Single-particle/single-molecule tracking (SPT) is a key tool for quantifying molecular motion in cells and in vitro. Wide-field SPT, in particular, can yield super-resolution mapping of physicochemical parameters and molecular interactions at the nanoscale, especially when integrated with single-molecule localization microscopy techniques like photoactivation and fluorophore exchange. However, wide-field SPT is often limited to the slow (<10 μm2/s) diffusion of molecules bound to membranes, chromosomes, or the small volume of bacteria, in part due to the ~10 ms framerate of common single-molecule cameras like electron-multiplying charge-coupled devices (EM-CCDs); for unbound diffusion in the mammalian cell and in solution, a molecule readily diffuses out of the <1 μm focal range of high-numerical-aperture objective lenses within 10 ms. While recent advances such as ultra-highspeed intensified CMOS cameras, feedback control by locking onto a molecule, trapping, and tandem excitation pulse schemes address the framerate issue, each also introduces drawbacks in light/signal efficiency, speed, uninterrupted diffusion paths, and/or trajectory resolution, e.g., number of time points.      UC Berkeley researchers have overcome these myriad challenges by introducing spatially-encoded dynamics tracking (SpeedyTrack), a strategy to enable direct microsecond wide-field single-molecule tracking/imaging on common microscopy setups. Wide-field tracking is achieved for freely diffusing molecules at down to 50 microsecond temporal resolutions for >30 timepoints, permitting trajectory analysis to quantify diffusion coefficients up to 1,000 um2/s. Concurrent acquisition of single-molecule diffusion trajectories and Forster resonance energy transfer (FRET) time traces further elucidates conformational dynamics and binding states for diffusing molecules. Moreover, spatial and temporal information is deconvolved to map long, fast single-molecule trajectories at the super-resolution level, thus resolving the diffusion mode of a fluorescent protein in live cells with nanoscale resolution. Already substantially outperforming existing approaches, SpeedyTrack stands out further for its simplicity—directly working off the built-in functionalities of EM-CCDs without the need to modify existing optics or electronics.

       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.

      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.

      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.

      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.

In magnetic resonance imaging (MRI) scanners, the detection of nuclear magnetic resonance (NMR) signals is achieved using radiofrequency, or RF, coils. RF coils are often equivalently called “resonance coils” due to their circuitry being engineered for resonance at a single frequency being received, for low-noise voltage gain and performance. However, such coils are therefore limited to a small bandwidth around the center frequency, restricting MRI systems from imaging more than one type of nucleus at a time (typically just hydrogen-1, or H1), at one magnetic field strength.To overcome the inherent restriction without sacrificing performance, UC Berkeley researchers have developed an MRI coil that can perform low-noise voltage gain at arbitrary relevant frequencies. These frequencies can be programmably chosen and can include magnetic resonance signals from any of various nuclei (e.g., 1H, 13C, 23Na, 31P, etc.), at any magnetic field strength (e.g., 50 mT, 1.5T, 3T, etc.). The multi-frequency resonance can be performed in a single system. The invention has further advantages in terms of resilience due to its decoupled response relative to other coils and system elements.

      Goniophotometers measure the luminance distribution of light emitted or reflected from a point in space or a material sample. Increasingly there is a need for such measurements in real-time, and in real-world situations, for example, for daylight monitoring or harvesting in commercial and residential buildings, design and optimization of greenhouses, and testing laser and display components for AR/VR and autonomous vehicles, to name a few. However, current goniophotometers are ill-suited for real-time measurements; mechanical scanning goniophotometers have a large form factor and slow acquisition times. Parallel goniophotometers take faster measurements but suffer from complexity, expense, and limited angular view ranges (dioptric angular mapping systems) or strict form factor and sample positioning requirements (catadioptric angular mapping systems). Overall, current goniophotometers are therefore limited to in-lab environments.      To overcome these challenges, UC Berkeley researchers have invented an optical sensor  for parallel goniophotometry that is compact, cost-effective, and capable of real-time daylight monitoring. The novel optical design addresses key size and flexibility constraints of current state-of-the-art catadioptric angular mapping systems, while maximizing the view angle measurement at 90°. This camera-like, angular mapping device could be deployed at many points within a building to measure reflected light from fenestrations, in agricultural greenhouses or solar farms for real-time monitoring, and in any industry benefitting from real-time daylight data.

