The present invention relates autoantibody biomarkers, kits, and methods for increasing the accuracy of a cancer or autoimmune screening of a subject suspected of having cancer or an autoimmune condition.

A lateral flow assay device includes a test strip that is configured to receive a sample fluid and detect a presence of antibodies to one or more of a plurality of proteins of the target pathogen. The lateral flow assay device includes a conjugate pad and a membrane. The conjugate pad contains a plurality of the proteins of the target pathogen, each conjugated with a label. If the sample fluid contains antibodies that are specific to the target pathogen through any of the target pathogen's proteins, a binding takes place between those antibodies and the corresponding tagged protein. The membrane may include a plurality of test lines. Each test line may contain the immobilized binding reagent to one antibody class, resulting in the concentration of all the molecules of that antibody class on the test line.

Described herein are diagnostic and control fusion protein reagents and methods for use thereof in simple rapid and inexpensive hemagglutinin assays for the detection of subject antibodies directed to the SARS-CoV-2 virus.

Protecting information by partitioning data across multiple storage resources. A method includes receiving an image of a test card and an identity of a patient associated with the test card. The method includes associating the image of the test card with the identity of the patient as a data pair on a first storage resource. The method includes providing the image of the test card to a second storage resource by way of a network, wherein the first storage resource is independent of the second storage resource. The method includes receiving a result for the test card and associating the result for the test card with the identity of the patient based on the data pair stored on the first storage resource.

Test cards for agglutination assays, wherein the test cards are configured for computer-implemented image analysis. A test card includes a negative control test region for receiving a negative control fluid sample, a positive control test region for receiving a positive control fluid sample, and a test sample region for receiving a test fluid sample. The test card includes one or more unique scannable codes comprising data for instructing a processor to capture an image of the test card that is suitable for computer-implemented image analysis.

A system for virus detection in a sample from a subject includes a microchip comprising at least one channel containing the sample from the subject and a mobile device. The sample is processed with nanoparticles and a catalyzer that are configured to generate gas bubbles in the presence of a target virus on a surface of the microchip. The mobile device includes a camera configured to acquire an image of the microchip containing the sample from the subject, a neural network configured to receive the acquired image and to generate a probability regarding the presence of the target virus in the sample from the subject based on the acquired image, and a display coupled to the neural network and configured to display the probability regarding presence of the target virus in the sample from the subject.

The disclosure relates to total antibody assays, including screening assays and confirmatory assays, for the detection of anti-AAV (e.g. anti-AAV6) antibodies in a subject as it relates to pre- and post-treatment total antibody levels. The disclosure also relates to methods of treating a subject with a gene therapy comprising a rAAV (e.g. rAAV6) vector.

Machine learning image analysis for quantitative and qualitative analysis of agglutination samples. A method includes receiving an image of an agglutination assay comprising a negative control sample, a positive control sample, and a test sample. The method includes providing the image to a machine learning algorithm trained to classify agglutination of the test sample on a quantitative scale. The machine learning algorithm calibrates the quantitative scale based at least in part on the negative control sample and the positive control sample.

A visibly perceived colorimetric pathogen sensor (100) can comprise a substrate (110) and an molecular recognition group (120) coupled to the substrate (110). The molecular recognition group (120) can be operable to bind to a target pathogen (130). Upon the molecular recognition group (120) binding with the target pathogen (130), reflected light can be altered thereby changing apparent color.

Technologies are described for detecting a pathogen. An example system can include a sensor array (118) having a plurality of sensors that include virus sensors (112) which directly detect a whole vims and at least one of a biomarker sensor, antibody sensor, saturated oxygen sensor, temperature sensor, and heart rate sensor (114a-114n). The system also includes executable instructions that receive sensor output from at least a portion of sensors included in the sensor array (118), assign weights to the sensor output of individual sensors in the sensor array based (118) in part on characteristics of the individual sensors to detect the response signature associated with the pathogen, and determine whether the pathogen has been detected based on the weights assigned to the sensor output of the individual sensors. The system can output (124) an indication whether the pathogen has been detected.