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Nanopore Sequencing of RNA Using Reverse Transcription

This invention demonstrates that an engineered cellular reverse transcriptase is a potent motor protein that can processively thread single-stranded RNA (ssRNA) through the MspA biological nanopore in single nucleotide steps while it is synthesizing cDNA. Notably, this represents a first-ever achievement for threading of ssRNA through the engineered Mycobacterium smegmatis porin A (MspA) nanopore in discrete steps, and also for ssRNA sequencing with the MspA nanopore. The inventors constructed the “quadromer map” for ssRNA in the MspA nanopore, which is essentially a table that can convert measured nanopore ion current to RNA sequences, using ssRNAs of known sequences. In addition, the inventors discovered that the single-molecule kinetic rates of the reverse transcriptase are affected by the presence of stable RNA secondary structures. Monitoring this biophysical behavior can be used to determine RNA structures during nanopore sequencing.  Nanopore sequencing is a powerful third generation sequencing technology that offers advantages such as ultra-long read length and direct detection of chemically modified bases. One of the key components of developing a successful nanopore sequencer is identifying potent motor proteins (such as polymerases or helicases) that can thread single-stranded (ss) DNA or ssRNA through the nanopore in discrete steps with high processivity.   

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.

Fetal Oximetry Measurement via Maternal Transabdominal Spectroscopy

Researchers at the University of California, Davis have developed a non-invasive, near-infrared, spectroscopy technique that measures fetal oxygen saturation via the maternal abdomen.

Programmable System that Mixes Large Numbers of Small Volume, High-Viscosity, Fluid Samples Simultaneously

Researchers at the University of California, Davis have developed a programmable machine that shakes and repeatedly inverts large numbers of small containers - such as vials and flasks – in order to mix high-viscosity fluids.

(SD2021-055) Mass Spectrometry-Based Detection of Beta Lactam Hydrolysis Enables Rapid Detection of Beta Lactamase Mediated Antibiotic Resistance

Beta-lactam antibiotics account for the majority of antibiotics used worldwide. Resistance by beta-lactamase expression is a serious and growing threat. The typical workflow in a clinical microbiology laboratory leading to identification of antibiotic resistant organisms consists of 1) sample plating and mixed growth, 2) pathogen isolation and growth, 3) identification of the organism by biochemical tests or  Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF), and finally 4) observed growth in antibiotic containing media to determine antibiotic susceptibility/resistance patterns. This workflow requires 36 to 72 hours, involves multiple manual steps, and may not detect inducible resistance. The evolution and spread of antibiotic resistance among human pathogens represents a serious public health threat. Faster identification of the presence of antibiotic resistant organisms is a key component in the effort to reduce the spread of antibiotic resistance, as evidenced by the inclusion of diagnostic development in the CDC’s national strategy to combat antibiotic resistance. Given the clinical challenges that beta-lactamase expressing pathogens present, there is a clear need for faster identification to both enable effective treatment and to enact isolation precautions preventing further spread of resistant organisms Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

DNN-Assisted Sensor for ECG Monitoring

Inventors at UCI have developed a method of monitoring ECG signals from wearable devices while using artificial intelligence to only select the signals that are relevant to disease for further evaluation.

Hormonal Responsive White Adipose Tissue Micro-Physiological System

The inventors have developed a first-of-its-kind human stem cell-derived metabolically functioning white adipose tissue micro-physiological system (WAT-MPS). The system reconstructs actual physiological circulation and provides a supportive microenvironment that promotes differentiation and maintains long-term cell viability that is superior to traditional tissue culture conditions. Previous studies of stem cell-derived human adipocytes often result in insulin resistant cells due to suboptimal differentiation conditions. The inventors systematically screened key differentiation factors and identified a window of conditions that can create insulin sensitive human adipocytes from mesenchymal and induced pluripotent stem cells without decreasing adipogenesis. To facilitate the rapid and scalable assessment of these human adipocytes, the inventors also optimized an MPS platform that can be used to quantitate insulin responsiveness of adipocytes. This WAT-MPS platform will enable high throughput drug screening for insulin sensitizers, regulators of lipolyisis, and environmental insulin desensitizers, and power personalized medicine approaches to investigate genetic risks of insulin resistance and pharmaco-genetics.   