      Probabilistic Seismic Hazard Analysis (PSHA) has become a foundational method for determining seismic design levels and conducting regional seismic risk analyses for insurance risk analysis, governmental hazard mapping, critical infrastructure planning, and more. PSHA traditionally relies on two computationally intensive approaches: Riemann Sum and conventional Monte Carlo (MC) integration. The former requires fine slices across magnitude, distance, and ground motion, and the latter demands extensive synthetic earthquake catalogs. Both approaches become notably resource intensive for low-probability seismic hazards, where achieving a COV of 1% for a 10−4 annual hazard probability may require 108 MC samples.       UC Berkeley researchers have developed an Adaptive Importance Sampling (AIS) PSHA, a novel framework to approximate optimal importance sampling (IS) distributions and dramatically reduce the number of MC samples to estimate hazards. Efficiency and accuracy of the proposed framework have been validated against Pacific Earthquake Engineering Research Center (PEER) PSHA benchmarks covering various seismic sources, including areal, vertical, and dipping faults, as well as combined types. Seismic hazards are calculated up to 3.7×104 and 7.1×103 times faster than Riemann Sum and traditional MC methods, respectively. Coefficients of variation (COVs) are below 1%. Enhanced “smart” AIS PSHA variants are also available that outperform “smart” implementations of Riemann Sum by a factor of up to 130.

         While nuclear magnetic resonance (NMR) is one of the most universal synthetic chemistry tools for its ability to measure highly specific kinetic and structural information nondestructively/noninvasively, it is costly and low-throughput primarily due to the small sample-size volumes and expensive equipment needed for stringent magnetic field homogeneity. Conversely, zero-to-ultralow field (ZULF) NMR is an emerging alternative offering similar chemical information but relaxing field homogeneity requirements during detection. ZULF NMR has been further propelled by recent advancements in key componentry, optically pumped magnetometers (OPMs), but suffers in scope due to its low sensitivity and its susceptibility to noise. It has not been possible to detect most organic molecules without resorting to hyperpolarization or 13C enrichment using ZULF NMR.         To overcome these challenges, UC Berkeley researchers have developed a multi-channel ZULF spectrometer that greatly improves on both the sensitivity and throughput abilities of state-of-the art ZULF NMR devices. The novel spectrometer was used in the first reported detection of organic molecules in natural isotopic abundance by ZULF NMR, with sensitivity comparable to current commercial benchtop NMR spectrometers. A proof-of-concept multichannel version of the ZULF spectrometer was capable of measuring three distinct chemical samples simultaneously. The combined sensitivity and throughput distinguish the present ZULF NMR spectrometer as a novel chemical analysis tool at unprecedented scales, potentially enabling emerging fields such as robotic chemistry, as well as meeting the demands of existing fields such as chemical manufacturing, agriculture, and pharmaceutical industries.

TnpB protein has generated interest as a potential compact genome-editing tool, due to the short amino acid sequence (408 AAs for ISDra2 TnpB), which overlaps with the wRNA sequence in their genomes of origin. There is a need for compositions and methods that provide more efficient TnpB systems. UC Berkeley researchers have created variant TnpB proteins and variant wRNAs that increase cleavage activity and/or DNA binding activity (e.g., revealed as endonuclease activity such as on-target endonuclease activity). These variant TnpB proteins include an amino acid sequence having one or more amino acid substitutions relative to a corresponding wild type TnpB protein. Also provided are variant TnpB wRNAs that can form a complex with a TnpB protein and a second nucleotide sequence that can hybridize to a target sequence of a target nucleic acid, thereby guiding the complex to the target sequence.

Researchers at UC Berkeley have developed methods to deliver biomolecules to plant cells using new plant-derived cell penetrating peptides (CPPs). Despite the revolution in DNA editing that the last decade has brought, plant genetic engineering has not been able to benefit to the same extent. This is due to certain challenges in plant physiology that limit the delivery of exogenous protein cargos, as required in the CRISPR-Cas9 system, primarily due to the plant cell wall. In mammalian cells, for instance, cargo delivery can be accomplished using cell-penetrating peptides (CPPs) which are short peptides that facilitate the transport of cargo molecules through the plasma membrane to the cytosol. While this technology has been optimized in mammalian cells, few have studied the delivery of CPPs in plants to verify whether the cell wall is permissible to these materials. Another barrier to the use of nanotechnologies for plant biomolecule delivery is the lack of quantitative validation of successful intracellular protein delivery. The near universal dependence on confocal microscopy to validate delivery of fluorescent proxy cargoes can be inappropriate for use in plants due to various physiological plant properties, for example intrinsic autofluorescence of plant tissues. Therefore, there exists an unmet need for new materials and methods to deliver biomolecules to plant cells and to confirm the delivery of proteins of varying sizes into walled plant tissues. Stage of Research The inventors have developed methods to deliver proteins into plant cells using cell penetrating peptides which are appropriate for use with CRISPR-Cas9 technology, siRNAs, zinc-finger nucleases, TALENs, and other DNA editing methods. They have also developed a biomolecule fluorophore-based assay to accurately quantitate protein delivery to plants cells.Stage of DevelopmentResearch - in vitro 

