Browse Category: Research Tools > Other

[Search within category]

Semi-Automated Insect Culturing Device

Drosophila spp., also known as fruit flies, are widely used in genetic research. Drosophila lines (e.g. flies with a particular mutation) can only be stored as live animals – they cannot be frozen and still remain viable. So to maintain the stocks, the live flies are manually transferred from an old vial to a new vial on a regular basis (every 1-2 weeks). Some Drosophila labs maintain hundreds or even thousands of individual lines and so maintenance of these lines can be very time consuming. A UC Santa Cruz Drosophila researcher has developed a simpler and more efficient method of transferring the flies that requires significantly less hands-on work.An earlier version of this invention has been patented and patent prosecution continues. However, additional improvements to hands-free Drosophila maintenance systems were still necessary. In particular, a device that could be fabricated by injection molding would be advantageous as would a device that could better facilitating labels of stocks and that can be more readily separated into individual components for shipping and study. 

Droplet microvortices for modulating cell dynamics

The invention presents a microfluidic platform equipped with specialized trapping arrays and droplet generation capabilities, enabling precise control over the formation of microvortices within cell-laden droplets. This novel system facilitates the study of cell-cell interactions at a single-cell level, offering configurable microenvironments for analyzing cell dynamics and pair relationships.

Fully Automated Multi-Organ Segmentation From Medical Imaging

A comprehensive method for automated multi-organ segmentation based on deep fully convolutional networks and adversarial training, achieving superior results compared to existing techniques.

New Cross-Linking Mass Spectrometry Platform: SDASO-L, SDASO-M, and SDASO-S

An innovative mass spectrometry platform that utilizes sulfoxide-containing MS-cleavable heterobifunctional photoactivated cross-linkers to enhance protein structural elucidation.

Imaging of cellular immune response in human skin

This patent application describes methods for non-invasive, label-free imaging of the cellular immune response in human skin using a nonlinear optical imaging system.

High throughput and precision cell sorting

A novel method and device for high-throughput sorting of cells in suspension, particularly focusing on the separation of key cellular blood components of the immune system. The patent application presents a novel approach to high-throughput cell sorting, particularly suitable for applications in medicine and biotechnology where precise separation of cell populations is crucial.

Lab-on-a-chip microfluidic microvalves

A design for compact and energy-efficient microvalves for use in lab-on-a-chip microfluidic devices

Precision 3D Modeling Technology

An innovative technology that uses a device to move any imaging device precisely through a path in 3D space, enabling the generation of high-resolution 3D models.

Daily Move© - Infant Body Position Classification

Prof. John Franchak and his team have developed a prototype system that accurately classifies an infant's body position.


Lipoxygenases (LOX) are enzymes that catalyze the peroxidation of certain fatty acids. The cell membrane is mostly made of lipids (which include fatty acids), and peroxidation can cause damage to the cell membrane. The human genome contains six functional LOX genes that encode for six LOX enzyme variants, or isozymes. The role that each LOX isozyme plays in health and disease varies greatly, spanning issues such as asthma, diabetes, and stroke. LOX enzymes are extremely difficult to target due to high hydrophobicity. Potential leads are often ineffective because they are either not readily soluble or not selective for a particular LOX enzyme.  Studies have implicated human epithelial 15-lipoxygenase-2 (h15-LOX-2, ALOX15B) in various diseases. h15-LOX-2 is highly expressed in atherosclerotic plaques and is linked to the progression of macrophages to foam cells, which are present in atherosclerotic plaques. h15-LOX-2 mRNA levels are also highly elevated in human macrophages isolated from carotid atherosclerotic lesions in symptomatic patients. Children with cystic fibrosis had reduced levels of h15-LOX-2, which affects the lipoxin A4 to leukotriene B4 ratio. Furthermore, the interactions of h15-LOX-2 and PEBP1 changes the substrate specificity of h15-LOX-2 from free polyunsaturated fatty acids (PUFA) to PUFA-phosphatidylethanolamines (PE), leading to the generation of hydroperoxyeicosatetraenoic acid (HpETE) esterified into PE (HpETE-PE). Accumulation of these hydroperoxyl membrane phospholipids has been shown to cause ferroptotic cell death, which implicates h15-LOX-2 in neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Huntington’s diseases.  

