Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. Researchers from UC San Diego developed a new method using a pair of femtosecond mid-infrared and visible excitation pulses to distinguish chromophores, including molecules and quantum dots, that possess nearly identical emission spectra using multiplexed conditions in a three-dimensional space. 

Engineers from UC San Diego have disclosed a new patent-pending technology (SHARP, VERTICALLY ALIGNED NANOWIRE ELECTRODE ARRAYS, HIGH-YIELD FABRICATION ANDINTRACELLULAR RECORDING) that minimizes the electrode size to an intracellular probe, and is scalable to integrate multiple channels at one platform and overcomes the previous disadvantages such as invasiveness and insensitivity. This newly disclosed improved technology reduces the number of steps and the number of metal layers used to increase the biocompatibility and device yield, as compared to an earlier disclosure for NEAs that were fabricated using a different process.

Dynamic Vision Sensors (DVS), also known as event cameras or neuromorphic sensors, enable extremely high temporal resolution and dynamic range compared to traditional sensors. However, DVS pixels only capture changes in intensity, which discards all static information. To overcome this issue, an additional photosensor array is needed either (1) in a two-sensor system or (2) combined into a single sensor with two-pixel technologies (DAVIS346). In both cases, the resulting system is bulkier, more complex to design, and more expensive to manufacture. UC Berkeley researchers have developed an event-based imaging system that can capture static intensity, thereby eliminating the need of such two-pixel technologies by extracting underlying static intensity information directly from DVS pixels. The researchers have also demonstrated the feasibility of this approach through the analysis of noise statistics in event cameras.

Electrical properties (EP), such as permittivity and conductivity, dictate the interactions between electromagnetic waves and biological tissue. EP are biomarkers for pathology characterization, such as cancer. Imaging of EP helps monitor the health of the tissue and can provide important information in therapeutic procedures. Magnetic resonance (MR)-based electrical properties tomography (MR-EPT) uses MR measurements, such as the magnetic transmit field B1+, to reconstruct EP. These reconstructions rely on the calculations of spatial derivatives of the measured B1+. However, the numerical approximation of derivatives leads to noise amplifications introducing errors and artifacts in the reconstructions. Recently, a supervised learning-based method (DL-EPT) has been introduced to reconstruct robust EP maps from noisy measurements. Still, the pattern-matching nature of this method does not allow it to generalize for new samples since the network’s training is done on a limited number of simulated data pairs, which makes it unrealistic in clinical applications. Thus, there is a need for a robust and realistic method for EP map construction.

Researchers at UC Irvine have developed methods to facilitate the delivery of a high dose, low energy electron beam or X-ray in a compact manner.

Common nuclear imaging techniques include computed tomography (CT), single photon emission CT (SPECT), and positron emission tomography (PET). PET differs from other nuclear imaging techniques in that it can visualize both functional and biological activities, including detection of metabolism within human tissues. PET is especially good for imaging patients with cancer, or brain or heart conditions. At low energies, when positrons collide with electrons near the radionuclide decay, Gamma rays (annihilation photons) are created. Gammas originating from the same electron-positron annihilation are generated exclusively in an entangled Bell state. Gammas which do not share an annihilation origin event, such as randoms, are not entangled. Additionally, a gamma which undergoes an internal scatter becomes decoherent (unentangled) from its pair, such as the gammas found in the scattered coincidence pairs. Scattered and random events degrade the image quality. Recently, quantum-based techniques utilizing entanglement of annihilation photons has been recognized as one approach to address scatter and random and to optimize the signal to noise (SNR) ratio.

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High-frequency photoacoustic tomography (> 20 MHz) is becoming increasingly important in biomedical applications. However, it requires data acquisition (DAQ) to have commensurately high sampling rate, which imposes challenges to hardwires and increases the cost of building a PA imaging system. For example, the sampling rate should be higher than 80 MHz to cover 100% bandwidth of a 26-MHz transducer (Nuquist limit). A commercial PA imaging system such as Vevo LAZR X (Fujifilm VISUALSONICS Inc. ON, Canada) with 80-MHz sampling rate can cost more than 990,000$ in the United States.Many PA groups use clinical ultrasound DAQs, which are low cost but also have a low sampling rate, e.g., the iu22 system’s sampling rate is 32 MHz.

