Streak Imaging Flow Cytometer for Rare Cell Analysis.

There is a need for simple and affordable techniques for cytology for clinical applications, especially for point-of-care (POC) medical diagnostics in resource-poor settings. However, this often requires adapting expensive and complex laboratory-based techniques that often require significant power and are too massive to transport easily. One such technique is flow cytometry, which has great potential for modification due to the simplicity of the principle of optical tracking of cells. However, it is limited in that regard due to the flow focusing technique used to isolate cells for optical detection. This technique inherently reduces the flow rate and is therefore unsuitable for rapid detection of rare cells which require large volume for analysis.To address these limitations, we developed a low-cost, mobile flow cytometer based on streak imaging. In our new configuration we utilize a simple webcam for optical detection over a large area associated with a wide-field flow cell. The new flow cell is capable of larger volume and higher throughput fluorescence detection of rare cells than the flow cells with hydrodynamic focusing used in conventional flow cytometry. The webcam is an inexpensive, commercially available system, and for fluorescence analysis we use a 1 W 450 nm blue laser to excite Syto-9 stained cells with emission at 535 nm. We were able to detect low concentrations of stained cells at high flow rates of 10 mL/min, which is suitable for rapidly analyzing larger specimen volumes to detect rare cells at appropriate concentration levels. The new rapid detection capabilities, combined with the simplicity and low cost of this device, suggest a potential for clinical POC flow cytometry in resource-poor settings associated with global health.

A computational streak mode cytometry biosensor for rare cell analysis.

Streak mode imaging flow cytometry for rare cell detection involves imaging moving fluorescently labeled cells in the video mode with a CCD camera. The path of the moving cells results in a "streak", whose length is proportional to the exposure time. The dynamic imaging conditions introduce detection challenges (e.g., images with high signal-to-noise ratio (SNR) backgrounds), especially for enumerating cells using low resolution webcams or smartphone cameras suitable for point of care testing (POCT). To overcome the imaging challenges, a new approach called a "computational biosensor" was developed. It involves combining biosensing hardware with computational algorithms to "computationally transduce" measureable signals from events captured by the hardware. The computational biosensor quantifies potential cells based on the streak intensity, length and relative location of the streaks in consecutive frames. Cell identification consists of three parts: (1) finding streaks, (2) identifying candidate cells, and (3) filtering out spurious cells to identify true cells. Samples of 1 cell per mL were analyzed in batch sizes of 30 mL at flow rates of 10 mL min-1 and imaged at 4 frames per second (fps). The detected cells were annotated, and the SNR was calculated. For images with SNR greater than 4.4 dB, the total detected cells (TD) compared with ground truth (GT) are 98%, while 66% were detected for low SNR. For true positive cells detected compared with ground truth (TP/GT), 91% were detected for high SNR. This demonstrated the new analytical capabilities of the computational biosensor to enumerate rare cells in large volumes not possible with current technologies.

Improving the Sensitivity and Functionality of Mobile Webcam-Based Fluorescence Detectors for Point-of-Care Diagnostics in Global Health.

Resource-poor countries and regions require effective, low-cost diagnostic devices for accurate identification and diagnosis of health conditions. Optical detection technologies used for many types of biological and clinical analysis can play a significant role in addressing this need, but must be sufficiently affordable and portable for use in global health settings. Most current clinical optical imaging technologies are accurate and sensitive, but also expensive and difficult to adapt for use in these settings. These challenges can be mitigated by taking advantage of affordable consumer electronics mobile devices such as webcams, mobile phones, charge-coupled device (CCD) cameras, lasers, and LEDs. Low-cost, portable multi-wavelength fluorescence plate readers have been developed for many applications including detection of microbial toxins such as C. Botulinum A neurotoxin, Shiga toxin, and S. aureus enterotoxin B (SEB), and flow cytometry has been used to detect very low cell concentrations. However, the relatively low sensitivities of these devices limit their clinical utility. We have developed several approaches to improve their sensitivity presented here for webcam based fluorescence detectors, including (1) image stacking to improve signal-to-noise ratios; (2) lasers to enable fluorescence excitation for flow cytometry; and (3) streak imaging to capture the trajectory of a single cell, enabling imaging sensors with high noise levels to detect rare cell events. These approaches can also help to overcome some of the limitations of other low-cost optical detection technologies such as CCD or phone-based detectors (like high noise levels or low sensitivities), and provide for their use in low-cost medical diagnostics in resource-poor settings.

