Amphiphilic Particle-Stabilized Nanoliter Droplet Reactors with a Multimodal Portable Reader for Distributive Biomarker Quantification.

Compartmentalization, leveraging microfluidics, enables highly sensitive assays, but the requirement for significant infrastructure for their design, build, and operation limits access. Multimaterial particle-based technologies thermodynamically stabilize monodisperse droplets as individual reaction compartments with simple liquid handling steps, precluding the need for expensive microfluidic equipment. Here, we further improve the accessibility of this lab on a particle technology to resource-limited settings by combining this assay system with a portable multimodal reader, thus enabling nanoliter droplet assays in an accessible platform. We show the utility of this platform in measuring N-terminal propeptide B-type natriuretic peptide (NT-proBNP), a heart failure biomarker, in complex medium and patient samples. We report a limit of detection of ∼0.05 ng/mL and a linear response between 0.2 and 2 ng/mL in spiked plasma samples. We also show that, owing to the plurality of measurements per sample, "swarm" sensing acquires better statistical quantitation with a portable reader. Monte Carlo simulations show the increasing capability of this platform to differentiate between negative and positive samples, i.e., below or above the clinical cutoff for acute heart failure (∼0.1 ng/mL), as a function of the number of particles measured. Our platform measurements correlate with gold standard ELISA measurement in cardiac patient samples, and achieve lower variation in measurement across samples compared to the standard well plate-based ELISA. Thus, we show the capabilities of a cost-effective droplet-reader system in accurately measuring biomarkers in nanoliter droplets for diseases that disproportionately affect underserved communities in resource-limited settings.

Monitoring gestational diabetes at the point-of-care via dual glycated albumin lateral flow assays in conjunction with a handheld reader.

Chronic conditions like diabetes require monitoring of vital biomarkers over extended periods of time. Monitoring gestational diabetes mellitus (GDM) is crucial to avoid short- and long-term adverse effects on both mother and infant. Providing monitoring systems to patients at the point-of-care (POC) has the potential to help mitigate these effects. In this manuscript, we propose the use of a sensing system combining lateral flow assays (LFAs) with a handheld colorimetric reader for use in tracking the glycemic status of a GDM patient at the POC. Current strategies of GDM monitoring include glucose and HbA1c measurements. These are often too frequent or not frequent enough for effective monitoring. Hence, we have developed a sensor for an intermediate interval biomarker - glycated albumin (GA). Based on the half-life of the protein, GA is measured once every 2-3 weeks. Here we first present two lateral flow assays, one for GA and another for total serum albumin used in conjunction with a handheld reader to read the colorimetric signals. Both assays have a sandwich aptamer format and measure the target proteins in their physiologically relevant ranges. The GA assay has a dynamic range of 3-20 mg ml-1 and the serum albumin assay has a range of 20-50 mg ml-1 without any sample dilution. Both LFAs were then incorporated into a single dual assay cartridge such that both assays could run simultaneously and provide the % glycated albumin value from a single test. Thus, the dual assay cartridge plus reader system has the potential to provide an effective platform for measuring GA for tracking GDM at the POC.

Sub-picomolar lateral flow antigen detection with two-wavelength imaging of composite nanoparticles.

Lateral flow tests, commonly based on metal plasmonic nanoparticles, are rapid, robust, and low-cost. However, improvements in analytical sensitivity are required to allow detection of low-abundance biomarkers, for example detection of low antigen concentrations for earlier or asymptomatic diagnosis of infectious diseases. Efforts to improve sensitivity often require changes to the assay. Here, we developed optical methods to improve the sensitivity of absorption-based lateral flow tests, requiring no assay modifications to existing tests. We experimentally compared five different lock-in and subtraction-based methods, exploiting the narrow plasmonic peak of gold nanoparticles for background removal by imaging at different light wavelengths. A statistical framework and three fitting models were used to compare limits of detection, giving a 2.0-5.4-fold improvement. We then demonstrated the broad applicability of the method to an ultrasensitive assay, designing 530 nm composite nanoparticles to increase the particle volume, and therefore light absorption per particle, whilst retaining the plasmonic peak to allow background removal and without adding any assay steps. This multifaceted, modular approach gave a combined 58-fold improvement in the fundamental limit of detection using a biotin-avidin model over 50 nm gold nanoparticles with single-wavelength imaging. Applying to a sandwich assay for the detection of HIV capsid protein gave a limit of detection of 170 fM. Additionally, we developed an open-source software tool for performing the detection limit analysis used in this work.