Hyperspectral imaging, the practice of capturing detailed spectral (color) information from the output of an optical instrument such as a microscope or telescope, is useful in biological and astronomical research and in manufacturing. In addition to being bulky and expensive, existing hyperspectral imagers typically require scanning across a specimen, limiting temporal resolution and preventing dynamic objects from being effectively imaged. Snapshot methods which eliminate scanning are limited by a tradeoff between spatial and spectral resolution.In order to address these problems, researchers at UC Berkeley have developed a hyperspectral imager which can be attached to the output of any benchtop microscope. The imager is compact (about 6-inches), and can achieve a higher spatial resolution than traditional snapshot imagers. Additionally, this imager needs only one exposure to collect measurements for an arbitrary number of spectral filters, giving it unprecedented spectral resolution.

Dynamic patterning of light is used in a variety of applications in imaging and projection. This is often done by spatial light modulation, in which a coherent beam of input light is modified at the pixel level to create arbitrary output patterns via later interference. Traditional approaches to spatial light modulation suffer from a high operating burden, especially as the number of pixels increases, and incomplete coverage of the optical surface. This results in high device complexity, and cost, as well as enormous real-time computation requirements, reduced optical performance, and optical artifacts.To address these problems, researchers at UC Berkeley have developed a method for wiring groups of pixels, such as annular rings, parallel strips, or radial strips. This takes advantage of the fact that most spatial light modulation tasks can be accomplished by combining a number of simple “primitive phase profiles”, in which not all pixels need be independent of each other. In this co-wiring method, individual optical elements remain at the pixel level, but are wired together in a way that they move in precisely the coordinated manner to produce one of these primitive phase profiles. This allows for high frame rates, high coverage of the optical plane, and a degree of sensitivity impossible to produce with large, geometric optical elements that exist in prior art.

Dynamic patterning of light is used in a variety of applications in imaging and projection. This is often done by spatial light modulation, in which a coherent beam of input light is modified at the pixel level to create arbitrary output patterns via later interference. Traditional approaches to spatial light modulation suffer from a fundamental restriction on frame rate which has led manufacturers to seek the diminishing returns of continually increasing pixel number, resulting in impractical device sizes, complexity, and cost, as well as enormous real-time computation requirements. Additionally, these devices inherently produce monochromatic and speckled frames due to the requirement that the input beam be coherent.To address these problems, researchers at UC Berkeley have developed a device which can perform spatial light modulation with a frame rate ~20 times higher than existing technologies. This allows for a smaller number of pixels to produce high resolution, full color images by interleaving images of different colors and scanning rapidly across a screen in a similar way to the operation of CRT televisions Researchers have also developed an efficient and robust fabrication method, which combined with the smaller pixel number of these devices could cause them to be much more cost effective than existing technologies.

The function of living tissue relies not only on its structure, but crucially on its dynamics at an array of timescales. Structural imaging of biological molecules at very high resolution has become routine in recent years, but these static snapshots provide little insight into the structural changes crucial for biological function. It is well known that changes in the geometry of macromolecules induce fluctuations in the Raman spectrum, but measurements of these fluctuations inherently suffer from poor signal strengths, meaning that dynamics at many timescales are obscured by the time-averaging necessary to obtain sufficient sensitivity.To address these problems, researchers at UC Berkeley have developed a method for probing the Raman spectrum, and hence dynamics of biological molecules at very high sensitivity and across timescales inaccessible to extant techniques. This technique, in fact, can in principle obtain arbitrarily fine spectral and temporal resolution, opening the door to, for example, probe everything from the dynamics of side chain rotations (picoseconds) to protein folding and domain motion (milliseconds).

Measurement of electrical activity in nervous tissue has many applications in medicine, but the implantation of a large number of sensors is traditionally very risky and costly. Devices must be large due to their necessary complexity and power requirements, driving up the risk further and discouraging adoption. To address these problems, researchers at UC Berkeley have developed devices and methods to allow small, very simple and power-efficient sensors to transmit information by backscatter feedback. That is, a much more complex and powerful external interrogator sends an electromagnetic or ultrasound signal, which is modulated by the sensor nodes and reflected back to the interrogator. Machine learning algorithms are then able to map the reflected signals to nervous activity. The asymmetric nature of this process allows most of the complexity to be offloaded to the external interrogator, which is not subject to the same constraints as implanted devices. This allows for larger networks of nodes which can generate higher resolution data at lower risks and costs than existing devices.