Mobile flow cytometer for mHealth.

Flow cytometry is used for cell counting and analysis in numerous clinical and environmental applications. However flow cytometry is not used in mHealth mainly because current flow cytometers are large, expensive, power-intensive devices designed to operate in a laboratory. Their design results in a lack of portability and makes them unsuitable for mHealth applications. Another limitation of current technology is the low volumetric throughput rates that are not suitable for rapid detection of rare cells.To address these limitations, we describe here a novel, low-cost, mobile flow cytometer based on wide-field imaging with a webcam for large volume and high throughput fluorescence detection of rare cells as a simulation for circulating tumor cells (CTCs) detection. The mobile flow cytometer uses a commercially available webcam capable of 187 frames per second video capture at a resolution of 320 × 240 pixels. For fluorescence detection, a 1 W 450 nm blue laser is used for excitation of Syto-9 fluorescently stained cells detected at 535 nm. A wide-field flow cell was developed for large volume analysis that allows for the linear velocity of target cells to be lower than in conventional hydrodynamic focusing flow cells typically used in cytometry. The mobile flow cytometer was found to be capable of detecting low concentrations at flow rates of 500 µL/min, suitable for rare cell detection in large volumes. The simplicity and low cost of this device suggests that it may have a potential clinical use for mHealth flow cytometry for resource-poor settings associated with global health.

Smartphone-based fluorescence detector for mHealth.

We describe here a compact smartphone-based fluorescence detector for mHealth. A key element to achieving high sensitivity using low sensitivity phone cameras is a capillary array, which increases sensitivity by 100×. The capillary array was combined with a white LED illumination system to enable wide spectra fluorescent excitation in the range of 450-740 nm. The detector utilizes an orthographic projection system to form parallel light projection images from the capillaries at a close distance via an object-space telecentric lens configuration that reduces the total lens-to-object distance while maintaining uniformity in measurement between capillaries. To further increase the limit of detection (LOD), a computational image processing approach was employed to decrease the level of noise. This enables an additional 5-10× decrease in LOD. This smartphone-based detector was used to measure serial dilutions of fluorescein with a LOD of 1 nM with image stacking and 10 nM without image stacking, similar to the LOD obtained with a commercial plate reader. Moreover, the capillary array required a sample volume of less than 10 µl, which is an order of magnitude less than the 100 µl required for the plate reader.As fluorescence detection is widely used in sensitive biomedical assays, the approach described here has the potential to increase mHealth clinical utility, especially for telemedicine and for resource-poor settings in global health applications.

Two-layer Lab-on-a-chip (LOC) with passive capillary valves for mHealth medical diagnostics.

There is a new potential to address needs for medical diagnostics in Point-of-Care (PoC) applications using mHealth (Mobile computing, medical sensors, and communications technologies for health care), a mHealth based lab test will require a LOC to perform clinical analysis. In this work, we describe the design of a simple Lab-on-a-chip (LOC) platform for mHealth medical diagnostics. The LOC utilizes a passive capillary valve with no moving parts for fluid control using channels with very low aspect ratios cross sections (i.e., channel width ≫ height) achieved through transitions in the channel geometry via that arrest capillary flow. Using a CO2 laser in raster engraving mode, we have designed and fabricated an eight-channel LOC for fluorescence signal detection fabricated by engraving and combining just two polymer layers. Each of the LOC channels is capable of mixing two reagents (e.g., enzyme and substrate) for various assays. For mHealth detection, we used a mobile CCD detector equipped with LED multispectral illumination in the red, green, blue, and white range. This technology enables the development of low-cost LOC platforms for mHealth whose fabrication is compatible with standard industrial plastic fabrication processes to enable mass production of mHealth diagnostic devices, which may broaden the use of LOCs in PoC applications, especially in global health settings.