Microplastics retained in stormwater control measures: Where do they come from and where do they go?

Stormwater control measures (SCM) can remove and accumulate microplastics and may serve as a long-term source of microplastics for groundwater pollution because of their potential for downward mobility in subsurface. Furthermore, the number of microplastics accumulated in SCM may have been underestimated as the calculation typically only accounts for microplastics accumulated via episodic stormwater loading and ignores microplastic accumuation via continuous atmospheric deposition. To evaluate the source pathways of accumulated microplastics and their potential for downward mobility to groundwater, we analyzed spatial distributions of microplastics above ground on the canopy around SCM and below ground in the subsurface in and outside the boundaries of fourteen SCM in Los Angeles. Using an exponential model, we link subsurface retardation of microplastics to the median particle size of soil (D50) and land use. Despite receiving significantly more stormwater, microplastic concentrations in SCM at surface depth or subsurface depth were not significantly different from the concentration at the same depth outside the SCM. Similar concentration in and outside of SCM indicates that stormwater is not the sole source of microplastics accumulated in SCM. The high concentration of microplastics on leaves of vegetation in SCM confirms that the contribution of atmospheric deposition is significant. Within and outside the SCM boundary, microplastics are removed within the top 5 cm of the subsurface, and their concentration decreases exponentially with depth, indicating limited potential for groundwater pollution from the microplastics accumulated in SCM. Outside the SCM boundary, the subsurface retardation coefficient decreases with increases in D50, indicating straining of microplastics as the dominant removal mechanism. Inside the boundary of SCM, however, the retardation coefficient was independent of D50, implying that microplastics could have either moved deeper into the filter layer in SCM or that compost, mulch, or organic amendments used in the filter media were pre-contaminated with microplastics. Overall, these results provide insights on microplastics source, accumulation, and downward mobility in SCM.

Sensing of electrolytes in urine using a miniaturized paper-based device.

Analyzing electrolytes in urine, such as sodium, potassium, calcium, chloride, and nitrite, has significant diagnostic value in detecting various conditions, such as kidney disorder, urinary stone disease, urinary tract infection, and cystic fibrosis. Ideally, by regularly monitoring these ions with the convenience of dipsticks and portable tools, such as cellphones, informed decision making is possible to control the consumption of these ions. Here, we report a paper-based sensor for measuring the concentration of sodium, potassium, calcium, chloride, and nitrite in urine, accurately quantified using a smartphone-enabled platform. By testing the device with both Tris buffer and artificial urine containing a wide range of electrolyte concentrations, we demonstrate that the proposed device can be used for detecting potassium, calcium, chloride, and nitrite within the whole physiological range of concentrations, and for binary quantification of sodium concentration.

Automated screening of sickle cells using a smartphone-based microscope and deep learning.

Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited settings, SCD is not consistently diagnosed. In Africa, where the majority of SCD patients reside, more than 50% of the 0.2-0.3 million children born with SCD each year will die from it; many of these deaths are in fact preventable with correct diagnosis and treatment. Here, we present a deep learning framework which can perform automatic screening of sickle cells in blood smears using a smartphone microscope. This framework uses two distinct, complementary deep neural networks. The first neural network enhances and standardizes the blood smear images captured by the smartphone microscope, spatially and spectrally matching the image quality of a laboratory-grade benchtop microscope. The second network acts on the output of the first image enhancement neural network and is used to perform the semantic segmentation between healthy and sickle cells within a blood smear. These segmented images are then used to rapidly determine the SCD diagnosis per patient. We blindly tested this mobile sickle cell detection method using blood smears from 96 unique patients (including 32 SCD patients) that were imaged by our smartphone microscope, and achieved ~98% accuracy, with an area-under-the-curve of 0.998. With its high accuracy, this mobile and cost-effective method has the potential to be used as a screening tool for SCD and other blood cell disorders in resource-limited settings.

