Researchers at the University of California, Davis have developed a method to identify vomocytosis events in time-lapse microscopy videos.

Microelectrodes are the gold standard for measuring the activity of individual neurons at high temporal resolution in any nervous system region and central to defining the role of neural circuits in controlling behavior. Microelectrode technologies such as the Utah or Michigan arrays, have allowed tracking of distributed neural activity with millisecond precision. However, their large footprint and rigidity lead to tissue damage and inflammation that hamper long-term recordings. State of the art Neuropixel and carbon fiber probes have improved on these previous devices by increasing electrode density and reducing probe dimensions and rigidity. Although these probes have advanced the field of recordings, next-generation devices should enable targeted stimulation in addition to colocalized electrical recordings. Optogenetic techniques enable high-speed modulation of cellular activity through targeted expression and activation of light-sensitive opsins. However, given the strong light scattering and high absorption properties of neural tissue optogenetic interfacing with deep neural circuits typically requires the implantation of large-diameter rigid fibers, which can make this approach more invasive than its electrical counterpart.Approaches to integrating optical and electrical modalities have ranged from adding fiber optics to existing Utah arrays to the Optetrode or other integrated electro-optical coaxial structures. These technologies have shown great promise for simultaneous electrical recordings and optical stimulation in vivo. However, the need to reduce the device footprint to minimize immune responses for long-term recordings is still present.

A fundamental limitation for the implantable brain-machine interfaces (BMI) is the wiring requirements for power transfer and signal transmission. Microelectrode arrays (MEAs), the workhorse technology in neuroscience, offer multiplexed electrophysiological recordings with high temporal resolution. However, their use is inherently limited to a few hundred electrodes as direct electronic measurements suffer from complex wiring requirements and inherent bandwidth (spatial multiplexing) limitations due to electron-electron interactions within conductors. Moreover, electrode arrays can only record from small sections of the brain and require invasive cranial surgical operations. The recent discovery of genetically encoded voltage sensitive fluorescence indicators (GEVI) has created tremendous excitement as light offers unparalleled multiplexing and information carrying capabilities. However, GEVI cannot be used in humans as it requires expression of voltage sensitive molecules by neurons and therefore genetic manipulation. In addition, attenuation of visible light in biological tissue renders much of the brain inaccessable to fluorescence based techniques.  

Brief description not available

Target biomarkers are often found at low levels (e.g., attomolar to picomolar scale) in the early stages of disease. Current biosensor technologies are limited by their ability to simply and precisely detect target biomarkers at very low concentrations though. Typical biomedical samples, like blood or urine, can also compromise the specificity and sensitivity of common diagnostic platforms without extensive sample processing to remove background contaminants.

The inventors have developed a scalable laser aperture that emits light perpendicular to the surface. The aperture can, in principal, scale to arbitrarily large sizes, offering a universal architecture for systems in need of small, intermediate, or high power. The technology is based on photonic crystal apertures, nanostructured apertures that exhibit a quasi-linear dispersion at the center of the Brillouin zone together with a mode-dependent loss controlled by the cavity boundaries, modes, and crystal truncation. Open Dirac cavities protect the fundamental mode and couple higher order modes to lossy bands of the photonic structure. The technology was developed with an open-Dirac electromagnetic aperture, known as a Berkeley Surface Emitting Laser (BKSEL).  The inventors demonstrate a subtle cavity-mode-dependent scaling of losses. For cavities with a quadratic dispersion, detuned from the Dirac singularity, the complex frequencies converge towards each other based on cavity size. While the convergence of the real parts of cavity modes towards each other is delayed, going quickly to zero, the normalized complex free-spectral range converge towards a constant solely governed by the loss rate of Bloch bands. The inventors show that this unique scaling of the complex frequency of cavity modes in open-Dirac electromagnetic apertures guarantees single-mode operation of large cavities. The technology demonstrates scaled up single-mode lasing, and confirmed from far-field measurements. By eliminating limits on electromagnetic aperture size, the technology will enable groundbreaking applications for devices of all sizes, operating at any power level. BACKGROUND Single aperture cavities are bounded by higher order transverse modes, fundamentally limiting the power emitted by single-mode lasers, as well as the brightness of quantum light sources. Electromagnetic apertures support cavity modes that rapidly become arbitrarily close with the size of the aperture. The free-spectral range of existing electromagnetic apertures goes to zero when the size of the aperture increases. As a result, scale-invariant apertures or lasers has remained elusive until now.  Surface-emitting lasers have advantages in scalability over commercially widespread vertical-cavity surface-emitting lasers (VCSELs). When a photonic crystal is truncated to a finite cavity, the continuous bands break up into discrete cavity modes. These higher order modes compete with the fundamental lasing mode and the device becomes more susceptible to multimode lasing response as the cavity size increases. 