The invention involves compositions and methods that deploy ddhNTPs (deoxy-dihydro-nucleoside triphosphates) as immunomodulatory therapeutics. These tools are designed to modulate P2 receptors, act as nucleotidase inhibitors, and have a wide range of applications including host-acting anti-infectives, oncolytics, anti-aging treatments, tissue regeneration, and green pesticides targeting plant P2K receptors. This invention represents a significant advancement in the field of nucleotide-sensing pathway modulation, offering innovative solutions for both medical and agricultural challenges.

Within the plant kingdom, a wide variety of species possess an extraordinary ability to regenerate whole organs and tissues naturally. Invasive weeds such as Japanese knotweed can regenerate from tiny root fragments in the soil, and many gardeners’ favorites can be propagated by taking cuttings from fully-grown plants. However, this flexible ability to regenerate organs is missing from most economically important crop species, and is currently the single biggest bottleneck for plant biotechnology.  While there is an increasingly impressive array of tools to edit the genes of a plant cell, regenerating whole organs and body plans from edited cells via labor-intensive tissue culture remains a painstaking process – often requiring a year or more – and resulting in undesirable mutations and chromosome instability.  UCB researchers have discovered that complete genetic knockout of the DNA demethylation pathway in the model plant Arabidopsis dramatically enhances the ability of plant organs to regenerate after wounding. In many plants, including Arabidopsis, regeneration after wounding does not occur naturally and requires intensive tissue culture. By contrast, quadruple homozygous mutant plants harboring loss of function mutations to all four DNA demethylase enzymes capably regenerate all organs and complete body plans after cutting, even in the absence of exogenous plant hormones and tissue culture. 

Gallium nitride is an essential semiconductor material that has shown great promise in electronic and optoelectronic applications. Its synthesis traditionally requires high temperatures (~300-1000℃) and/or pressures (~1-100MPa) in order to break the strong bond in molecular nitrogen. Manufacture of gallium nitride and similar semiconductor materials under these conditions is very expensive. Additionally, artificial nitrogen fixation in the form of ammonia manufacture is critical to the global food supply, but similarly requires very expensive high temperature and/or pressure synthesis. To address these problems, researchers at UC Berkeley have developed a method to synthesize gallium nitride from molecular nitrogen at approximately room temperature (30℃) and atmospheric pressure. This process can be accomplished more cheaply than traditional methods, using only standard reagents and equipment. Researchers have confirmed that prior to the synthesis of gallium nitride, atomic nitrogen is freely dissociated. This suggests that a similar method can be used in the manufacture of other nitride semiconductor materials, or even of nitrogenous substances such as ammonia.