Methyl-CpG-binding-protein 2 (MeCP2) is a nuclear protein expressed in all cell types, especially neurons. Mutations in the MECP2 gene cause Rett syndrome (RTT), an incurable neurological disorder that disproportionately affects young girls. Strategies to restore MeCP2 expression phenotypically reverse RTT-like symptoms in male and female MeCP2-deficient mice, suggesting that direct nuclear delivery of functional MeCP2 could restore MeCP2 activity.The inventors have discovered that ZF-tMeCP2, a conjugate of MeCP2(aa13-71, 313-484) and the cell-permeant mini-protein ZF5.3, binds DNA in a methylation-dependent manner and reaches the nucleus of model cell lines intact at concentrations above 700 nM. When delivered to live cells, ZF-tMeCP2 engages the NCoR/SMRT co-repressor complex and selectively represses transcription from methylated promoters. Efficient nuclear delivery of ZF-tMeCP2 relies on a unique endosomal escape portal provided by HOPS-dependent endosomal fusion.In a comparative evaluation, the inventors observed the Tat conjugate of MeCP2 (Tat-tMeCP2) (1) degrades within the nucleus, (2) is not selective for methylated promoters, and (3) traffics in a HOPS-independent manner. These results support the feasibility of a HOPS-dependent portal for delivering functional macromolecules to the cell interior using the cell-penetrant mini-protein ZF5.3. Such a strategy could broaden the impact of multiple families of protein-derived therapeutics.

Plant viral nanoparticles (plant VNPs) are promising biogenetic nanosystems for the delivery of therapeutic, immunotherapeutic, and diagnostic agents. The production of plant VNPs is simple and highly scalable through molecular farming in plants. Some of the important advances in VNP nanotechnology include genetic modification, disassembly/reassembly, and bioconjugation. Although effective, these methods often involve complex and time-consuming multi-step protocols.

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See patent application publication no. US20210282642A16. The present invention is directed to a system for multimodal imaging through the use of a dual-rotational imaging catheter. The system may comprise a swept-source laser for providing a light source for OCT and OCE imaging, and an optical fiber coupler that splits said light source into one for a compensation arm and the other for the imaging catheter. The imaging catheter may comprise a rotary apparatus for a first scanning method, and a distal motor for a second scanning method. The dual-rotational model may allow for optimal performance of multiple imaging modalities. The imaging catheter may utilize optical imaging and acoustic imaging. A balanced photodetector receives input from the destinations of both light sources to offset DC noise. An US pulser/receiver is used for US imaging, a multifunction I/O module, a function generator, and an amplifier are used for generating an acoustic excitation force for OCE imaging.

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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.

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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;}

Researchers from UC San Diego have developed a device that solves all these major limitations. It is a quick, inexpensive, non-radiative, non-invasive,  point-of-care imaging modality.  The inventors created a fast,  point-of-care imaging technique that can image deep within soft tissues. This technique can be used to monitor. wound health over long periods of time.  This ultrasound imaging technology is poised to become a medical imaging tool to measure, and visualize wound size, progression, tunneling, and skin graft integration or rejection.

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Cardiac MRI is the clinical reference standard for visual and quantitative assessment of heart function. Specifically, cine balanced steady-state free precession (SSFP) can yield cardiac images with high myocardium–blood pool contrast for evaluation of left ventricular (LV) function. However, MRI suffers from long acquisition times, often requiring averaging across multiple heartbeats, and necessitates a trade-off among spatial resolution, temporal resolution, and scan time. Clinically, radiologists are forced to balance acquisition time with resolution to fit clinical needs, and certain applications such as real-time imaging may require small acquisition matrices. Image scaling is typically performed by using conventional upscaling methods, such as Fourier domain zero padding and bicubic interpolation. These methods, however, do not readily recover spatial detail, such as the myocardium–blood pool interface or delineation of papillary muscles.