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Templated Synthesis Of Metal Nanorods

Brief description not available

Deep Learning-Based Approach to Accelerate T cell Receptor Design

Researchers at the University of California, Davis have developed a deep learning simulation model to predict mutated T-cell receptor affinity and avidity for immunotherapy applications.

High Accuracy Machine Learning Model for Predicting Liver Cancer Risk

Researchers at the University of California, Davis have developed a method to predict if patients diagnosed with nonalcoholic fatty liver disease are at risk for developing liver cancer using a machine learning algorithm that analyzes a variety of easily available phenotypes and risk factors.

Inter-Brain Measurements for Matching Applications

This technology utilizes inter-subject measurement of brain activity for the purpose of matching individuals. In particular, the invention measures the similarity and differences in neural activity patterns between interacting individuals (either in person or online) as a signature measurement for their matching capabilities. Relevant applications can be in the world of human resources (e.g., building collaborative teams), patient-therapist matching and others. The application relies on the utilization of both custom and commercial devices for measuring brain activity.

At-Home Health Diagnostics Using Face Mask

The inventors propose to collect and detect exhaled breath condensate (EBC) on nanostructured face masks to detect viral infections. Nanofibers can provide more than 100 times the surface area of a conventional mask. With this extensive surface area, nanostructured face masks can collect and accumulate virus with high concentrations without the time/equipment-intense amplification step in RT-PCR or RT-LAMP. By wearing the mask for 6 hours, a person may accumulate 5,400 times more virus than the amount collected in a throat swab specimen. Together, 540,000 times higher virus concentration could be achieved, which is equivalent to 19 cycles in a typical PCR amplification process - the same level as current state-of-art detection schemes for COVID-19 virus.COVID-19 is used here as an example for the possible application of the invention. Over 50% of COVID-19 patients have delayed or no symptoms while they are spreading the virus. Both healthy and symptomless people could easily conduct self-tests at home if there are at-home detection kits. Face masks have become mandatory personal protection equipment (PPE) around the world, and are widely accepted to stop the spread of COVID-19.   

Composition and Methods of a Nuclease Chain Reaction for Nucleic Acid Detection

This invention leverages the nuclease activity of CRISPR proteins for the direct, sensitive detection of specific nucleic acid sequences. This all-in-one detection modality includes an internal Nuclease Chain Reaction (NCR), which possesses an amplifying, feed-forward loop to generate an exponential signal upon detection of a target nucleic acid.Cas13 or Cas12 enzymes can be programmed with a guide RNA that recognizes a desired target sequence, activating a non-specific RNase or DNase activity. This can be used to release a detectable label. On its own, this approach is inherently limited in sensitivity and current methods require an amplification of genetic material before CRISPR-base detection. 

Cellular Potassium Imaging Using A Ratiometric Fluorescent Sensor

The inventors developed a ratiometric fluorescent small molecule probe for potassium ion detection composed of a duo-fluorophore system (KR-1). UV-vis detector and fluorometer measurement support ratiometric response of the probe towards potassium ion concentration. The probe was further applied to cellular potassium level detection using confocal microscope imaging technique. KR-1 enables simple determination of potassium levels in various cancer or non-cancer cell lines.

Identification Of Pan-Cancer Small Cell Neuroendocrine Phenotypes And Vulnerabilities

UCLA researchers in the Department of Molecular and Medical Pharmacology have developed a classifier for the identification and treatment of small cell neuroendocrine cancers and small-round-blue cell tumors not previously identified.

4D-seq: Single Cell RNA-sequencing with in situ Spatiotemporal Information

To develop a novel imaging-based single cell RNA-sequencing (scRNA-Seq) platform that allows capturing of spatiotemporal information and cellular behavior of the sequenced cells within tissue.

DARTS: Deep Learning Augmented RNA-seq Analysis of Transcript Splicing

Researchers led by Yi Xing have developed a novel deep learning algorithm to detect alternative splicing patterns in RNA-seq data

A New Human-Monitor Interface For Interpreting Clinical Images

UCLA researchers in the Department of Radiological Sciences have invented a novel interactive tool that can rapidly focus and zoom on a large number of images using eye tracking technology.

3D Population Maps for Noninvasively Identifying Phenotypes and Pathologies in Individual Patients

UCLA researchers in the Department of Radiological Sciences have developed a novel computation system that uses large imaging datasets to aid in clinical diagnosis and prognosis.

Development Of A Method For Endocrine Network Discovery Uncovers Peptide Therapeutic Targets

UCLA researchers in the Division of Cardiology at the Geffen School of Medicine have developed a bioinformatics methodology to identify and functionally annotate novel endocrine pathways.

High Throughput Digital Cell Quantification Of Immune Cell Subsets Via Epigenetic Markers

UCLA researchers in the Department of Molecular, Cell, and Developmental Biology have developed a novel high-throughput method for the quantification of immune cell subtype.

DNA Methylation Biomarker of Aging for Human Ex Vivo and In Vivo Studies

A UCLA researcher in the Department of Human Genetic and Biostatistics has developed a DNA methylation biomarker for detecting aging in humans.

Lipid-Modified Oligonucleotides For Sample Barcoding in Droplet Microfluidics-Based Single-Cell RNA Sequencing

A new strategy for barcoding single living cells using lipid-modified oligonucleotides that can vastly enhance sample multiplexing in droplet microfluidics-based RNA sequencing

“EchoCV”: A Web-Based Fully Automated Echocardiogram Interpretation System

Echo-CV is a novel, fully-automated system for analyzing images obtained from an echocardiogram that can be deployed on the web.

A Distance-Immune Low-Power Inductively-Coupled Bidirectional Data Link

UCLA researchers in the Department of Electrical Engineering have developed a distance-immune wireless data link for monitoring data in biomedical implants.

Printed All-Organic Reflectance Oximeter Array

A flexible reflectance oximeter array (ROA) composed of printed organic light-emitting diodes (OLEDs) and organic photodiodes (OPDs), which senses reflected light from tissue to determine the oxygen saturation. Since reflected light is used as the signal, the sensor array can be used beyond the conventional sensing locations. We implemented the ROA to measure SpO2 on the forehead with 1.1% mean error and to create two-dimensional (2D) oxygenation maps of the adult forearm under pressure cuff-induced ischemia. Due to the mechanical flexibility, 2D oxygenation mapping capability, and the ability to place the sensor in diverse places, the ROA is promising for novel medical sensing applications such as mapping oxygenation in tissues, wounds, or transplanted organs.

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