The inventors have developed an engineering approach to identify novel and nonobvious membrane-associated accessory protein (MAAP) sequence variants that confer increased Adeno-associated virus (AAV) secretion during packaging. The technique is based upon the iterative process of sequence diversification and selection of functional gene variants known as directed evolution. First, the inventors generated a library of more than 1E6 MAAP variants. The variants were subjected to five rounds of packaging into an AAV2 capsid for which MAAP expression was inactivated without altering the viral protein VP1 open reading frame (ORF) (AAV2-MAAP-null). Among each iterative packaging round, the inventors observed a progressive increase in both the overall titer and ratio of secreted vector genomes conferred by the bulk selected MAAP library population. Next-generation sequencing uncovered common mutational features that were enriched up to over 10,000-fold on the amino acid level. Individual MAAP variants were isolated and systematically tested for effect on recombinant AAV2-MAAP-null packaging in HEK293 cells. The inventors predict that this work may be applicable to increasing per-cell AAV output in industrial settings, potentially reducing global costs and increasing functional vector recovery in downstream manufacturing processes.BACKGROUNDParvoviruses are small, single-stranded DNA viruses that are ubiquitously found in many animal species. AAV is a prototypic dependoparvovirus whose replication cycle requires the function of helper genes from larger co-infected viruses such as Adenoviruses or Herpesviruses. The natural genome of AAV contains ~4.7 kb of ssDNA that encodes up to ten known proteins in a highly overlapped fashion. The rep gene encodes four protein products named based on their molecular weight: Rep72 and Rep68 facilitate genomic replication, whereas Rep52, and Rep40 play essential roles in loading nascent ssDNA genomes into assembled capsids. Downstream of rep lies the cap gene, which encodes three known protein products off of overlapping reading frames: VP1, VP2, and VP3 are structural proteins that assemble to form the capsid, the assembly activating protein (AAP) targets VP proteins to the nucleus and is involved in capsid assembly. The most recently discovered AAV-encoded gene is the membrane-associated accessory protein (MAAP). MAAP is encoded by an alternative ORF in the AAV cap gene that is found in all presently reported natural serotypes. Gene delivery by recombinant AAV (rAAV) have shown significant success in both research and clinical gene therapy applications. In the rAAV system, Rep and Cap are removed from between AAV’s 5’ and 3’ inverted terminal repeats (ITRs) and provided in trans. Instead, a transgene of interest is inserted between the ITRs and subsequently packaged into the nascent AAV capsids. However, manufacturing quantities of good manufacturing practice (GMP)-grade rAAVs necessary to achieve current and projected dosing requirements–particularly in a clinical context–presents a significant hurdle to expanding rAAV-based gene therapies. Recently, evidence has emerged supporting a functional role of MAAP in AAV egress. This led to the hypothesis that MAAP could be engineered to facilitate increased levels of secreted AAV produced from HEK293 cells. 

Plants rely on systemic signaling mechanisms to establish whole-plant defense in response to insect and nematode attack. The Glutamate receptor-like (GLR) genes have been implicated in long-distance propagation of wound signals to initiate accumulation of defense hormone jasmonate (JA) at undamaged distal sites.UCB researchers have shown the ability to desensitize GLR channels, providing a potential target for engineering anti-herbivore defense in crops.

In this technology, the inventors introduce additives to purposely change the morphology of polycaprolactone (PCL) by increasing the bending and twisting of crystalline lamellae. These morphological changes immobilize chain-ends preferentially at the crystalline/amorphous interfaces and limit chain-end accessibility by the embedded processive enzyme. This chain end redistribution reduces the polymer-to-monomer conversion from >95% to less than 50%, causing formation of highly crystalline plastic pieces including microplastics. By synergizing both random chain scission and processive depolymerization, it is feasible to navigate morphological changes in polymer/additive blends and to achieve near complete depolymerization. The random scission enzymes in the amorphous domains create new chain ends that are subsequently bound and depolymerized by processive enzymes. Present studies further highlight the importance to consider host polymer morphological effects on the reactions catalyzed by embedded catalytic species.This is part of a patent family in compostable plastics.  

UC researchers have discovered a novel use of proteins denoted CasLamda/Cas12L within the Type V CRISPR Cas superfamily distantly related to CasX, CasY and other published type V sequences.  These CasLamda/Cas12L proteins utilize a guide RNA to perform RNA-directed cleavage of DNA.  The researchers have developed compounds and structures for use in in editing plant cells.

The inventors have developed ion-selective potentiometric sensors for monitoring soil analytes with naturally degradable substrate, conductor, electrode, and encapsulant materials that minimize pollution and ecotoxicity. This novel sensor-creation method uses printing technologies for the measurement of nitrate, ammonium, sodium, calcium, potassium, phosphate, nitrite, and others. Monitoring soil analytes is key to precision agriculture and optimizing the health and growth of plant life. 