Measurement of serum phosphate levels using a mobile sensor.

The measurement of serum phosphate concentration is crucial for patients with advanced chronic kidney disease (CKD) and those on maintenance dialysis, as abnormal phosphate levels may be associated with severe health risks. It is important to monitor serum phosphate levels on a regular basis in these patients; however, such measurements are generally limited to every 0.5-3 months, depending on the severity of CKD. This is due to the fact that serum phosphate measurements can only be performed at regular clinic visits, in addition to cost considerations. Here we present a portable and cost-effective point-of-care device capable of measuring serum phosphate levels using a single drop of blood (<60 µl). This is achieved by integrating a paper-based microfluidic platform with a custom-designed smartphone reader. This mobile sensor was tested on patients undergoing dialysis, where whole blood samples were acquired before starting the hemodialysis and during the three-hour treatment. This sampling during the hemodialysis, under patient consent, allowed us to test blood samples with a wide range of phosphate concentrations, and our results showed a strong correlation with the ground truth laboratory tests performed on the same patient samples (Pearson coefficient r = 0.95 and p < 0.001). Our 3D-printed smartphone attachment weighs about 400 g and costs less than 80 USD, whereas the material cost for the disposable test is <3.5 USD (under low volume manufacturing). This low-cost and easy-to-operate system can be used to measure serum phosphate levels at the point-of-care in about 45 min and can potentially be used on a daily basis by patients at home.

Holographic detection of nanoparticles using acoustically actuated nanolenses.

The optical detection of nanoparticles, including viruses and bacteria, underpins many of the biological, physical and engineering sciences. However, due to their low inherent scattering, detection of these particles remains challenging, requiring complex instrumentation involving extensive sample preparation methods, especially when sensing is performed in liquid media. Here we present an easy-to-use, high-throughput, label-free and cost-effective method for detecting nanoparticles in low volumes of liquids (25 nL) on a disposable chip, using an acoustically actuated lens-free holographic system. By creating an ultrasonic standing wave in the liquid sample, placed on a low-cost glass chip, we cause deformations in a thin liquid layer (850 nm) containing the target nanoparticles (≥140 nm), resulting in the creation of localized lens-like liquid menisci. We also show that the same acoustic waves, used to create the nanolenses, can mitigate against non-specific, adventitious nanoparticle binding, without the need for complex surface chemistries acting as blocking agents.

Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning.

Caused by the tick-borne spirochete Borrelia burgdorferi, Lyme disease (LD) is the most common vector-borne infectious disease in North America and Europe. Though timely diagnosis and treatment are effective in preventing disease progression, current tests are insensitive in early stage LD, with a sensitivity of <50%. Additionally, the serological testing currently recommended by the U.S. Center for Disease Control has high costs (>$400/test) and extended sample-to-answer timelines (>24 h). To address these challenges, we created a cost-effective and rapid point-of-care (POC) test for early-stage LD that assays for antibodies specific to seven Borrelia antigens and a synthetic peptide in a paper-based multiplexed vertical flow assay (xVFA). We trained a deep-learning-based diagnostic algorithm to select an optimal subset of antigen/peptide targets and then blindly tested our xVFA using human samples (N(+) = 42, N(-) = 54), achieving an area-under-the-curve (AUC), sensitivity, and specificity of 0.950, 90.5%, and 87.0%, respectively, outperforming previous LD POC tests. With batch-specific standardization and threshold tuning, the specificity of our blind-testing performance improved to 96.3%, with an AUC and sensitivity of 0.963 and 85.7%, respectively.

Smartphone-based turbidity reader.

