Deep learning-enabled multiplexed point-of-care sensor using a paper-based fluorescence vertical flow assay

We demonstrate multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) processed by a low-cost mobile reader, which quantifies the target biomarkers through trained neural networks, all within <15 min of test time using 50 microliters of serum sample per patient. This fxVFA platform is validated using human serum samples to quantify three cardiac biomarkers, i.e., myoglobin, creatine kinase-MB (CK-MB) and heart-type fatty acid binding protein (FABP), achieving less than 0.52 ng/mL limit-of-detection for all three biomarkers with minimal cross-reactivity. Biomarker concentration quantification using the fxVFA that is coupled to neural network-based inference is blindly tested using 46 individually activated cartridges, which showed a high correlation with the ground truth concentrations for all three biomarkers achieving > 0.9 linearity and < 15 % coefficient of variation. The competitive performance of this multiplexed computational fxVFA along with its inexpensive paper-based design and handheld footprint make it a promising point-of-care sensor platform that could expand access to diagnostics in resource-limited settings.Comment: 17 Pages, 6 Figure

Surface plasmon resonance analysis of Alzheimer's beta-amyloid aggregation on a solid surface: From monomers to fully-grown fibrils

We analyzed the aggregation of Alzheimer's ??-amyloid (1-42) (A??42) peptides from fresh monomers to fully grown fibrils by using in situ surface plasmon resonance (SPR) spectrometry and ex situ atomic force microscopy (AFM). To immobilize A??42 peptide on an SPR chip surface, different carboxy-terminated surfaces were investigated: (1) self-assembled monolayer of 11-mercaptoundecanoic acid and (2) carboxylated dextran-modified surface. It was found that the carboxylated dextran surface was more appropriate due to a much lower degree of nonspecific binding. By using the carboxylated dextran surface, we further investigated effects of key environmental factors, such as the density of surface-bound A??42, the concentration of A??42 in solution phase, and the presence of Fe3+ ions on A??42 fibrillation. The increase in either the surface density of A??42 or its concentration in incubation solution highly accelerated the formation of amyloid fibrils on the chip surface. The presence of Fe3+ ions in the incubation solution induced significantly denser aggregates, resulting in a nearly 6-fold increase of SPR angle shift. This work shows that SPR analysis coupled with AFM can be effectively used for analyzing amyloid aggregation and deposition on a solid surface from the very beginning to fully grown fibrils.close474

Rapid and Simple Detection of Ochratoxin A using Fluorescence Resonance Energy Transfer on Lateral Flow Immunoassay (FRET-LFI)

The detection of mycotoxins is crucial because of their toxicity in plants, animals, and humans. It is very important to determine whether food products are contaminated with mycotoxins such as ochratoxin A (OTA), as mycotoxins can survive heat treatments and hydrolysis. In this study, we designed a fluorescence resonance energy transfer (FRET)-based system that exploits antibody-antigen binding to detect mycotoxins more rapidly and easily than other currently available methods. In addition, we were able to effectively counteract the matrix effect in the sample by using a nitrocellulose membrane that enabled fluorescence measurement in coffee samples. The developed FRET on lateral flow immunoassay (FRET-LFI) system was used to detect OTA at a limit of detection (LOD) of 0.64 ng∙mL&#8722;1, and the test can be completed in only 30 min. Moreover, OTA in coffee samples was successfully detected at a LOD of 0.88 ng∙mL&#8722;1, overcoming the matrix effect, owing to the chromatographic properties of the capillary force of the membrane. We believe that the developed system can be used as a powerful tool for the sensitive diagnosis of harmful substances such as mycotoxins and pesticides for environmental and food quality control monitoring

Graphene-Based Chemiluminescence Resonance Energy Transfer for Homogeneous Immunoassay

We report on chemiluminescence resonance energy transfer (CRET) between graphene nanosheets and chemiluminescent donors. In contrast to fluorescence resonance energy transfer, CRET occurs <i>via</i> nonradiative dipole–dipole transfer of energy from a chemiluminescent donor to a suitable acceptor molecule without an external excitation source. We designed a graphene-based CRET platform for homogeneous immunoassay of C-reactive protein (CRP), a key marker for human inflammation and cardiovascular diseases, using a luminol/hydrogen peroxide chemiluminescence (CL) reaction catalyzed by horseradish peroxidase. According to our results, anti-CRP antibody conjugated to graphene nanosheets enabled the capture of CRP at the concentration above 1.6 ngmL^–1. In the CRET platform, graphene played a key role as an energy acceptor, which was more efficient than graphene oxide, while luminol served as a donor to graphene, triggering the CRET phenomenon between luminol and graphene. The graphene-based CRET platform was successfully applied to the detection of CRP in human serum samples in the range observed during acute inflammatory stress

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 (&lt;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 &lt; 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 &lt;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

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 $400/test) and extended sample-to-answer timelines (\u3e24 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