Researchers at the University of California, Davis have developed a large area sensor array for ultrasound imaging systems that utilizes high-bandwidth piezoelectric sensors and modular design elements.

As an important tool for electrophysiological recordings, neural electrodes implanted on the brain surface have been instrumental in basic neuroscience research to study large-scale neural dynamics in various cognitive processes, such as sensorimotor processing as well as learning and memory. In clinical settings, neural recordings have been adopted as a standard tool to monitor the brain activity in epilepsy patients before surgery for detection and localization of epileptogenic zones initiating seizures and functional cortical mapping. Neural activity recorded from the brain surface exhibits rich information content about the collective neural activities reflecting the cognitive states and brain functions. For the interpretation of surface potentials in terms of their neural correlates, most research has focused on local neural activities.   From basic neuroscience research to clinical treatments and neural engineering, electrocorticography (ECoG) has been widely used to record surface potentials to evaluate brain function and develop neuroprosthetic devices. However, the requirement of invasive surgeries for implanting ECoG arrays significantly limits the coverage of different cortical regions, preventing simultaneous recordings from spatially distributed cortical networks. However, this rich information content of surface potentials encoded for the large-scale cortical activity remains unexploited and little is known on how local surface potentials are correlated with the spontaneous neural activities of distributed large-scale cortical networks. 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;}

This technology automates the polymerase chain reaction (PCR) process using digital microfluidics for droplet manipulation. The invention also increases PCR speed and efficiency by combining electrowetting and plasmonic heating in a single device.PCR tests have a wide variety of applications, including the diagnosis of infectious organisms such as viruses and bacterias, as well as cloning, mutagenesis, sequencing, gene expression, and more. The test has become a gold standard for detecting SARS-CoV-2, the virus that causes COVID-19. In the PCR process, a gene or part of the DNA of the infecting organism is amplified exponentially to the extent that it can be detected using conventional methods like gel electrophoresis. This invention addresses the following challenges in current PCR methods: a long sample to answer time; and manual manipulation by humans, which increases the error rate in the tests.  

Our sense of touch is critical for understanding and interacting with the world around us. While interacting with the physical world, force-sensitive mechanoreceptors in the skin respond to various vibrations, motions, pressures, and stretching of the skin to provide us with critical information on the location and magnitude of the stimuli. Thus, if we want the next generation of tactile sensors to emulate how our skin reacts to stimuli, we need to both sense the magnitude and location of contact forces acting on the sensing surface.Contact force is a natural way for humans to interact with the physical world around us. However, most of our interactions with the digital world are largely based on a simple binary sense of touch (contact or no contact). Similarly, when interacting with robots to perform complex tasks, such as surgery, we need to acquire the rich force information and contact location, to aid in the task.

Researchers at the University of California, Davis have developed a device that allows needles to be reliably and easily bent to a range of specified and reproducible angles. The device also enables protection of the needle tip and the maintenance of needle sterility during bending.

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.

Researchers at the University of California, Irvine have fabricated a flexible and unobtrusive wearable electrode that can detect glucose at a very low limit of detection.In fact, the detection limits are the lowest ever reported for an enzyme-free sensor. This sensor is applicable for detecting glucose levels in saliva, sweat or tears, and can safely be used at home, especially by diabetic patients without the need to frequently draw blood.