System And Method For Tomographic Fluorescence Imaging For Material Monitoring

Volumetric additive manufacturing and vat-polymerization 3D printing methods rapidly solidify freeform objects via photopolymerization, but problematically raises the local temperature in addition to degree-of-conversion (DOC). The generated heat can critically affect the printing process as it can auto-accelerate the polymerization reaction, trigger convection flows, and cause optical aberrations. Therefore, temperature measurement alongside conversion state monitoring is crucial for devising mitigation strategies and implementing process control. Traditional infrared imaging suffers from multiple drawbacks such as limited transmission of measurement signal, material-dependent absorptions, and high background signals emitted by other objects. Consequently, a viable temperature and DOC monitoring method for volumetric 3D printing doesn’t exist.To address this opportunity, UC Berkeley researchers have developed a tomographic imaging technique that detects the spatiotemporal evolution of temperature and DOC during volumetric printing. The invention lays foundations for the development of volumetric measurement systems that uniquely resolve both temperature and DOC in volumetric printing.This novel Berkeley measurement system is envisaged as an integral tool for existing manufacturing technologies, such as computed axial lithography (CAL, Tech ID #28754), and as a new research tool for commercial biomanufacturing, general fluid dynamics, and more.

Micron-resolution malleable strain and pressure sensor

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.

Three-dimensional organoid culture system for basic, translational, and drug discovery research

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.

Biological and Hybrid Neural Networks Communication

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.

Advanced Potentiostat

During In the last few decades, the use of miniaturized electrochemical devices has grown rapidly and found diverse applications in scientific and consumer products. The process of developing specialized electrochemical devices is often time-consuming and expensive. Experimental setups involving electrochemistry often use specialized measurement equipment such as a potentiostat. A potentiostat is an analytical instrument that controls the voltage and current between two or more electrodes in a cell. The accuracy, precision, and flexibility of applying or measuring voltages and currents depends on the quality and design of the electronic hardware, which for commercially available potentiostats, often correlate with the device’s cost and architecture. Consequently, one of the challenges faced by today’s electrochemical research community is how to perform modern experimental designs with expensive, asynchronous, and inflexible potentiostats.

Add-Seq: Quantitative Genome-Wide, Single-Molecule, And Long-Range Nucleosome Profiling

In cells, DNA is organized by wrapping DNA strands around histone proteins, creating protein-DNA complexes called nucleosomes which comprise the basic unit of chromatin. Chromatin is associated with regions of low gene expression, as compacted DNA is inaccessible to proteins that would promote transcription. Conversely, regions in the DNA not bound by histones experience higher gene expression, as this DNA is readily available to be transcribed.  Nucleosomes are not uniformly positioned on a DNA molecule, and they change based on factors like which genes are expressed during different cellular processes. It is beneficial to understand where nucleosomes are positioned, as this can provide insight into how genes are regulated, or how factors like epigenetic modifications or chromatin structure affect this accessibility and can additionally illuminate gene expression patterns in disease for designing therapies. Nucleosome profiling is a technique used to study the positions of nucleosomes along a DNA molecule. Typically, histones are crosslinked to DNA, then the DNA is fragmented and digested leaving only regions protected by nucleosomes left for short-read sequencing. However, this fragmentation only reveals nucleosome positioning at the resolution of a few hundred base pairs, leaving the larger genomic context of these nucleosome positions to be desired. To address this, researchers at UC Santa Cruz developed Add-SEQ, a pipeline using long-read nanopore sequencing to map nucleosomes across long stretches > 10 kb of single DNA molecules.

Full Signal Utilization In Charge Detection Mass Spectrometry

UC Berkeley researchers have developed several methods that take advantage of all of the information contained in ion signals in charge detection mass spectrometry (CDMS). Unlike most conventional types of mass spectrometry (MS), which rely on mass-to-charge ratio (m/z) measurements of ensembles of ions, CDMS instead makes direct measurements of the mass of individual ions. CDMS has recently gained significant popularity in the analysis of large biomolecules, nanoparticles, and nanodroplets because it is one of very few methods that can characterize these analytes. State-of-the-art CDMS instruments incorporate ion traps and signals from individual trapped ions are used to find the mass, charge, and energy of these ions. Previously used techniques have used Fourier transform (FT)-based analyses, but only use the fundamental and/or second harmonic frequency and amplitude as the basis of the measurement. The significant additional information contained in the higher order harmonic frequencies and amplitudes of the ion signal is fully utilized in the novel methods comprising this invention and large improvements in measurement uncertainties are realized as a result. 

Hyperspectral Microscopy Using A Phase Mask And Spectral Filter Array

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.

