Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of organ development, providing an exceptional tool for studying the complexities of biology. Among these, cerebral cortex organoids (hereafter "organoid") have become particularly instrumental in providing valuable insights into brain formation, function, and pathology. Despite their potential, organoid experiments present several challenges. Organoids require a rigorous, months-long developmental process, demanding substantial resources and meticulous care to yield valuable data on aspects of biology such as neural unit electrophysiology, cytoarchitecture, and transcriptional regulation. Traditionally the data has been difficult to collect on a more frequent and consistent basis, which limits the breadth and depth of modern organoid biology. Generating and measuring organoids depend on media manipulations, imaging, and electrophysiological measurements. Historically are labor- and skill-intensive processes which can increase risks associated with experimental validity, reliability, efficiency, and scalability.

Dr. René Riedel and Stephen Lepore from the University of California, Riverside have developed an NMR tube/reactor that enables in-situ irradiation to photo-initiate reactions in an inert or controlled atmosphere. It allows for the data acquisition of air, moisture, and temperature-sensitive liquid samples by nuclear magnetic resonance (NMR) spectroscopy without needing to remove the sample from the spectrometer for irradiation. This technology is advantageous because it makes photochemical reactions and kinetic measurements of sensitive samples more reproducible, and it enables the previously impossible maintenance of a controlled environment during photochemical NMR investigations.

A novel method for selectively targeting and modulating brain border-associated myeloid cells for the treatment of neurological disorders.

Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of brain development, providing an exceptional tool for studying the complexities of biology. Among these, cortical organoids, comprising in part of neurons, have been instrumental in providing early insights into brain formation, function, and pathology. Functional characteristics of cortical organoids, such as cellular morphology and electrophysiology, provide physiological insight into cellular states and are crucial for understanding the roles of cell types within their specific niches. And while progress has been made studying engineered neuronal systems, decoding the functional properties of neuronal networks and their role in producing behaviors depends in part on recognizing neuronal cell types, their general locations within the brain, and how they connect.

Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of organ development, providing an exceptional tool for studying the complexities of biology. Among these, cerebral cortex organoids (hereafter "organoid") have become particularly instrumental in providing valuable insights into brain formation, function, and pathology. Modern methods of interfacing with organoids involve any combination of encoding information, decoding information, or perturbing the underlying dynamics through various timescales of plasticity. Our knowledge of biological learning rules has not yet translated to reliable methods for consistently training neural tissue in goal-directed ways. In vivo training methods commonly exploit principles of reinforcement learning and Hebbian learning to modify biological networks. However, in vitro training has not seen comparable success, and often cannot utilize the underlying, multi-regional circuits enabling dopaminergic learning. Successfully harnessing in vitro learning methods and systems could uniquely reveal fundamental mesoscale processing and learning principles. This may have profound implications, from developing targeted stimulation protocols for therapeutic interventions to creating energy-efficient bio-electronic systems.

Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of organ development, providing an exceptional tool for studying the complexities of biology. Among these, cerebral cortex organoids (hereafter “organoid”) have become particularly instrumental in providing valuable insights into brain formation, function, and pathology. Despite their potential, organoid experiments present several challenges. Organoids require a rigorous, months-long developmental process, demanding substantial resources and meticulous care to yield valuable data on aspects of biology such as neural unit electrophysiology, cytoarchitecture, and transcriptional regulation. Traditionally the data has been difficult to collect on a more frequent and consistent basis, which limits the breadth and depth of modern organoid biology. Generating and measuring organoids depend on media manipulations, imaging, and electrophysiological measurements. Historically these are labor- and skill-intensive processes which can increase risks associated with known human error and contamination.

A breakthrough imaging technique that provides high-resolution visualization of optically transparent materials at a low cost.

A novel suite of trioxane-based, MS-cleavable cross-linking reagents enhancing protein-protein interaction studies.

An AI-powered platform for the generation of automated electronic patient anatomy education models, providing surgeons with clinically relevant patient anatomy data.

An innovative algorithm linking electroencephalogram (EEG) neural data with cognitive model parameters to predict brain signals from behavioral data.

Professor Hideaki Tsutsui and colleagues from the University of California, Riverside have developed a portable handheld device for nucleic acid extraction. With its high-speed motor, knurled lysis chamber for rapid sample lysis, and quick nucleic acid extraction using paper disks, this device can yield ready-to-use extracts in just 12 minutes, significantly reducing the time required for sample preparation. This technology is advantageous over current methods as it can be expedited without the need for cumbersome specimen collection, packaging, and submission, shortening the turnaround time.  