Cell streak imaging cytometry for rare cell detection.

Detection of rare cells, such as circulating tumor cells, have many clinical applications. To measure rare cells with increased sensitivity and improved data managements, we developed an imaging flow cytometer with a streak imaging mode capability. The new streak mode imaging mode utilizes low speed video to capture moving fluorescently labeled cells in a flow cell. Each moving cell is imaged on multiple pixels on each frame, where the cell path is marked as a streak line proportional to the length of the exposure. Finding rare cells (e.g., <1 cell/mL) requires measuring larger sample volumes to achieve higher sensitivity, therefore we combined streak mode imaging with a "wide" high throughput flow cell (e.g. flow rates set to 10 mL/min) in contrast to the conventional "narrow" hydrodynamic focusing cells typically used in cytometry that are inherently limited to low flow rates. The new flow cell is capable of analyzing 20 mL/min of fluorescently labeled cells. To further increase sensitivity, the signal to noise ratio of the images was also enhanced by combining three imaging methods: (1) background subtraction, (2) pixel binning, and (3) CMOS color channel selection. The streaking mode cytometer has been used for the analysis of SYTO-9 labeled THP-1 human monocytes in buffer and in blood. Samples of cells at 1 cell/mL and 0.1 cell/mL were analyzed in 30 mL with flow rates set to 10 mL/min and frame rates of 4 fps (frame per second). For the target of 1 cell/mL, an average concentration of 0.91 cell/mL was measured by cytometry, with a standard error of 0.03 (C(95) = 0.85-0.97). For the target of 0.1 cell/mL, an average concentration of 0.083 cell/mL was measured, with a standard error of 0.01 (C(95) = 0.065-0.102). Whole blood was also spiked with SYTO-9 labeled cells to a concentration of 10 cell/mL, and the average flow cytometry measurement was 8.7 cells/mL (i.e. 0.87 cells/mL in diluted blood) with a 95% CL of 8.1-9.2 cells/mL. This demonstrated the ability to detect rare cells in blood with high accuracy. Such detection approaches for rare cells have many potential clinical applications. Furthermore, the simplicity and low cost of this device may enable expansion of cell-based clinical diagnostics, especially in resource-poor settings.

Webcam-based flow cytometer using wide-field imaging for low cell number detection at high throughput.

Here we describe a novel low-cost flow cytometer based on a webcam capable of low cell number detection in a large volume which may overcome the limitations of current flow cytometry. Several key elements have been combined to yield both high throughput and high sensitivity. The first element is a commercially available webcam capable of 187 frames per second video capture at a resolution of 320 × 240 pixels. The second element in this design is a 1 W 450 nm laser module for area-excitation, which combined with the webcam allows for rapid interrogation of a flow field. The final element is a 2D flow-cell which overcomes the flow limitation of hydrodynamic focusing and allows for higher sample throughput in a wider flow field. This cell allows for the linear velocity of target cells to be lower than in a conventional "1D" hydrodynamic focusing flow-cells typically used in cytometry at similar volumetric flow rates. It also allows cells to be imaged at the full frame rate of the webcam. Using this webcam-based flow cytometer with wide-field imaging, it was confirmed that the detection of fluorescently tagged 5 µm polystyrene beads in "1D" hydrodynamic focusing flow-cells was not practical for low cell number detection due to streaking from the motion of the beads, which did not occur with the 2D flow-cell design. The sensitivity and throughput of this webcam-based flow cytometer was then investigated using THP-1 human monocytes stained with SYTO-9 florescent dye in the 2D flow-cell. The flow cytometer was found to be capable of detecting fluorescently tagged cells at concentrations as low as 1 cell per mL at flow rates of 500 µL min(-1) in buffer and in blood. The effectiveness of detection was concentration dependent: at 100 cells per mL 84% of the cells were detected compared to microscopy, 10 cells per mL 79% detected and 1 cell per mL 59% of the cells were detected. With the blood samples spiked to 100 cells per mL, the average concentration for all samples was 91.4 cells per mL, with a 95% confidence interval of 86-97 cells per mL. These low cell concentrations and the large volume capabilities of the system may overcome the limitations of current cytometry, and are applicable to rare cell (such as circulating tumor cell) detection The simplicity and low cost of this device suggests that it may have a potential use in developing point-of-care clinical flow cytometry for resource-poor settings associated with global health.

