Bingen Cortazar

Cellphone-Based Hand-Held Microplate Reader for Point-of-Care Testing of Enzyme-Linked Immunosorbent Assays

Standard microplate based enzyme-linked immunosorbent assays (ELISA) are widely utilized for various nanomedicine, molecular sensing, and disease screening applications, and this multiwell plate batched analysis dramatically reduces diagnosis costs per patient compared to nonbatched or nonstandard tests. However, their use in resource-limited and field-settings is inhibited by the necessity for relatively large and expensive readout instruments. To mitigate this problem, we created a hand-held and cost-effective cellphone-based colorimetric microplate reader, which uses a 3D-printed opto-mechanical attachment to hold and illuminate a 96-well plate using a light-emitting-diode (LED) array. This LED light is transmitted through each well, and is then collected via 96 individual optical fibers. Captured images of this fiber-bundle are transmitted to our servers through a custom-designed app for processing using a machine learning algorithm, yielding diagnostic results, which are delivered to the user within ∼1 min per 96-well plate, and are visualized using the same app. We successfully tested this mobile platform in a clinical microbiology laboratory using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests using a total of 567 and 571 patient samples for training and blind testing, respectively, and achieved an accuracy of 99.6%, 98.6%, 99.4%, and 99.4% for mumps, measles, HSV-1, and HSV-2 tests, respectively. This cost-effective and hand-held platform could assist health-care professionals to perform high-throughput disease screening or tracking of vaccination campaigns at the point-of-care, even in resource-poor and field-settings. Also, its intrinsic wireless connectivity can serve epidemiological studies, generating spatiotemporal maps of disease prevalence and immunity.

Immunochromatographic Diagnostic Test Analysis Using Google Glass

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health.

Cellphone-based hand-held microplate reader for point-of-care ELISA testing(Conference Presentation)

Enzyme-linked immunosorbent assay (ELISA) in a microplate format has been a gold standard first-line clinical test for diagnosis of various diseases including infectious diseases. However, this technology requires a relatively large and expensive multi-well scanning spectrophotometer to read and quantify the signal from each well, hindering its implementation in resource-limited-settings. Here, we demonstrate a cost-effective and handheld smartphone-based colorimetric microplate reader for rapid digitization and quantification of immunoserology-related ELISA tests in a conventional 96-well plate format at the point of care (POC). This device consists of a bundle of 96 optical fibers to collect the transmitted light from each well of the microplate and direct all the transmission signals from the wells onto the camera of the mobile-phone. Captured images are then transmitted to a remote server through a custom-designed app, and both quantitative and qualitative diagnostic results are returned back to the user within ~1 minute per 96-well plate by using a machine learning algorithm. We tested this mobile-phone based micro-plate reader in a clinical microbiology lab using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests on 1138 remnant patient samples (roughly 50% training and 50% testing), and achieved an overall accuracy of ~99% or higher for each ELISA test. This handheld and cost-effective platform could be immediately useful for large-scale vaccination monitoring in low-infrastructure settings, and also for other high-throughput disease screening applications at POC.

Rapid and sensitive detection of waterborne pathogens using machine learning on a smartphone based fluorescence microscope (Conference Presentation)

Abstract not available.

Field quantification of plant chlorophyll content using Google Glass

Quantification of plant health is crucial for agriculture and can even be used to monitor environmental factors and climate related changes. Plant health is known to be directly related to the chlorophyll content of leaves, which correlates with the capacity of the leaves to transmit or absorb light. The gold-standard method for measuring the chlorophyll concentration of a leaf is based on chemical extraction, which is complex, destructive and time-consuming. As an alternative, here we present a field-portable, cost-effective, and colorimetric method to quantify the chlorophyll content of leaves using Google Glass. For this purpose, we created a custom designed handheld device which is battery-powered and 3D-printed to separately provide uniform illumination of a selected region of interest on the leaf surface using red and white light-emitting-diodes (LEDs). The design of this device minimizes the interference of ambient light conditions to our chlorophyll measurements performed through the Glass camera. We tested this platform by using fifteen randomly selected plant species from UCLA Botanical Garden and imaging fully-grown leaves of these species using Glass. An image-processing algorithm was developed to process the acquired images and obtain the chlorophyll concentration information using the red channel intensities in our region-of-interest for both the white and red LED illumination conditions. The results obtained by this algorithm are in good agreement with the SPAD indices measured for each plant, demonstrating that Google Glass, in combination with our custom-designed illumination platform, can expand its functionality to be used as a chlorophyll meter in field-settings.

Google glass based immunochromatographic diagnostic test analysis

Integration of optical imagers and sensors into recently emerging wearable computational devices allows for simpler and more intuitive methods of integrating biomedical imaging and medical diagnostics tasks into existing infrastructures. Here we demonstrate the ability of one such device, the Google Glass, to perform qualitative and quantitative analysis of immunochromatographic rapid diagnostic tests (RDTs) using a voice-commandable hands-free software-only interface, as an alternative to larger and more bulky desktop or handheld units. Using the built-in camera of Glass to image one or more RDTs (labeled with Quick Response (QR) codes), our Glass software application uploads the captured image and related information (e.g., user name, GPS, etc.) to our servers for remote analysis and storage. After digital analysis of the RDT images, the results are transmitted back to the originating Glass device, and made available through a website in geospatial and tabular representations. We tested this system on qualitative human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) RDTs. For qualitative HIV tests, we demonstrate successful detection and labeling (i.e., yes/no decisions) for up to 6-fold dilution of HIV samples. For quantitative measurements, we activated and imaged PSA concentrations ranging from 0 to 200 ng/mL and generated calibration curves relating the RDT line intensity values to PSA concentration. By providing automated digitization of both qualitative and quantitative test results, this wearable colorimetric diagnostic test reader platform on Google Glass can reduce operator errors caused by poor training, provide real-time spatiotemporal mapping of test results, and assist with remote monitoring of various biomedical conditions.

Google Glass-based Rapid Analysis of Immuno-chromatographic Diagnostic Tests

For rapid, real-time disease diagnostics, we demonstrate the ability of the Google Glass to perform qualitative and quantitative analysis of lateral-flow immuno-chromatographic diagnostic tests.