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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.

      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.

This technology introduces a novel method for dynamically tuning the optical properties of living cells by expressing cephalopod proteins.

This technology offers a groundbreaking approach to mimic human placental development and study pregnancy-related complications in vitro.

This technology offers a groundbreaking approach to map biomolecules in 3D space with subcellular resolution, revolutionizing our understanding of tissue organization and disease propagation.

Researchers at the University of California, Davis have developed a technology that offers a sophisticated solution for collecting and measuring gas emissions from surfaces, particularly skin, with high sensitivity and specificity.

      Molecular dynamics (MD) is a computational materials science modality widely used in academic and industrial settings for materials discovery and more. A critical aspect of modern MD calculations are machine learning interatomic potentials (MLIPs), which learn from reference quantum mechanical calculations and predict the energy and forces of atomic configurations quickly. MLIPs allow for more accurate and comprehensive exploration of material/molecular properties at-scale. However, state-of-the-art MLIP methods mostly use a short-range approximation, which may be sufficient for describing properties of homogeneous bulk systems but fail for liquid-vapor interfaces, dielectric response, dilute ionic solutions with Debye-Huckel screening, and interactions between gas phase molecules. Short-range MLIPs neglect all long-range interactions, such as Coulomb and dispersion interactions.      To address the current shortcoming, UC Berkeley researchers have developed a straightforward and efficient algorithm to account for long-range interactions in MLIPs. The algorithm can predict system properties including those with charged, polar or apolar molecular dimers, bulk water, and water-vapor interfaces. In these cases standard short-range MLIPs lead to unphysical predictions, even when utilizing message passing algorithms. The present method eliminates artifacts while only about doubling the computational cost. Furthermore, it can be incorporated into most existing MLIP architectures, including potentials based on local atomic environments such as HDNPP, Gaussian Approximation Potentials (GAP), Moment Tensor Potentials (MTPs), atomic cluster expansion (ACE), and MPNN (e.g., NequIP, MACE).

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.

Inflatable pouches are attractive as actuators and structural links in soft robots due to their low deflated profile and high deformation ratio. Particularly compelling for minimally invasive surgery, deflated robots/actuators may be deployed in small form factors and maneuver delicately in tight spaces once inflated. However, current fabrication methods do not readily scale for production of actuators with less than 1 mm feature sizes; they often require precision handling of separator films; and/or there are limited multilayer integration capabilities. Fully miniaturized, high degree-of-freedom surgical pouch robots and actuators have not yet been realized.To overcome these challenges, UC Berkeley researchers have developed a rapid, monolithic, and scalable manufacturing method for fabricating thin-film-based pneumatic pouch soft robots. Small features (less than 0.3 mm) can be patterned at high speeds and using commercially available manufacturing tools while maintaining film planarity. Resulting robots can have complex, multilayer structures including single- and bi-directional joint actuators, structural links, integrated in-plane air channels, through-holes for interlayer connectivity, and air inlets to a supply manifold—from a single integrated processing step. Researchers have demonstrated a miniature four finger hand which can dexterously manipulate a cube (8 degrees of freedom), as well as an 10 degree-of-freedom planar arm with a gripper which can maneuver around obstacles. Entire pouch robot structures can have un-inflated thickness of less than 300 um and be inherently soft, allowing the robots to be used in tight spaces with fragile tissues for surgical applications.

Researchers at the University of California, Davis, have developed new synthesis methods for the rapid and highly pure production of glycosphingolipids. The prototyped process can produce pure glycosphingolipids that can be used within basic disease research and drug and diagnostic development.

As the density and performance of electronics continues to increase, thermal challenges have become a primary concern. Removing heat from electronic components can be extremely challenging, given their small size, electrical activity, and mechanical constraints. This necessitates the design of cooling solutions for a wide variety of electronic designs in applications such as datacenters, renewables, aircraft, etc. To address this problem, researchers at UC Berkeley have developed a thermal test vehicle (TTV) for characterizing the performance of electronics cooling solutions under a wide variety of operating conditions. All of the TTV circuitry required to perform measurements and temperature estimations can be included on one printed circuit board (PCB). This represents a simple, highly flexible approach for thermal test vehicle design. The overall size of the array can be scaled to any desired amount. This novel TTV represents a simple, highly flexible approach for thermal test vehicle design. Furthermore, its use of standard commercial electronic components allows for a vast reduction in cost compared to existing commercial solutions.