Thousand-fold fluorescent signal amplification for mHealth diagnostics.

The low sensitivity of Mobile Health (mHealth) optical detectors, such as those found on mobile phones, is a limiting factor for many mHealth clinical applications. To improve sensitivity, we have combined two approaches for optical signal amplification: (1) a computational approach based on an image stacking algorithm to decrease the image noise and enhance weak signals, and (2) an optical signal amplifier utilizing a capillary tube array. These approaches were used in a detection system which includes multi-wavelength LEDs capable of exciting many fluorophores in multiple wavelengths, a mobile phone or a webcam as a detector, and capillary tube array configured with 36 capillary tubes for signal enhancement. The capillary array enables a ~100× increase in signal sensitivity for fluorescein, reducing the limit of detection (LOD) for mobile phones and webcams from 1000 nM to 10nM. Computational image stacking enables another ~10× increase in signal sensitivity, further reducing the LOD for webcam from 10nM to 1 nM. To demonstrate the feasibility of the device for the detection of disease-related biomarkers, adenovirus DNA labeled with SYBR green or fluorescein was analyzed by both our capillary array and a commercial plate reader. The LOD for the capillary array was 5 ug/mL, and that of the plate reader was 1 ug/mL. Similar results were obtained using DNA stained with fluorescein. The combination of the two signal amplification approaches enables a ~1000× increase in LOD for the webcam platform. This brings it into the range of a conventional plate reader while using a smaller sample volume (10 ul) than the plate reader requires (100 ul). This suggests that such a device could be suitable for biosensing applications where up to 10 fold smaller sample sizes are needed. The simple optical configuration for mHealth described in this paper employing the combined capillary and image processing signal amplification is capable of measuring weak fluorescent signals without the need of dedicated laboratories. It has the potential to be used to increase sensitivity of other optically based mHealth technologies, and may increase mHealth's clinical utility, especially for telemedicine and for resource-poor settings and global health applications.

Orthographic projection capillary array fluorescent sensor for mHealth.

To overcome the limited sensitivity of phone cameras for mobile health (mHealth) fluorescent detection, we have previously developed a capillary array which enables a ∼100 × increase in detection sensitivity. However, for an effective detection platform, the optical configuration must allow for uniform measurement sensitivity between channels when using such a capillary array sensor. This is a challenge due to the parallax inherent in imaging long parallel capillary tubes with typical lens configurations. To enable effective detection, we have developed an orthographic projection system in this work which forms parallel light projection images from the capillaries using an object-space telecentric lens configuration. This optical configuration results in a significantly higher degree of uniformity in measurement between channels, as well as a significantly reduced focal distance, which enables a more compact sensor. A plano-convex lens (f=150 mm) was shown to produce a uniform orthographic projection when properly combined with the phone camera's built in lens (f=4mm), enabling measurements of long capillaries (125 mm) to be made from a distance of 160 mm. The number of parallel measurements which can be made is determined by the size of the secondary lens. Based on these results, a more compact configuration with shorter 32 mm capillaries and a plano-convex lens with a shorter focal length (f=10mm) was constructed. This optical system was used to measure serial dilutions of fluorescein with a limit of detection (LOD) of 10nM, similar to the LOD of a commercial plate reader. However, many plate readers based on standard 96 well plate requires sample volumes of 100 µl for measurement, while the capillary array requires a sample volume of less than 10 µl. This optical configuration allows for a device to make use of the ∼100 × increase in fluorescent detection sensitivity produced by capillary amplification while maintaining a compact size and capability to analyze extremely small sample volumes. Such a device based on a phone or other optical mHealth technology will have the sensitivity of a conventional plate reader but have greater mHealth clinical utility, especially for telemedicine and for resource-poor settings and global health applications.

Capillary Array Waveguide Amplified Fluorescence Detector for mHealth.

Mobile Health (mHealth) analytical technologies are potentially useful for carrying out modern medical diagnostics in resource-poor settings. Effective mHealth devices for underserved populations need to be simple, low cost, and portable. Although cell phone cameras have been used for biodetection, their sensitivity is a limiting factor because currently it is too low to be effective for many mHealth applications, which depend on detection of weak fluorescent signals. To improve the sensitivity of portable phones, a capillary tube array was developed to amplify fluorescence signals using their waveguide properties. An array configured with 36 capillary tubes was demonstrated to have a ~100X increase in sensitivity, lowering the limit of detection (LOD) of mobile phones from 1000 nM to 10 nM for fluorescein. To confirm that the amplification was due to waveguide behavior, we coated the external surfaces of the capillaries with silver. The silver coating interfered with the waveguide behavior and diminished the fluorescence signal, thereby proving that the waveguide behavior was the main mechanism for enhancing optical sensitivity. The optical configuration described here is novel in several ways. First, the use of capillaries waveguide properties to improve detection of weak florescence signal is new. Second we describe here a three dimensional illumination system, while conventional angular laser waveguide illumination is spot (or line), which is functionally one-dimensional illumination, can illuminate only a single capillary or a single column (when a line generator is used) of capillaries and thus inherently limits the multiplexing capability of detection. The planar illumination demonstrated in this work enables illumination of a two dimensional capillary array (e.g. x columns and y rows of capillaries). In addition, the waveguide light propagation via the capillary wall provides a third dimension for illumination along the axis of the capillaries. Such an array can potentially be used for sensitive analysis of multiple fluorescent detection assays simultaneously. The simple phone based capillary array approach presented in this paper is capable of amplifying weak fluorescent signals thereby improving the sensitivity of optical detectors based on mobile phones. This may allow sensitive biological assays to be measured with low sensitivity detectors and may make mHealth practical for many diagnostics applications, especially in resource-poor and global health settings.

Electrical percolation based biosensors.

A new approach to label free biosensing has been developed based on the principle of "electrical percolation". In electrical percolation, long-range electrical connectivity is formed in randomly oriented and distributed systems of discrete elements. By applying this principle to biological interactions, it is possible to measure biological components both directly and electronically. The main element for electrical percolation biosensor is the biological semiconductor (BSC) which is a multi-layer 3-D carbon nanotube-antibody network. In the BSC, molecular interactions, such as binding of antigens to the antibodies, disrupt the network continuity causing increased resistance of the network. BSCs can be fabricated by immobilizing conducting elements, such as pre-functionalized single-walled carbon nanotubes (SWNTs)-antibody complex, directly onto a substrate, such as a Poly(methyl methacrylate) (PMMA) surface (also known as plexi-glass or Acrylic). BSCs have been demonstrated for direct (label-free) electronic measurements of antibody-antigen binding using SWNTs. If the concentration of the SWNT network is slightly above the electrical percolation threshold, then binding of a specific antigen to the pre-functionalized SWNT dramatically increases the electrical resistance due to changes in the tunneling between the SWNTs. Using anti-staphylococcal enterotoxin B (SEB) IgG as a "gate" and SEB as an "actuator", it was demonstrated that the BSC was able to detect SEB at concentrations of 1 ng/ml. Based on this concept, an automated configuration for BSCs is described here that enables real time continuous detection. The new BSC configuration may permit assembly of multiple sensors on the same chip to create "biological central processing units (CPUs)" with multiple biological elements, capable of processing and sorting out information on multiple analytes simultaneously.

Low-cost technologies for medical diagnostics in low-resource settings.

