Sample-to-Answer Detection of SARS-CoV-2 Viremia Using Thermally Responsive Alkane Partitions.

The diagnosis of bloodborne viral infections (viremia) is currently relegated to central laboratories because of the complex procedures required to detect viruses in blood samples. The development of point-of-care diagnostics for viremia would enable patients to receive a diagnosis and begin treatment immediately instead of waiting days for results. Point-of-care systems for viremia have been limited by the challenges of integrating multiple precise steps into a fully automated (i.e., sample-to-answer), compact, low-cost system. We recently reported the development of thermally responsive alkane partitions (TRAPs), which enable the complete automation of diagnostic assays with complex samples. Here we report the use of TRAPs for the sample-to-answer detection of viruses in blood using a low-cost portable device and easily manufacturable cassettes. Specifically, we demonstrate the detection of SARS-CoV-2 in spiked blood samples, and we show that our system detects viremia in COVID-19 patient samples with good agreement to conventional RT-qPCR. We anticipate that our sample-to-answer system can be used to rapidly diagnose SARS-CoV-2 viremia at the point of care, leading to better health outcomes for patients with severe COVID-19 disease, and that our system can be applied to the diagnosis of other life-threatening bloodborne viral diseases, including Hepatitis C and HIV.

Sample-to-Answer Immuno-Magnetic Assay Using Thermally Responsive Alkane Partitions.

To combat pandemics, there is a need for rapid point-of-care diagnostics to identify infected patients and to track the spread of the disease. While recent progress has been made in response to COVID-19, there continues to be a need for point-of-care diagnostics capable of detecting biomarkers-such as antibodies-in whole blood. We have recently reported the development of thermally responsive alkane partitions (TRAPs) for the automation of point-of-care immuno-magnetic assays. Here, we demonstrate the use of TRAPs to enable sample-to-answer detection of antibodies against the SARS-CoV-2 virus in whole blood samples. We report a limit of detection of 84 pg/mL, well below the clinically relevant threshold. We anticipate that the TRAP-enabled sample-to-answer immunoassay can be used to track the progression of future pandemics, leading to a more informed and robust clinical and societal response.

Thermally Responsive Alkane Partitions for Assay Automation.

For point-of-care diagnostic tools to be impactful, they must be inexpensive, equipment-free, and sample-to-answer (i.e., require no user intervention). Here, we report a new approach to enable sample-to-answer diagnostics that utilizes thermally responsive alkane partitions (TRAPs) as automated pseudo-valves. When combined with the magnetic manipulation of microbeads, TRAPs enable the pumpless automation of all steps in complex assays. We demonstrate that in relatively narrow channel geometries, liquified alkane partitions continue to separate reagents on each side of the partition while enabling the transition of magnetic beads from one reagent to the next, replacing manual pipetting steps in conventional assays. In addition, we show that in relatively broader geometries, liquified partitions breach, enabling the addition/mixing of preloaded reagents. Through calculation and experimentation, we determine the geometric design rules for implementing the stationary and removable partitions in fluidic channels. In addition, we demonstrate that magnetic microbeads can be pulled through liquified stationary TRAPs without disrupting partition integrity and without disrupting bound protein complexes attached at the microbead surface. The TRAP technology introduced here can enable a new low-cost and equipment-free approach for fully automated sample-to-answer diagnostics.

Indoor Localization of Hand-Held OCT Probe Using Visual Odometry and Real-Time Segmentation Using Deep Learning.

OBJECTIVE: Optical coherence tomography (OCT) is an established medical imaging modality that has found widespread use due to its ability to visualize tissue structures at a high resolution. Currently, OCT hand-held imaging probes lack positional information, making it difficult or even impossible to link a specific image to the location it was originally obtained. In this study, we propose a camera-based localization method to track and record the scanner position in real-time, as well as providing a deep learning-based segmentation method. METHODS: We used camera-based visual odometry (VO) and simultaneous mapping and localization (SLAM) to compute and visualize the location of a hand-held OCT imaging probe. A deep convolutional neural network (CNN) was used for kidney tubule lumens segmentation. RESULTS: The mean absolute error (MAE) and the standard deviation (STD) for 1D translation were found to be 0.15 mm and 0.26mm respectively. For 2D translation, the MAE and STD were found to be 0.85 mm and 0.50 mm, respectively. The dice coefficient of the segmentation method was 0.7. The t-statistic of the T-test between predicted and actual average densities and predicted and actual average diameters were 7.7547e-13 and 2.2288e-15 respectively. We also experimented on a preserved kidney utilizing our localization method with automatic segmentation. Comparisons of the average density maps and average diameter maps were made between the 3D comprehensive scan and VO system scan. CONCLUSION: Our results demonstrate that VO can track the probe location at high accuracy, and provides a user-friendly visualization tool to review OCT 2D images in 3D space. It also indicates that deep learning can provide high accuracy and high speed for segmentation. SIGNIFICANCE: The proposed methods can be potentially used to predict delayed graft function (DGF) in kidney transplantation.

Sample-to-Answer Diagnostic System for the Detection of Circulating Histones in Whole Blood.

Severe internal trauma results in millions of hospitalizations each year, including thousands of deaths caused by subsequent multiple organ failure. The majority of these deaths occur within the first 24 h, and thus, rapid diagnosis of internal trauma severity is necessary for immediate treatment. For early organ damage identification, diagnosis in point-of-care settings is crucial for rapid triage and treatment. Recent reports suggest that circulating histones may serve as a biomarker for severe organ damage and the risk of multiple organ failure. Here, we report a point-of-care diagnostic system that utilizes the inherent interactions between histones and DNA for the fluorescence-based detection of histones in whole blood. In the assay, histones within the sample are wrapped by DNA, thus preventing an intercalating dye from binding the DNA and fluorescing. To allow for quantitative fluorescent measurements to be made in a point-of-care setting, we integrate a rapid, automated blood separation step into our assay. Furthermore, we eliminate manual reagent additions using a thermally responsive alkane partition (TRAP), thus making the system sample-to-answer. Finally, we demonstrate the assay in a portable fluorescence reader compatible with a point-of-care environment. We report a limit of detection 112 ng/mL in whole blood, suggesting that our device can be used to rapidly diagnose internal trauma severity and the likelihood of multiple organ failure in near-patient settings.