Water quality is undergoing significant deterioration due to bacteria, pollutants and other harmful particles, damaging aquatic life and lowering the quality of drinking water. It is, therefore, important to be able to rapidly and accurately measure water quality in a cost-effective manner using e.g., a turbidimeter. Turbidimeters typically use different illumination angles to measure the scattering and transmittance of light through a sample and translate these readings into a measurement based on the standard nephelometric turbidity unit (NTU). Traditional turbidimeters have high sensitivity and specificity, but they are not field-portable and require electricity to operate in field settings. Here we present a field-portable and cost effective turbidimeter that is based on a smartphone. This mobile turbidimeter contains an opto-mechanical attachment coupled to the rear camera of the smartphone, which contains two white light-emitting-diodes to illuminate the water sample, optical fibers to transmit the light collected from the sample to the camera, an external lens for image formation, and diffusers for uniform illumination of the sample. Including the smartphone, this cost-effective device weighs only ~350 g. In our mobile turbidimeter design, we combined two illumination approaches: transmittance, in which the optical fibers were placed directly below the sample cuvette at 180° with respect to the light source, and nephelometry in which the optical fibers were placed on the sides of the sample cuvette at a 90° angle with respect to the to the light source. Images of the end facets of these fiber optic cables were captured using the smart phone and processed using a custom written image processing algorithm to automatically quantify the turbidity of each sample. Using transmittance and nephelometric readings, our mobile turbidimeter achieved accurate measurements over a large dynamic range, from 0.3 NTU to 2000 NTU. The accurate performance of our smartphone-based turbidimeter was also confirmed with various water samples collected in Los Angeles (USA), bacteria spiked water samples, as well as diesel fuel contaminated water samples. Having a detection limit of ~0.3 NTU, this cost-effective smartphone-based turbidimeter can be a useful analytical tool for screening of water quality in resource limited settings.

Computational Image Analysis of Guided Acoustic Waves Enables Rheological Assessment of Sub-nanoliter Volumes.

We present a method for the computational image analysis of high frequency guided sound waves based upon the measurement of optical interference fringes, produced at the air interface of a thin film of liquid. These acoustic actuations induce an affine deformation of the liquid, creating a lensing effect that can be readily observed using a simple imaging system. We exploit this effect to measure and analyze the spatiotemporal behavior of the thin liquid film as the acoustic wave interacts with it. We also show that, by investigating the dynamics of the relaxation processes of these deformations when actuation ceases, we are able to determine the liquid's viscosity using just a lens-free imaging system and a simple disposable biochip. Contrary to all other acoustic-based techniques in rheology, our measurements do not require monitoring of the wave parameters to obtain quantitative values for fluid viscosities, for sample volumes as low as 200 pL. We envisage that the proposed methods could enable high throughput, chip-based, reagent-free rheological studies within very small samples.

Early detection of E. coli and total coliform using an automated, colorimetric and fluorometric fiber optics-based device.

Lack of access to clean water is a major global issue that affects millions of people worldwide. Drinking contaminated water can be extremely hazardous, so it is imperative that it is tested sufficiently. One method commonly used to determine the quality of water is testing for both E. coli and total coliform. Here, we present a cost-effective and automated device which can concurrently test drinking water samples for both E. coli and total coliform using an EPA-approved reagent. Equipped with a Raspberry Pi microcontroller and camera, we perform automated periodic measurements of both the absorption and fluorescence of the water under test over 24 hours. In each test, 100 mL of the water sample is split into a custom designed 40-well plate, where the transmitted blue light and the fluorescent light (under UV excitation) are collected by 520 individual optical fibers. Images of these fiber outputs are then acquired periodically, and digitally processed to determine the presence of the bacteria in each well of the 40-well plate. We demonstrate that this cost-effective device, weighing 1.66 kg, can automatically detect the presence of both E. coli and total coliform in drinking water within ∼16 hours, down to a level of one colony-forming unit (CFU) per 100 mL. Furthermore, due to its automated analysis, this approach is also more sensitive than a manual count performed by an expert, reducing the time needed to determine whether the water under test is safe to drink or not.

Rapid imaging, detection, and quantification of Nosema ceranae spores in honey bees using mobile phone-based fluorescence microscopy.

