Stem cells have the potential to develop into different types of cells. They are key to an organism’s development. Producing stem cell lines are important for research. Currently, avian embryonic stems cells are cultured on a layer of feeder cells. Feeder cells ensure that the stem cells survive and do not differentiate into other types of cells. However, using feeder cells can be costly and inconvenient.

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.

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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.

Scientists at UC Irvine have developed a sensitive, customizable, and user-friendly sensor for (1) strain detection as a result of cellular movement, (2) micro-fluidic device pressure detection, and (3) real-time monitoring of valve statuses in microfluidic chips. This research tool will provide new insights regarding cellular biophysics.

Researchers at UC Irvine have developed an organoid culture system capable of generating three-dimensional molecular gradients. This recapitulates in vivo tissue development more accurately than current two-dimensional organoid culture systems and will allow scientists to study human-specific disease mechanisms in native tissue.

Researchers from UC San Diego have created a system to enable animal model research by reducing the physical impact of weight introduced by body worn or implanted instrumentation. It does so by dynamically counterbalancing the force introduced by the additional mass of the instrumentation. Together the dynamic counterbalance system, dynamic adjustment arm, and dynamic pulley provide a low cost system that addresses several of the pressing weight constraints of chronic small animal experiments. Together they will enable researchers to conduct experiments that would not have been possible due to weight restrictions of existing recording instruments.

Researchers at UC Irvine have used a computationally powered method to identify small molecule drug leads that exhibited anti-cancer activity in a human-cell-based assay. These small molecules and the approach used to find them will accelerate the research and development of anti-cancer therapeutics.

During initial stages of development, the human brain self assembles from a vast network of billions of neurons into a system capable of sophisticated cognitive behaviors. The human brain maintains these capabilities over a lifetime of homeostasis, and neuroscience helps us explore the brain’s capabilities. The pace of progress in neuroscience depends on experimental toolkits available to researchers. New tools are required to explore new forms of experiments and to achieve better statistical certainty.Significant challenges remain in modern neuroscience in terms of unifying processes at the macroscopic and microscopic scale. Recently, brain organoids, three-dimensional neural tissue structures generated from human stem cells, are being used to model neural development and connectivity. Organoids are more realistic than two-dimensional cultures, recapitulating the brain, which is inherently three-dimensional. While progress has been made studying large-scale brain patterns or behaviors, as well as understanding the brain at a cellular level, it’s still unclear how smaller neural interactions (e.g., on the order of 10,000 cells) create meaningful cognition. Furthermore, systems for interrogation, observation, and data acquisition for such in vitro cultures, in addition to streaming data online to link with these analysis infrastructures, remains a challenge.

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.

Many genomes encode Restriction-Modification systems (RMs) that act to protect the host cell from invading DNA by cutting at specific sites (frequently short 4-6 base reverse complement palindromes). RMs also protect host DNA from unfavorably being cut by modifying sites within the host DNA that could be targets by the host’s own surveillance enzymes. It is also not unusual to find that these enzymes are adjacent to each other in the host genome. Traditional approaches to understanding these sites involve finding a methylase that is typically adjacent to a restriction enzyme, and then extracting DNA, expressing protein and then testing DNA sequence for evidence of cutting. In certain laboratory research (e.g., programs that involve transforming DNA/RNA) it may be desirable to more comprehensively understand the sequences being surveilled by the host. Moreover, it may be desirable in certain laboratory research to know/predict which surveillance enzymes are present in a genome in order to affect cell transformation efficiency through evasion of those sequences.

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Currently, conventional methods of epigenome editor discovery require time and labor-intensive construct development, which is typically performed in low-throughput arrayed formats. The platform bypasses current time/labor constraints (and without reliance on construct barcodes) to facilitate the identification of an optimal gene modulator in a single experiment.

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.

Researchers at the University of California, Riverside (UCR) in collaboration Nationwide Children’s Hospital  have developed and characterized small peptidomimetics that act as EphA4 agonists. Given ALS is a heterogeneous disease, astrocytes reprogrammed from the fibroblasts of patients with sporadic and SOD1-linked ALS (iAstrocytes) were cultured with MNs and the UCR/Nationwide EphA4 agonists.  As seen in Fig. 1, these small agonistic peptidomimetics decrease MN death in iAstrocytes derived from sporadic ALS (sALS) cells.     

RNA-mediated adaptive immune systems in bacteria and archaea rely on Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) genomic loci and CRISPR associated (Cas) proteins that function together to provide protection from invading viruses and plasmids. Genome editing can be carried out using a CRISPR-Cas system comprising a CRISPR-Cas effector polypeptide and a guide nucleic acid, such as a guide RNA. However, unintended chromosomal abnormalities following on-target genome editing, such as chromosome loss, are potential concerns for genome editing. UC Berkeley researchers and others have developed a method to modulate the expression levels of the DNA damage response factor p53 in order to mitigate chromosomal abnormalities that occur after genome editing by nucleases like Cas9. The invention provides treatment methods by generating a modified cell and then administering the modified cell to an individual in need thereof and compositions having a CRISPR-Cas effector polypeptide, a guide nucleic acid, and an agent that increases the level of a p53 polypeptide in a mammalian cell.

Novel system for imaging of specimens in high refractive index solutions on the Zeiss Z.1 fluorescence light sheet microscope. System will allow for deep imaging of large and intact biological samples (i.e. mouse brain) for enhanced optical resolution and faster imaging speed.

DP-L4056 is a prophage-cured strain of Listeria monocytogenes based on wild-type strain 10403S. A prophage is a bacteriophage genome that is integrated into a bacterial genome. It remains latent until activation by an external factor, and activation leads to production of new bacteriophage particles that lyse the bacterial cell and spread. Curing the prophages in Listeria monocytogenes strain 10403S, which is ubiquitous in the microbiology community as a wild-type reference strain, allows for more predictable engineering and performance of Listeria monocytogenes.

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.

Researchers at the University of California, Davis have developed a method of biofluid assessment capable of real-time monitoring as well as compatible with machine learning and neural network processing.

Researchers at the University of California, Davis have developed a method to stop bacterial growth while maintaining desirable metabolic functions for therapeutic and biotechnological applications.

Pathogenic transmission of dental aerosol created by ultrasonic scaling is considered a major concern during dental procedures. Researchers at UC Irvine have developed a novel tool/method to address this concern by removing the created aerosol at the source.

Noncanonical redox cofactor-based biotransformation is an attractive low-cost alternative to traditional cell-free reductive biotransformation. However, engineering enzymes to utilize noncanonical redox cofactors has been challenging. Addressing this problem, researchers at UC Irvine have developed a high-throughput directed evolution platform that enables development of such enzymes with ~147-fold improved catalytic efficiency, which translates to an industry-viable total turnover number of ~45,000 in cell-free biotransformation without requiring high cofactor concentrations.

Scientists at UCSF have developed a method for highly parallel testing of gene knockins/overexpression in combination with a cancer-specific T cell receptor (TCR) or chimeric antigen receptor (CAR). The method enables researchers to evaluate what constructs can improve anti-tumor efficacy of conventional T-cell therapies.