INTRODUCTION: Medical diagnostics is a critical element of effective medical treatment. However, many modern and emerging diagnostic technologies are not affordable or compatible with the needs and conditions found in low- and middle-income countries. Resource-poor countries require low-cost, robust, easy-to-use, and portable diagnostic devices compatible with telemedicine that can be adapted to meet diverse medical needs. AREAS COVERED: The most suitable devices are likely those that will be based on optical technologies, which are used for many types of biological analyses. This manuscript describes several prototypes of low-cost optical technologies and their application developed at the FDA's Office of Science and Engineering laboratories including a webcam-based multiwavelength fluorescence plate reader, a webcam-based fluorescence microscope demonstrated for colonic mucosa tissue pathology analysis, a lens-free optical detector used for the detection of Botulinum A neurotoxin activity, and a lab-on-a-chip which enables the performance of enzyme-linked immunosorbent assay and other immunological or enzymatic assays without the need of dedicated laboratories and complex equipment demonstrated for the detection of the toxin staphylococcal enterotoxin B. EXPERT OPINION: Sensitive and effective optical detection devices can be developed using readily available consumer electronics components such as webcams, charge-coupled device cameras, and LEDs. There are challenges in developing devices with sufficient sensitivity and specificity. Several optical and computational approaches were developed to overcome these challenges to create optical detectors that can serve as low-cost medical diagnostics in resource-poor settings.

Modeling and design of micromachined optical Söller collimators for lensless CCD-based fluorometry.

To address the needs of medical diagnostics in resource-poor settings, it is necessary to develop low cost, simple and portable Point of Care detectors for integrated medical diagnostics. Previously, we have described a simple lensless fluorometer with sensitivity in the range of current ELISA plate readers. The key to the lensfree fluorometer is the uniform spatial distribution of light, which we achieved using a simple optical collimator based on a "stack of pinholes" (a stack of black PMMA plates with arrays of pinholes machined via laser) enabling the light to be collimated from the LED light source through the necessary wavelength filters and the assay's microfluidics directly onto the CCD without a lens. In this paper, we describe the optical principle for designing these Söller collimators for lensfree CCD-based fluorometry. The illuminating surface was modeled as a collection of differential areas emitting uniformly and spherically, and the intensity contribution of each emitting area was summed over the detector surface. To compute the final light intensity distribution from such a differential model we derived an integral equation to sum the individual intensity contributions from the two-dimensional emitting surface. The equation is for a single-hole collimator. Light intensity measurements were taken by placing a collimator with a particular aspect ratio (the ratio of hole length to diameter (L/d)) over the CCD image sensor and capturing an image. The resulting image is the 2D light intensity profile generated by the collimator. As the aspect ratio is increased the slope of the light intensity profile increases, corresponding to an increased degree of collimation. To test the model, the measured maximum and mean light intensities were compared with the theoretical predictions generated from the model. There was an agreement between the variation of the mean (R(2) = 0.990) and maximum (R(2) = 0.938) values of light intensities with aspect ratios based modeling. These profile measurements suggest an excellent agreement with the theoretical predictions. The integral equation presented here can be used to perfect the design of the optical Söller collimator. These results may lead to the development of more effective Söller collimators for lensfree CCD-based fluorometry for use in simple low cost lensfree optical detectors with the potential to enhance the accessibility and the quality of health care for underserved populations.

Image stacking approach to increase sensitivity of fluorescence detection using a low cost complementary metal-oxide-semiconductor (CMOS) webcam.