In developed countries, buildings demand a large percentage of a region's energy-generating requirements. This has led to an urgent need for efficient buildings with reduced energy requirements. In office buildings, lighting takes up 20% to 45% of the total energy consumption. Furthermore, the adoption of smart lighting control strategies such as daylight harvesting is shown to reduce lighting energy use by 30% to 50%.For most closed-loop lighting control systems, the real-time data of the daylight level at areas of interest (e.g., the office workbench) are the most important inputs. Current state-of-the-art solutions use dense arrays of luxmeters (photosensors) to monitor the daylight environment inside buildings. The luxmeters are placed on either workbenches, or ceilings and walls near working areas. Digital cameras are used in controlled laboratory environments and occasionally in common buildings to evaluate glare resulting from excessive daylight. The disadvantage of these sensor-based approaches is that they're expensive to install and commission. Additionally, the sample area of these sensors is limited to either the area of the luxmeters or the view of the cameras. Consequently, many sensors are needed to measure the daylight in a large office space.To address this situation, researchers at UC Berkeley developed a portable cyber-physical system for real time, daylight evaluation in buildings, agriculture facilities, and solar farms (collectively referred to as "structures").

The CRISPR-Cas system is now understood to confer bacteria and archaea with acquired immunity against phage and viruses. CRISPR-Cas systems consist of Cas proteins, which are involved in acquisition, targeting and cleavage of foreign DNA or RNA, and a CRISPR array, which includes direct repeats flanking short spacer sequences that guide Cas proteins to their targets.  Class 2 CRISPR-Cas are streamlined versions in which a single Cas protein bound to RNA is responsible for binding to and cleavage of a targeted sequence. The programmable nature of these minimal systems has facilitated their use as a versatile technology that is revolutionizing the field of genome manipulation.  There is a need in the art for additional Class 2 CRISPR/Cas systems (e.g., Cas protein plus guide RNA combinations).     UC Berkeley researchers discovered a new type of CasPhi/12j protein.  Site-specific binding and/or cleavage of a target nucleic acid (e.g., genomic DNA, ds DNA, RNA, etc.) can occur at locations (e.g., target sequence of a target locus) determined by base-pairing complementarity between the Cas12 guide RNA (the guide sequence of the Cas12 guide RNA) and the target nucleic acid.  Similar to CRISPR Cas9, the compact Cas12 enzymes are expected to have a wide variety of applications in genome editing and nucleic acid manipulation.  

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.

Producing meat products using cells grown in culture (instead of via animal husbandry farming) has many benefits and great potential. Current cell-cultured approaches either: (1) use suspension culture to produce homogenous products that don't meet consumer taste expectations for a substitute meat, or (2) organ culture methods to create products that meet consumer taste expectations, but at unacceptably high prices. To address this situation, researchers at UC Berkeley have been developing a process by which cells are grown in free suspension, making possible the economies of scaling that result from using large stirred tanks. After growth, the cells can be assembled into desirable macroscopic structures by controlling the conditions under which the desired multiple cell types and scaffolds are mixed and dewatered. The macroscopic structures include features such as fat marbling and muscle fiber orientation as expected by meat consumers.

The inventors have developed two new CasX gene-editing platforms (DpbCasXv2 and PlmCasXv2) through rationale structural engineering of the CasX protein and gRNA, which yield improved in vitro and in vivo behaviors. These platforms dramatically increase DNA cleavage activity and can be used as the basis for further improving CasX tools.The RNA-guided CRISPR-associated (Cas) protein CasX has been reported as a fundamentally distinct, RNA-guided platform compared to Cas9 and Cpf1. Structural studies revealed structural differences within the nucleotide-binding loops of CasX, with a compact protein size less than 1,000 amino acids, and guide RNA (gRNA) scaffold stem. These structural differences affect the active ternary complex assembly, leading to different in vivo and in vitro behaviors of these two enzymes.

Green algae have been promoted as vehicles for the production of biofuels, pharmaceuticals, food additives, vaccines, and for toxic substance remediation, and many plants are the focus of efforts to produce drought tolerant, pest resistant, or more nutritious crops. Many of these engineering efforts rely on expression of multiple transgenes (e.g. in a multistep metabolic pathway to avoid accumulation of a toxic intermediate). It can also be useful to produce two or more proteins in a particular stoichiometry, as in a heterodimer that requires equimolar production of two polypeptides. Whether the goal is to express one transgene, or several, most efforts to transform plants and algae require cotransformation of the gene of interest with a selectable marker, such as a gene that confers resistance to a drug or herbicide, or complements an auxotrophy. Unfortunately, commonly used methods for co-transformation of algae and other plants are very inefficient. UC Berkeley investigators have developed a method for polycistronic gene expression,  and show how to achieve this using the organism's own sequences, without recourse to viral elements or other foreign elements, which is important for any technology where bioproducts are generated, since these may be used on humans (cosmetics) or in humans (food additives), especially crop technology.