Recent declines in honey bee colonies in the United States have put increased strain on agricultural pollination. Nosema ceranae and Nosema apis, are microsporidian parasites that are highly pathogenic to honey bees and have been implicated as a factor in honey bee losses. While traditional methods for quantifying Nosema infection have high sensitivity and specificity, there is no field-portable device for field measurements by beekeepers. Here we present a field-portable and cost-effective smartphone-based platform for detection and quantification of chitin-positive Nosema spores in honey bees. The handheld platform, weighing only 374 g, consists of a smartphone-based fluorescence microscope, a custom-developed smartphone application, and an easy to perform sample preparation protocol. We tested the performance of the platform using samples at different parasite concentrations and compared the method with manual microscopic counts and qPCR quantification. We demonstrated that this device provides results that are comparable with other methods, having a limit of detection of 0.5 × 106 spores per bee. Thus, the assay can easily identify infected colonies and provide accurate quantification of infection levels requiring treatment of infection, suggesting that this method is potentially adaptable for diagnosis of Nosema infection in the field by beekeepers. Coupled with treatment recommendations, this protocol and smartphone-based optical platform could improve the diagnosis and treatment of nosemosis in bees and provide a powerful proof-of-principle for the use of such mobile diagnostics as useful analytical tools for beekeepers in resource-limited settings.

Paper-based multiplexed vertical flow assay for point-of-care testing.

We developed a multiplexed point-of-care immunodiagnostic assay for antibody detection in human sera made through the vertical stacking of functional paper layers. In this multiplexed vertical flow immunodiagnostic assay (xVFA), a colorimetric signal is generated by gold nanoparticles captured on a spatially-multiplexed sensing membrane containing specific antigens. The assay is completed in 20 minutes, following which the sensing membrane is imaged by a cost-effective mobile-phone reader. The images are sent to a server, where the results are rapidly analyzed and relayed back to the user. The performance of the assay was evaluated by measuring Lyme-specific antibodies in human sera as model target antibodies. The presented platform is rapid, simple, inexpensive, and allows for simultaneous and quantitative measurement of multiple antibodies and/or antigens making it a suitable point-of-care platform for disease diagnostics.

Ferrodrop Dose-Optimized Digital Quantification of Biomolecules in Low-Volume Samples.

We present an approach to estimate the concentration of a biomolecule in a solution by sampling several nanoliter-scale volumes and determining if the volumes contain any biomolecules. In this method, varying volume fractions (nanoliter-scale) of a sample of nucleic acids are introduced to an array of uniform volume reaction wells (100 µL), which are then fluorescently imaged to determine if signal is above a threshold after nucleic acid amplification, all without complex instrumentation. The nanoliter volumes are generated and introduced using the simple positioning of a permanent magnet, and imaging is performed with a cellphone-based fluorescence detection scheme, both methods suitable for limited-resource settings. We use the length of time a magnetic field is applied to generate a calibrated number of nanoliter ferrodrops of sample mixed with ferrofluid at a step emulsification microfluidic junction. Each dose of ferrodrops is then transferred into larger microliter scale reaction wells on chip through a simple shift of the external magnet. Nucleic acid amplification is achieved using loop-mediated isothermal amplification (LAMP). By repeating each nanoliter dosage a number of times to calculate the probability of a positive signal at each dosage, we can use a binomial probability distribution to estimate the sample nucleic acid concentration. Using this approach we demonstrate detection of lambda DNA molecules down to 25 copies per microliter. The ability to dose separate nanoliter-scale volumes of a low-volume sample across wells in this platform is suited for multiplexed assays. This platform has the potential to be applied to a range of diseases by mixing a sample with magnetic nanoparticles.

Enzyme-Free Nucleic Acid Amplification Assay Using a Cellphone-Based Well Plate Fluorescence Reader.

