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REVEALR Technology for Viral Detection

A novel diagnostic technology offering rapid, accurate, and inexpensive detection, genotyping, and quantification of viral RNA in patient-derived samples, enhancing public health capabilities.

System And Methods For Acoustic Monitoring Of Electron Radiotherapy

A novel technology for real-time, non-invasive monitoring and adaptive control of electron radiotherapy treatments using acoustic signals.

Advanced Vaccine Technology: Lipid Nanoparticle Adjuvants

This technology represents a pioneering approach to vaccine development, focusing on encapsulated adjuvants and antigens to enhance efficacy while minimizing side effects.

Monoclonal Neutralizing Antibodies Specific for Canine TNF Alpha

Researchers at the University of California, Davis have developed monoclonal antibodies engineered for the treatment and detection of autoimmune disorders and cancers in dogs.

AI-Powered Trabecular Meshwork Identification for Glaucoma Surgeries

A revolutionary software that integrates with surgical microscopes to accurately locate the trabecular meshwork (TM), enhancing the safety and efficiency of glaucoma surgeries.

Nanoparticle Therapeutic Vaccines for Cancer Treatment

A cutting-edge vaccine delivery platform that enhances tumor treatment by co-delivering MHC class I and II restricted antigens.

Non-Pharmacological, Neurostimulation Treatment for Hypertension

A groundbreaking non-pharmacological approach to controlling resistant hypertension through personalized, closed-loop neurostimulation.

Method and System for Signal Separation in Wearable Sensors with Limited Data (with Applications to Transabdominal Fetal Oximetry)

Researchers at the University of California, Davis have developed method for separating quasi-periodic mixed-signals using a single data trace, enhancing wearable sensor applications.

Spectral Kernel Machines With Electrically Tunable Photodetectors

       Spectral machine vision collects both the spectral and spatial dependence (x,y,λ) of incident light, containing potentially useful information such as chemical composition or micro/nanoscale structure.  However, analyzing the dense 3D hypercubes of information produced by hyperspectral and multispectral imaging causes a data bottleneck and demands tradeoffs in spatial/spectral information, frame rate, and power efficiency. Furthermore, real-time applications like precision agriculture, rescue operations, and battlefields have shifting, unpredictable environments that are challenging for spectroscopy. A spectral imaging detector that can analyze raw data and learn tasks in-situ, rather than sending data out for post-processing, would overcome challenges. No intelligent device that can automatically learn complex spectral recognition tasks has been realized.       UC Berkeley researchers have met this opportunity by developing a novel photodetector capable of learning to perform machine learning analysis and provide ultimate answers in the readout photocurrent. The photodetector automatically learns from example objects to identify new samples. Devices have been experimentally built in both visible and mid-infrared (MIR) bands to perform intelligent tasks from semiconductor wafer metrology to chemometrics. Further calculations indicate 1,000x lower power consumption and 100x higher speed than existing solutions when implemented for hyperspectral imaging analysis, defining a new intelligent photodetection paradigm with intriguing possibilities.

Ultrafast Light-Induced Inactivation of both Bacteria and Virus based on Bio-Affinity Ligands

Researchers at the University of California, Davis have developed an approach for the rapid inactivation of bacteria and virus using photo-active matrices enhanced with bio-affinity ligands under daylight irradiation conditions.

Tertiary Structure Of The Chlamydia Major Outer Membrane Protein (MOMP)

Researchers at UCI have discovered the tertiary structure of the Chlamydia major outer membrane protein (MOMP). Despite historical challenges in formulating an effective vaccine, recent advancements in understanding MOMP's structure offer new pathways for vaccine development against urogenital and ocular infections caused by C. trachomatis.

Jc071c, a Caninized Monoclonal Antibody Specific for Canine Pd-L1

Researchers at the University of California, Davis, have developed a modified, caninized monoclonal antibody that targets canine PD-L1, developed for use as dog cancer therapy.

Polymeric Vectors For mRNA Delivery

A novel dendronized polypeptide architecture for efficient and safe mRNA delivery, suitable for anti-tumor immunotherapy.

A System And Method For Telerehabilitation

An innovative system designed to enhance rehabilitation therapy for neurological conditions through comprehensive, computer-based solutions.

Device And Method For The Preparation And Operation On Biological Specimen

This device offers a non-invasive solution for treating nasal airway obstructions, significantly improving recovery time and patient outcomes.

Natural Lens Curvature Measurements As A Variable In Calculating Intraocular Lens Power

A novel method for predicting the effective lens position (ELP) in cataract surgery through pre-operative measurements of natural lens curvatures.

Tinnitus Treatment Using Transtympanic Electrical Stimulation

A novel approach to treating tinnitus through electrical stimulation of the inner ear or auditory nerve.

Transabdominal Fetal Oximetry (TFO) for Intrapartum Fetal Health Monitoring

Researchers at the University of California, Davis have developed an innovative technology designed to directly measure fetus blood oxygen saturation level through the maternal abdomen from the onset of labor until birth, thereby improving fetal health outcomes.

In-situ Production of Anti-inflammatory Lipids for Treating Inflammation

Researchers at the University of California, Davis, have developed a process for isolating anti-inflammatory lipids for treating autoimmune and inflammatory diseases.

