Detection of sucralose (also known under its trade name Splenda®), particularly in food and beverages, is slow and involves the use of complex instrumentation. Current techniques involve high pressure liquid chromatography and/or mass spectrometry. Use of these techniques is not commercially viable. Producers want rapid and accurate responses - resulting in some producers determining sucralose concentration by taste alone. 

The use of telemedicine/telehealth increased substantially during the COVID-19 pandemic, leading to its accelerated development, utilization and acceptability. Telehealth momentum with patients, providers, and other stakeholders will likely continue, which will further promote its safe and evidence-based use. Improved healthcare by telehealth has also extended to musculoskeletal care. In a recent study looking at implementation of telehealth physical therapy in response to COVID-19, almost 95% of participants felt satisfied with the outcome they received from the telehealth physical therapy (PT) services, and over 90% expressed willingness to attend another telehealth session. While telehealth has enhanced accessibility by virtual patient visits, certain physical rehabilitation largely depends on physical facility and tools for evaluation and therapy. For example, limb kinematics in PT with respect to the shoulder joint is difficult to evaluate remotely, because the structure of the shoulder allows for tri-planar movement that cannot be estimated by simple single plane joint models. With the emergence of gaming technologies, such as videogames and virtual reality (VR), comes new potential tools for virtual-based physical rehabilitation protocols. Some research has shown digital game environments, and associated peripherals like immersive VR (iVR) headsets, can provide a powerful medium and motivator for physical exercise. And while low-cost motion tracking systems exist to match user movement in the real world to that in the virtual environment, challenges remain in bridging traditional PT tooling and telehealth-friendly physical rehabilitation.

Brief description not available

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.

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. 

Researchers from UC San Diego have developed an invention that allows the continuous monitoring of atmospheric He, Ne, and H2 at unprecedented precision. This enables important new applications including in the understanding of the global carbon cycle, verifying reported natural gas emissions, and predicting earthquakes.

Short-time Fourier transforms with short segment lengths are typically used to analyze single ion charge detection mass spectrometry (CDMS) data either to overcome effects of frequency shifts that may occur during the trapping period or to more precisely determine the time at which an ion changes mass, charge or enters an unstable orbit. The short segment lengths can lead to scalloping loss unless a large number of zero-fills are used, making computational time a significant factor in real time analysis of data.    To address the foregoing deficiencies in prior approaches, UC Berkeley researchers have developed an apodization specific fitting that can lead to a 9-fold reduction in computation time compared to zero-filling to a similar extent of accuracy. This makes possible real-time data analysis using a standard desktop computer and capable of separating ions with similar frequencies.  

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Brief description not available

Mass spectrometers for high precision gas isotope measurements (e.g., noble gases, carbon, nitrogen) are typically equipped with a dual inlet system in which one side contains the unknown sample gas and the second side contains a known standard. Repeated comparisons of the two gases allows precise determination of differences in the gas composition. 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 at the University of California, Irvine have fabricated a flexible and unobtrusive wearable electrode that can detect glucose at a very low limit of detection.In fact, the detection limits are the lowest ever reported for an enzyme-free sensor. This sensor is applicable for detecting glucose levels in saliva, sweat or tears, and can safely be used at home, especially by diabetic patients without the need to frequently draw blood.

Researchers at the University of California, Riverside can discriminate between mixed populations of cells and particles in solution using pressure to displace objects across a nanopore multiple times.  Ionic current flow through the nanopore indicates the pressure required to translocate the object in the pore, which correlates to the object’s mass and volume.  Key to these results is that a nanopore sensor allows pressure oscillations to capture and release repeatedly the same object to learn about its inertia and morphology.  Such data can provide details about the size and shape of analytes, their morphologies and structural constraints, or even pathological conditions of living cells. Fig. 1 Nanopore sensing of differently sized cells in a mixed bacterial culture.  