Nucleic acids, DNA and RNA, provide important fingerprint information for various pathogens and have significant diagnostic value; however, improved approaches are urgently needed to enable rapid detection of nucleic acids in simple point-of-care formats with high sensitivity and specificity. Here, we present a system that utilizes a series of toehold-triggered hybridization/displacement reactions that are designed to convert a given amount of RNA molecules (i.e., the analyte) into an amplified amount of signaling molecules without any washing steps or thermocycling. Fluorescent probes for signal generation were designed to consume products of the catalytic reaction in order to push the equilibrium and enhance the assay fold amplification for improved sensitivity and reaction speed. The system of toehold-assisted reactions is also modeled to better understand its performance and capabilities, and we empirically demonstrate the success of this approach with two analytes of diagnostic importance, i.e., influenza viral RNA and a micro RNA (miR-31). We also show that the amplified signal permits using a compact and cost-effective smartphone-based fluorescence reader, an important requirement toward a nucleic-acid-based point-of-care diagnostic system.

Identification of pathogenic bacteria in complex samples using a smartphone based fluorescence microscope.

Diagnostics based on fluorescence imaging of biomolecules is typically performed in well-equipped laboratories and is in general not suitable for remote and resource limited settings. Here we demonstrate the development of a compact, lightweight and cost-effective smartphone-based fluorescence microscope, capable of detecting signals from fluorescently labeled bacteria. By optimizing a peptide nucleic acid (PNA) based fluorescence in situ hybridization (FISH) assay, we demonstrate the use of the smartphone-based microscope for rapid identification of pathogenic bacteria. We evaluated the use of both a general nucleic acid stain as well as species-specific PNA probes and demonstrated that the mobile platform can detect bacteria with a sensitivity comparable to that of a conventional fluorescence microscope. The PNA-based FISH assay, in combination with the smartphone-based fluorescence microscope, allowed us to qualitatively analyze pathogenic bacteria in contaminated powdered infant formula (PIF) at initial concentrations prior to cultivation as low as 10 CFU per 30 g of PIF. Importantly, the detection can be done directly on the smartphone screen, without the need for additional image analysis. The assay should be straightforward to adapt for bacterial identification also in clinical samples. The cost-effectiveness, field-portability and simplicity of this platform will create various opportunities for its use in resource limited settings and point-of-care offices, opening up a myriad of additional applications based on other fluorescence-based diagnostic assays.

Inkjet-printed point-of-care immunoassay on a nanoscale polymer brush enables subpicomolar detection of analytes in blood.

The ELISA is the mainstay for sensitive and quantitative detection of protein analytes. Despite its utility, ELISA is time-consuming, resource-intensive, and infrastructure-dependent, limiting its availability in resource-limited regions. Here, we describe a self-contained immunoassay platform (the "D4 assay") that converts the sandwich immunoassay into a point-of-care test (POCT). The D4 assay is fabricated by inkjet printing assay reagents as microarrays on nanoscale polymer brushes on glass chips, so that all reagents are "on-chip," and these chips show durable storage stability without cold storage. The D4 assay can interrogate multiple analytes from a drop of blood, is compatible with a smartphone detector, and displays analytical figures of merit that are comparable to standard laboratory-based ELISA in whole blood. These attributes of the D4 POCT have the potential to democratize access to high-performance immunoassays in resource-limited settings without sacrificing their performance.

Evaluation of a Mobile Phone-Based Microscope for Screening of Schistosoma haematobium Infection in Rural Ghana.

AbstractSchistosomiasis affects over 170 million people in Africa. Here we compare a novel, low-cost mobile phone microscope to a conventional light microscope for the label-free diagnosis of Schistosoma haematobium infections in a rural Ghanaian school setting. We tested the performance of our handheld microscope using 60 slides that were randomly chosen from an ongoing epidemiologic study in school-aged children. The mobile phone microscope had a sensitivity of 72.1% (95% confidence interval [CI]: 56.1-84.2), specificity of 100% (95% CI: 75.9-100), positive predictive value of 100% (95% CI: 86.3-100), and a negative predictive value of 57.1% (95% CI: 37.4-75.0). With its modest sensitivity and high specificity, this handheld and cost-effective mobile phone-based microscope is a stepping-stone toward developing a powerful tool in clinical and public health settings where there is limited access to conventional laboratory diagnostic support.