Systems and Methods of Single-Cell Segmentation and Spatial Multiomics Analyses

Researchers at the University of California, Davis have developed a novel cell segmentation technology for accurate analysis of non-spherical cells and that offers a comprehensive, high-throughput approach for analyzing the transcriptomic and metabolomic data to study complex biological processes at the single-cell level.

Real-Time Antibody Therapeutics Monitoring On An Implantable Living Pharmacy

      Biologics are antibodies produced by genetically engineered cells and are widely used in therapeutic applications. Examples include pembrolizumab (Keytruda) and atezolizumab (Tecentriq), both employed in cancer immunotherapy as checkpoint inhibitors to restore T- cell immune responses against tumor cells. These biologics are produced by engineered cells in bioreactors in a process that is highly sensitive to the bioreactor environment, making it essential to integrate process analytical technologies (PAT) for closed-loop, real-time adjustments. Recent trends have focused on leveraging integrated circuit (IC) solutions for system miniaturization and enhanced functionality, for example enabling a single IC that monitors O2, pH, oxidation-reduction potential (ORP), temperature, and glucose levels. However, no current technology can directly and continuously quantify the concentration and quality of the produced biologics in real-time within the bioreactor. Such critical measurements still rely on off-line methods such as immunoassays and mass spectrometry, which are time-consuming and not suitable for real- time process control.       UC Berkeley researchers have developed a microsystem for real-time, in-vivo monitoring of antibody therapeutics using structure-switching aptamers by employing an integrator-based readout front-end. This approach effectively addresses the challenge of a 100× reduction in signal levels compared to the measurement of small-molecule drugs in prior works. The microsystem is also uniquely suited to the emerging paradigm of “living pharmacies.” In living pharmacies, drug-producing cells will be hosted on implantable devices, and real-time monitoring of drug production/diffusion rates based on an individual’s pharmokinetics will be crucial.

One-step Packaged Multi-mode CMOS Bio-analyzer for Point-of-Care

      Current clinical practice for detecting low-concentration molecular biomarkers requires sending samples to centralized labs, leading to high costs and delays. Successful point-of-care (POC) diagnostic technology exist, such as the paper-based lateral-flow assay (LFA) used for pregnancy tests and SARS-CoV-2 rapid antigen tests, or miniaturized instruments such as the Abbot i-Stat Alinity. However, the former provides binary results or limited quantitative accuracy, and the latter is too expensive for in-home deployment. A promising approach for POC diagnostics, offering tailored circuit optimization, multiplexed detection, and significant cost and size reductions, is millimeter-sized CMOS integrated circuits coupled with microfluidics. Recent demonstrations include protein, DNA/RNA, and cell detection. The current complexity of system packaging (e.g., wire/flip-chip bonding) makes integrating microfluidics with more sophisticated functions challenging, and often-required syringe pumps and tubing are operationally unfriendly, limiting current approaches.       UC Berkeley researchers have developed a fully integrated, multi-mode POC device that requires single-step assembly and operates autonomously. Drawing inspiration from RFID technology and implantables, they have introduced inductively-coupled wireless powering and communication functionality into a CMOS bio-analyzer. With the chip being fully wireless, the die can be easily integrated into a substrate carrier, achieving a completely flat surface that allows for seamless bonding with the microfluidic module. In the final product, the device will be sealed in a pouch inside a vacuum desiccator. The user tears the pouch, adds a drop of sample, and the system automatically begins operation. The operation window can last up to 40 minutes, making the process insensitive to time delays. The present CMOS bio-analyzer integrates pH-sensing and amperometric readout circuits for both proton-based and redox-based immunoassays.

Subtractive Microfluidics in CMOS

      Integrating microelectronics with microfluidics, especially those implemented in silicon-based CMOS technology, has driven the next generation of in vitro diagnostics. CMOS/microfluidics platforms offer (1) close interfaces between electronics and biological samples, and (2) tight integration of readout circuits with multi-channel microfluidics, both of which are crucial factors in achieving enhanced sensitivity and detection throughput. Conventionally bulky benchtop instruments are now being transformed into millimeter-sized form factors at low cost, making the deployment for Point-of-Care (PoC) applications feasible. However, conventional CMOS/microfluidics integration suffers from significant misalignment between the microfluidics and the sensing transducers on the chip, especially when the transducer sizes are reduced or the microfluidic channel width shrinks, due to limitations of current fabrication methods.       UC Berkeley researchers have developed a novel methodology for fabricating microfluidics platforms closely embedded within a silicon chip implemented in CMOS technology. The process utilizes a one-step approach to create fluidic channels directly within the CMOS technology and avoids the previously cited misalignment. Three types of structures are presented in a TSMC 180-nm CMOS chip: (1) passive microfluidics in the form of a micro-mixer and a 1:64 splitter, (2) fluidic channels with embedded ion-sensitive field-effect transistors (ISFETs) and Hall sensors, and (3) integrated on-chip impedance-sensing readout circuits including voltage drivers and a fully differential transimpedance amplifier (TIA). Sensors and transistors are functional pre- and post-etching with minimal changes in performance. Tight integration of fluidics and electronics is achieved, paving the way for future small-size, high-throughput lab-on-chip (LOC) devices.

Machine Learning for Systems Biology Model Determination

A revolutionary method utilizing machine learning to derive systems biology models from experimental data to improve drug discovery and development.

A Multi-Chip Module for Treatment of Ear/Brain Disorders

This unique device delivers electrical stimulation to the inner ear or cranial nerves to treat a panel of ear/brain disorders, including tinnitus.

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