Optical technologies are important for biological analysis. Current biomedical optical analyses rely on high-cost, high-sensitivity optical detectors such as photomultipliers, avalanched photodiodes or cooled CCD cameras. In contrast, Webcams, mobile phones and other popular consumer electronics use lower-sensitivity, lower-cost optical components such as photodiodes or CMOS sensors. In order for consumer electronics devices, such as webcams, to be useful for biomedical analysis, they must have increased sensitivity. We combined two strategies to increase the sensitivity of CMOS-based fluorescence detector. We captured hundreds of low sensitivity images using a Webcam in video mode, instead of a single image typically used in cooled CCD devices.We then used a computational approach consisting of an image stacking algorithm to remove the noise by combining all of the images into a single image. While video mode is widely used for dynamic scene imaging (e.g. movies or time-lapse photography), it is not used to capture a single static image, which removes noise and increases sensitivity by more than thirty fold. The portable, battery-operated Webcam-based fluorometer system developed here consists of five modules: (1) a low cost CMOS Webcam to monitor light emission, (2) a plate to perform assays, (3) filters and multi-wavelength LED illuminator for fluorophore excitation, (4) a portable computer to acquire and analyze images, and (5) image stacking software for image enhancement. The samples consisted of various concentrations of fluorescein, ranging from 30 µM to 1000 µM, in a 36-well miniature plate. In the single frame mode, the fluorometer's limit-of-detection (LOD) for fluorescein is ∼1000 µM, which is relatively insensitive. However, when used in video mode combined with image stacking enhancement, the LOD is dramatically reduced to 30 µM, sensitivity which is similar to that of state-of-the-art ELISA plate photomultiplier-based readers. Numerous medical diagnostics assays rely on optical and fluorescence readers. Our novel combination of detection technologies, which is new to biodetection may enable the development of new low cost optical detectors based on an inexpensive Webcam (<$10). It has the potential to form the basis for high sensitivity, low cost medical diagnostics in resource-poor settings.

Lensless CCD-based fluorometer using a micromachined optical Söller collimator.

In this paper, we describe a simple charge-coupled device (CCD) based lensless fluorometer with sensitivity in the range of current ELISA plate readers. In our lensfree fluorometer, a multi-wavelength LED light source was used for fluorophore excitation. To collimate the light, we developed a simple optical Söller collimator based on a "stack of pinholes" (a stack of black PMMA with array of pinholes machined with laser) enabling the light to be collimated from the LED through the filters and the assay's microfluidics directly onto the CCD without a lens. The elimination of the lens that is used in almost all other current CCD based detection systems has four major advantages: (1) It simplifies the device design and fabrication while reducing cost. (2) It reduces the distance between the sample and the measuring device (without a lens the distance needed to focus the image on the CCD is reduced and the fluorometer can be more compact). (3) It couples the CCD and the detected surface by using an optical Söller Collimator which allows the use of filters for fluorescence detection. (4) It also uncouples the CCD and the microfluidics to enable the use of interchangeable fluidics while protecting the delicate CCD. The lensless CCD-based fluorometer is capable of detecting 16 samples simultaneously, and was used for in vitro detection of botulinum neurotoxin serotype A (BoNT-A) activity with a FRET assay that measures cleavage of a fluorophore-tagged peptide substrate specific for BoNT-A (SNAP-25) by the toxin light chain (LcA). The limit of detection (LOD) of our lensless fluorometer is 1.25 nM, which is similar to the LOD of a modern ELISA plate reader. Combined with microfluidics, this simple low cost point-of-care (POC) medical diagnostic system may be useful for the performance of many other complex medical diagnostic assays without a laboratory and thus potentially enhancing the accessibility and the quality of health care delivery in underserved populations.

Lab-on-a-chip for label free biological semiconductor analysis of staphylococcal enterotoxin B.

We describe a new lab-on-a-chip (LOC) which utilizes a biological semiconductor (BSC) transducer for label free analysis of Staphylococcal Enterotoxin B (SEB) (or other biological interactions) directly and electronically. BSCs are new transducers based on electrical percolation through a multi-layer carbon nanotube-antibody network. In BSCs the passage of current through the conductive network is dependent upon the continuity of the network. Molecular interactions within the network, such as binding of antigens to the antibodies, disrupt the network continuity causing increased resistance of the network. For the fabrication of a BSC based detector, we combined several elements: (1) BSC transducers for direct detection, (2) LOC for flow through continuous measurements, (3) a digital multimeter with computer connection for data logging, (4) pumps and valves for fluid delivery, and (5) a computer for fluid delivery control and data analysis. Polymer lamination technology was used for the fabrication of a four layer LOC for BSC detection, the BSC on the chip is fabricated by immobilizing pre-functionalized single-walled carbon nanotubes (SWNTs)-antibody complex directly on the PMMA surface of the LOC. SEB samples were loaded into the device using a peristaltic pump and the change in resistance resulting from antibody-antigen interactions was continuously monitored and recorded. Binding of SEB rapidly increases the BSC electrical resistance. SEB in buffer was assayed with limit of detection (LOD) of 5 ng mL(-1) at a signal to baseline (S/B) ratio of 2. A secondary antibody was used to verify the presence of the SEB captured on the surface of the BSC and for signal amplification. The new LOC system permits rapid detection and semi-automated operation of BSCs. Such an approach may enable the development of multiple biological elements "Biological Central Processing Units (CPUs)" for parallel processing and sorting out automatically information on multiple analytes simultaneously. Such an approach has potential use for point-of-care medical and environmental testing.