Technology for Eliminating the False Positive Discovery in Comparative Proteomic

The inventors have developed a technique to improve the accuracy of proteomic analyses by revealing the false positives that are surprisingly common with many methods of comparative proteomics and bio-orthogonal non canonical amino acid tagging (BONCAT). The inventors also describe newly developed methods for minimizing artifacts, including removal of naturally biotinylated proteome, data segmentation with a machine learning algorithm (termed Computer Vision), and employing an optimized digital graphene-based protein biosensor that has ELISA-accuracy.Conventional comparative proteomics and BONCAT are indispensable in various biomedical fields, including aging research, neuroscience, environmental and microbial research, immunology and virology, and cancer research.  

Single Catheter System Combining Intravascular Ultrasound and Fiber-Based Fluorescence Lifetime Imaging

Researchers at the University of California, Davis have developed a catheter device that combines intravascular ultrasound with fluorescence lifetime imaging to better detect significant vascular conditions.

Targeted Identification Of Rna Bases That Hydrogen Bond With Protein

Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} RNA binding proteins are increasingly implicated in genetic and somatic diseases.  Higher resolution methods to identify their RNA targets and how the proteins may interact with specific bases within them are needed to develop drugs that interfere with the regulation or misregulation of RBPs via their binding sites.

Deep Learning Techniques For In Vivo Elasticity Imaging

Imaging the material property distribution of solids has a broad range of applications in materials science, biomechanical engineering, and clinical diagnosis. For example, as various diseases progress, the elasticity of human cells, tissues, and organs can change significantly. If these changes in elasticity can be measured accurately over time, early detection and diagnosis of different disease states can be achieved. Elasticity imaging is an emerging method to qualitatively image the elasticity distribution of an inhomogeneous body. A long-standing goal of this imaging is to provide alternative methods of clinical palpation (e.g. manual breast examination) for reliable tumor diagnosis. The displacement distribution of a body under externally applied forces (or displacements) can be acquired by a variety of imaging techniques such as ultrasound, magnetic resonance, and digital image correlation. A strain distribution, determined by the gradient of a displacement distribution, can be computed (or approximated) from measured displacements. If the strain and stress distributions of a body are both known, the elasticity distribution can be computed using the constitutive elasticity equations. However, there is currently no technique that can measure the stress distribution of a body in vivo. Therefore, in elastography, the stress distribution of a body is commonly assumed to be uniform and a measured strain distribution can be interpreted as a relative elasticity distribution. This approach has the advantage of being easy to implement. The uniform stress assumption in this approach, however, is inaccurate for an inhomogeneous body. The stress field of a body can be distorted significantly near a hole, inclusion, or wherever the elasticity varies. Though strain-based elastography has been deployed on many commercial ultrasound diagnostic-imaging devices, the elasticity distribution predicted based on this method is prone to inaccuracies.To address these inaccuracies, researchers at UC Berkeley have developed a de novo imaging method to learn the elasticity of solids from measured strains. Our approach involves using deep neural networks supervised by the theory of elasticity and does not require labeled data for the training process. Results show that the Berkeley method can learn the hidden elasticity of solids accurately and is robust when it comes to noisy and missing measurements.

Automated Histological Image Processing tool for Identifying and Quantifying Tissue Calcification

Researchers at UCI have developed a method of identifying, quantifying, and visualizing tissue with calcification. The image processing tool can automatically characterize calcium deposits in CT images histological tissue, especially when it has accumulated in unusual places in the body.

Particle-Sorting Device for Isolation, and Enrichment of Particles at Ultra-Low Concentrations

The ability to detect and sort particles by type is important to many fields, such as medical diagnostics, environmental monitoring, and food safety.UCI researchers have developed a platform to sort and isolate particles from a turbid medium with minimal pre-processing. The platform is very desirable for applications in which enrichment of particles or biological substances at low concentrations is necessary.