Adaptive Machine Learning-Based Control For Personalized Plasma Medicine

Plasma medicine has emerged as a promising approach for treatment of biofilm-related and virus infections, assistance in cancer treatment, and treatment of wounds and skin diseases. However, an important challenge arises with the need to adapt control policies, often only determined after each treatment and using limited observations of therapeutic effects. Control policy adaptation that accounts for the variable characteristics of plasma and of target surfaces across different subjects and treatment scenarios is needed. Personalized, point-of-care plasma medicine can only advance efficaciously with new control policy strategies.To address this opportunity, UC Berkeley researchers have developed a novel control scheme for tailored and personalized plasma treatment of surfaces. The approach draws from concepts in deep learning, Bayesian optimization and embedded control. The approach has been demonstrated in experiments on a cold atmospheric plasma jet, with prototypical applications in plasma medicine.

Method To Inverse Design Mechanical Behaviors Using Artificial Intelligence

Metamaterials are constructed from regular patterns of simpler constituents known as unit cells. These engineered metamaterials can exhibit exotic mechanical properties not found in naturally occurring materials, and accordingly they have the potential for use in a variety of applications from running shoe soles to automobile crumple zones to airplane wings. Practical design using metamaterials requires the specification of the desired mechanical properties based on understanding the precise unit cell structure and repeating pattern. Traditional design approaches, however, are often unable to take advantage of the full range of possible stress-strain relationships, as they are hampered by significant nonlinear behavior, process-dependent manufacturing errors, and the interplay between multiple competing design objectives. To solve these problems, researchers at UC Berkeley have developed a machine learning algorithm in which designers input a desired stress-strain curve that encodes the mechanical properties of a material. Within seconds, the algorithm outputs the digital design of a metamaterial that, once printed, fully encapsulates the desired properties from the inputted stress-strain curve. This algorithm produces results with a fidelity to the desired curve in excess of 90%, and can reproduce a variety of complex phenomena completely inaccessible to existing methods.

Improved system for imaging of large biological samples in high refractive index solutions

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.

Dropblot Design Integrates Droplet Microfluidics With Single-Cell Electrophoresis

Single-cell analyses are revolutionizing biomedicine and biology, with genomics (DNA) and transcriptomics (RNA) tools leading the way. At the protein-level, single-cell analyses are limited to mass spectrometry and immunoassays. Neither assay provides comprehensive coverage of proteome for single cells, missing key protein forms (called isoforms).  UC Berkeley researchers have developed a hybrid droplet-electrophoresis device, termed “DropBlot”, to detect proteins from patient-derived tissue biospecimens relevant to clinical medicine and pathology. The DropBlot takes advantage of water-in-oil (W/O) droplets to encapsulate single cells derived from chemically fixed tissues, thus providing a picoliter-volume reaction chamber in which said cells are lysed and subjected to harsh lysis conditions (100ºC, 2 hours), as needed for fixed cells. We report an all-in-one microdevice to facilitate cell-laden droplet loading with >98% microwell occupancy. Droplets remain intact under the electric field and protein isoforms are shown to electromigrate out of the droplet and into a microfluidic separation channel where protein sizing takes place via the action of electrophoresis in a photoactive polyacrylamide (PA) gel. DropBlot has been successfully applied to live and fixed cancer cell lines and resolved proteins with high sensitivity.

Generalizable and Non-genetic Approach to Create Metabolically-active-but-non-replicating Bacteria

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.

Non-Planar Granular 3D Printing

The inventors have developed a novel 3D printing technique, named Non-Planar Granular 3D Printing (NGP), which selectively deposits a liquid binder into granular particles, enabling rapid fabrication of complex 3-dimensional objects. For this new method, an industrial robotic arm is equipped with a dispenser attached to a long metal needle, called a liquid deposition end-effector, and a container of granular particles, such as sand, beads, or powders. The needle moves freely as it injects the binding liquid into the granular material. Like other 3D printing methods, NGP can use a CAD 3D model and conventional slicing software to produce a robotic toolpath following a desired height and width. However, the advantage of the process lies in its ability to 3D print objects non-planarly, by moving the extruder’s dispensing tip freely within the granular medium. The selective application of the binding liquid causes the particles to bond together, forming parts of the 3D printed object. Meanwhile, the loose particles remaining in the container temporarily support the weight of the wet particles while they cure. This unique approach enables the creation of complex geometric forms without the need for supporting structures that are typical in traditional 3D printing methods, thereby eliminating material waste typically associated with such processes. After the completion of the process, and the binding material has cured, the hard objects can be easily extracted from the container, leaving behind the remaining loose particles, which can be repeatedly re-used.   

  • Go to Page: