-dimensional (2D) transmission images of cells to their locations on the membrane filter for around 100,000 cells in less than 10 min. While the current work uses our specially designed 3D imaging flow cytometer to produce 3D cell images, our methodology can support other imaging modalities. The technology and method form a bridge between single-cell image analysis and single-cell molecular analysis.