Low-Dose Ct Perfusion Technique

Coronary atherosclerosis (a thickening of the arterial wall) is correlated to the occurrence of cardiac events; therefore, its correct and early diagnosis is paramount in the prevention and treatment of coronary artery disease. Researchers at UCI have developed an innovative method for assesses coronary artery stenosis and microvascular disease that is both accurate and non-invasive.

New Non-Invasive Markers To Assess Efficacy Of Anti-Integrin Therapies

Inflammatory bowel disease is a chronic disease, which affects the lower bowel parts or the entire GI tract, causing symptoms like abdominal pain, diarrhea, fever and weight loss. An estimated two million people in North America suffer from IBD seemingly caused by an overactive mucosal immune system. Crohn’s Disease and ulcerative colitis (UC) are the major groups of inflammatory conditions that make up IBD and are incurable, serious and chronic organic diseases of the intestinal tract.   Recently, anti-integrin monoclonal antibodies have been approved by the FDA as therapeutic agents for treatment of IBD and there are a number of phase three clinical trials ongoing using monoclonal antibody therapy. The immune system responds to the inflammation that is part of the immunopathology of IBD and acts by recruiting inflammatory cells to the intestinal lesions.  Intergrins, specifically alpha 4-β7, plays a key role in mediating leukocyte trafficking from the circulation to the vascular endothelial barrier in gut-associate lymphoid tissue with the ligand MAdCAM-1. The use of anti-integrin therapy targeting alpha 4-β7 reduces the number of immune cells to the gut endothelium. However, the precise identity of the cell subsets depleted from the intestinal lamina by these anti-integrin drugs have not been identified. Thus, there is an unmet need to further develop tools that allow for the identification of the critical effector cell subsets targeted by these drugs in the intestine.

Imaging Modalities and Methods for Enhanced, Label-free Histopathology During Surgery

Researchers at the University of California, Davis have developed new techniques capable of producing near real-time tissue analysis with quality and accuracy attributes comparable to traditional Haemotoxylin and Eosin (H&E) histopathology methods.

Detecting Cardiovascular Disease Using Noninvasive Imaging of the Eye

Cardiovascular disease is the leading cause of mortality and disability worldwide. It is also prevalent, affecting 9% of the population over 20 years of age. Patients with cardiovascular risk factors can reduce their risk of developing catastrophic cardiovascular events such as heart attack and stroke through lifestyle modification and medications. Unfortunately for many, the disease may go undiagnosed until the occurrence of serious events. Identifying biomarkers of subclinical ischemia can help identify patients with occult cardiovascular disease.

Human-Centered Drug Discovery: A Methodology To Identify And Validate High-Value Therapeutic Targets For Human Diseases

Modeling diseases as networks has helped simplify an otherwise complex web of multi‐cellular processes; however, an exclusive reliance on symmetric relationships in these networks overlooks the existence of disease continuum states and loses information relevant to pathogenesis and for the development of therapeutics. Network‐based analyses severely influenced by symmetric analyses have helped formalize Network Medicine as a field and deliver many successes, but drugs that can predictably re‐set the network in complex multi‐component diseases are yet to emerge.

A Microplatform For Performing High Throughput, Multiplexed Assays On Adherent Cells

Systems and methods are providing for performing high-throughput, programmable, multiplexed assays of biological, chemical or biochemical systems. Preferably, a micro-pallet includes a small flat surface designed for single adherent cells to plate, a cell plating region designed to protect the cells, and shaping designed to enable or improve flow-through operation. The micro-pallet is preferably patterned in a readily identifiable manner and sized to accommodate a single cell to which it is comparable in size. Each cell thus has its own mobile surface. The cell can be transported from place to place and be directed into a system similar to a flow cytometer. Since, since the surface itself may be tagged (e.g., a bar code), multiple cells of different origin and history may be placed into the same experiment allowing multiplexed experiments to be performed.

A Wearable Platform for In-Situ Analysis of Hormones

UCLA researchers in the Department of Electrical and Computer Engineering have developed a highly sensitive, wearable hormone monitoring platform.

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.

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