Electrical percolation-based biosensor for real-time direct detection of staphylococcal enterotoxin B (SEB).

Electrical percolation-based biosensing is a new technology. This is the first report of an electrical percolation-based biosensor for real-time detection. The label-free biosensor is based on electrical percolation through a single-walled carbon nanotubes (SWNTs)-antibody complex that forms a network functioning as a "Biological Semiconductor" (BSC). The conductivity of a BSC is directly related to the number of contacts facilitated by the antibody-antigen "connectors" within the SWNT network. BSCs are fabricated by immobilizing a pre-functionalized SWNTs-antibody complex directly on a poly(methyl methacrylate) (PMMA) and polycarbonate (PC) surface. Each BSC is connected via silver electrodes to a computerized ohmmeter, thereby enabling a continuous electronic measurement of molecular interactions (e.g. antibody-antigen binding) via the change in resistance. Using anti-staphylococcal enterotoxin B (SEB) IgG to functionalize the BSC, we demonstrate that the biosensor was able to detect SEB at concentrations as low as 5 ng/mL at a signal to baseline (S/B) ratio of 2. Such measurements were performed on the chip in wet conditions. The actuation of the chip by SEB is immediate, permitting real-time signal measurements. In addition to this "direct" label-free detection mode, a secondary antibody can be used to "label" the target molecule bound to the BSC in a manner analogous to an immunological sandwich "indirect" detection-type assay. Although a secondary antibody is not needed for direct detection, the indirect mode of detection may be useful as an additional measurement to verify or amplify signals from direct detection in clinical, food safety and other critical assays. The BSC was used to measure SEB both in buffer and in milk, a complex matrix, demonstrating the potential of electrical percolation-based biosensors for real-time label-free multi-analyte detection in clinical and complex samples. Assembly of BSCs is simple enough that multiple sensors can be fabricated on the same chip, thereby creating "Biological Central Processing Units (BCPUs)" capable of parallel processing and sorting out information on multiple analytes simultaneously which may be used for complex analysis and for point of care diagnostics.

Biological semiconductor based on electrical percolation.

We have developed a novel biological semiconductor (BSC) based on electrical percolation through a multilayer three-dimensional carbon nanotube-antibody bionanocomposite network, which can measure biological interactions directly and electronically. In electrical percolation, the passage of current through the conductive network is dependent upon the continuity of the network. Molecular interactions, such as binding of antigens to the antibodies, disrupt the network continuity causing increased resistance of the network. A BSC is fabricated by immobilizing a prefunctionalized single-walled carbon nanotubes (SWNTs)-antibody bionanocomposite directly on a poly(methyl methacrylate) (PMMA) surface (also known as plexiglass or acrylic). We used the BSC for direct (label-free) electronic measurements of antibody-antigen binding, showing that, at slightly above the electrical percolation threshold of the network, binding of a specific antigen dramatically increases the electrical resistance. Using anti-staphylococcal enterotoxin B (SEB) IgG as a "gate" and SEB as an "actuator", we demonstrated that the BSC was able to detect SEB at concentrations of 1 ng/mL. The new BSCs may permit assembly of multiple sensors on the same chip to create "biological central processing units (CPUs)" with multiple BSC elements, capable of processing and sorting out information on multiple analytes simultaneously.