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.

Researchers from the University of California, Irvine have developed a new method and device to efficiently mix and analyze liquid samples on CD-based point of care devices.

Researchers from the University of California, Irvine have developed a new method and device to efficiently mix and analyze liquid samples on CD-based point of care devices.

UCI researchers developed a percutaneous heart valve delivery system to deliver and implant a prosthetic valve. This system incorporates the means to fracture a previously implanted prosthetic valve in situ without interfering with the transcatheter valve to be implanted.

The enhanced electrochemical activity of nanostructured materials is readily exploited in energy devices, but their utility in scalable and human-compatible implantable neural interfaces can significantly advance the performance of clinical and research electrodes. Traditional biologically inert noble metals such as Pt, Ir or IrPt – are preferential material choices for manufacturing nerve electrodes/ biomedical devices in clinical-relevant applications because of their biocompatibility and stability against corrosion, and because of their superior electrochemical properties compared to other material combinations. But despite these superior properties, the electrochemical interface impedance is not sufficiently low to enable recording minute potential fluctuations with low noise baseline or to efficiently inject charges across the interface without building large voltages across the interface and therefore consuming larger powers per pulse.  As a result, large electrodes are needed to compensate for this large impedance, but large electrodes compromise spatial resolution and specificity for recording and/or stimulation and limit the density and overall number of contacts. To increase the surface area and decrease the electrochemical impedance, nano-structures are often incorporated onto electrode surfaces to enhance their electrochemical properties. Prior work has successfully incorporated nano-structured Pt into electrodes, using electrochemical methods (electro-plating) , but these electrodes suffered from poor structural integrity and physical strength due to incorporation of electrochemical surfactants at the interface between nano-structured Pt and the underlying electrode. Furthermore, common approaches for the fabrication of nano-structured Pt are generally not monolithic and face additional challenges for translation to clinical practice whereas some are also problematic due to the residual of toxic ligand additives remaining after Pt alloy electro-deposition.  

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.

UCI researchers introduced a medical device which simultaneously detects hydrofluoroalkane (HFA), carbon dioxide (CO2), and nitrogen monoxide (NO) in exhaled breath for monitoring and improving treatment of asthma and chronic obstructive pulmonary disease (COPD).

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.

Researchers at UCI have developed an imaging technique that can monitor and measure small mobile structures called cilia in our airways and in the oviduct. This invention will serve as a stepping stone for study of respiratory diseases, oviduct ciliary colonoscopy and future clinical translations.

An improved method for isothermal nucleic acid detection based on a loop mediated isothermal amplification (LAMP) technique that can be broadly applied for nucleic acid diagnostics.LAMP is an isothermal amplification method that amplifies DNA or RNA. This iteration of LAMP allows for the integration of any short DNA sequence, including tags, restriction enzyme sites, or promoters, into an isothermally amplified amplicon. The technique presented by the inventors allows for the insertion of sequence tags up to 35 nt into the flanking regions of the LAMP amplicon using the forward and backward inner primers (FIP and BIP), and loop primers. The inventors have demonstrated insertion of sequence fragments into the 5’ and middle regions of the FIP and BIP primers, and the 5’ region of the loop primers. In some embodiments, the sequence tag comprises a T7 RNA polymerase promoter, which is then incorporated into the LAMP amplicon (termed RT-LAMP/T7). With the addition of T7 polymerase, the amplicon can be in vitro transcribed, leading to additional amplification of the target molecule into an RNA substrate. This improves the efficiency of the amplification reaction and enables substrate conversion into different nucleic acid types.In other embodiments, the amplified RNA sequence can be detected by CRISPR enzymes, such as RNA-targeting Cas13 systems. 

Brief description not available

Researchers in the UCLA Department of Electrical and Computer Engineering have developed a strategy for high-fidelity, wearable biomarker data acquisition and sensor integration with consumer electronics.