Scanning tunneling microscopy (STM) techniques and associated spectroscopic (STS) methods, such as dI/dV point spectroscopy, have been widely used to measure electronic structures and local density of states of molecules and materials with unprecedented spatial and energy resolutions. However, the quality of dI/dV spectra highly depends on the shape of the probe tips, and atomically sharp tips with well-defined apex structures are required for obtaining reliable spectra. In most cases, STS measurements are performed in ultra-high vacuum  and low temperature (4 K) to minimize disturbances. Advance tip preparation and constant in situ tip conditioning are required before and during the characterization of target molecules and materials. A common way to prepare STM tips is to repetitively poke them on known and bare substrates (i.e. coinage metals or silicon) to remove contaminations and to potentially coat the tip with substrate atoms. The standard dI/dV spectra of the substrate is then used as a reference to determine whether the tip is available for further experiments. However, tip geometry changes during the poking process are unpredictable, and consequently tip conditioning is typically slow and needs to be constantly monitored. Therefore, it restricts the speed of high-quality STM spectroscopic studies. In order to make efficient use of instrument idle time and minimize the research time wasted on tip conditioning, UC Berkeley researchers developed software based on Python and machine learning that can automate the time-consuming tip conditioning processes. The program is designed to do tip conditioning on Au(111) surfaces that are clean or with low molecular coverage with little human intervention. By just one click, the program is capable of continued poking until the tip can generate near-publication quality spectroscopic data on gold surfaces. It can control the operation of a Scienta Omicron STM and automatically analyze the collected topographic images to find bare Au areas that are large enough for tip conditioning. It will then collect dI/dV spectra at selected positions and use machine learning models to determine their quality compared to standard dI/dV spectra for Au20 and determine if the tip is good enough for further STS measurements. If the tip condition is not ideal, the program will control the STM to poke at the identified positions until the machine learning model predicts the tip to be in good condition.

The invention is a smart non-intrusive workflow assessment platform for monitoring and optimizing manufacturing environments. The platform monitors environmental and energy metrics, and provides learning models to classify workers’ activities and relate them to the equipment utilization and performance. Correlating both stream of data enables both workers and supervisors to improve the efficiency of the whole manufacturing process and at an affordable price.

Researchers at the University of California, Davis have developed a robotic dispensing interface that uses a microfluidic-embedded container cap – often referred to as a microfluidic Cap-to-Dispense or μCD - to seamlessly integrate robotic operations into precision liquids handling.

Brief description not available

UCLA researchers from the Department of Electrical Engineering have developed a novel sweat induction and sensing platform to achieve personalized physiological monitoring non-invasively.

Microfluidic devices have long been touted as a powerful analytical tool with which to characterize a wide range of analytes, including particles, and cells. Despite the apparent convenience of microfluidic technologies for applications in healthcare, such devices often rely on capital-intensive optics and other peripheral equipment that limit throughput, perhaps because the majority of microfluidic devices operate using optics-based principles, which typically require high-speed or sensitive cameras, sophisticated confocal microscopes, vibration isolation tables, and laser excitation systems.

Native mass spectrometry (MS), in which electrospray ionization (ESI) is used to transfer large macromolecules and macromolecular complexes directly from solution into the gas phase, is a powerful tool in structural biology.  However, charge-state distributions of individual components in mixtures of macromolecular complexes or synthetic polymers are often unresolved making it impossible to obtain mass information directly from an ESI mass spectrum. Other conventional methods can provide accurate masses of individual ions, but often at the expense of analysis time.     Weighing ions individually with charge detection mass spectrometry (CDMS) has the advantage that fast measurements are possible depending on the accuracy and sensitivity required. However, a limitation of trapping CDMS technology is the need to weigh single ions individually in order to eliminate potential interferences between the signals of multiple ions or ion-ion interactions that can potentially interfere with these measurements. UC researchers have created multiplex charge detection mass spectroscopy, particularly for high throughput single ion analysis of large molecules and measuring the masses of large molecules, macromolecular complexes and synthetic polymers that are too large or heterogeneous for conventional mass spectrometry measurements.  The new multiplexing method makes it possible to measure the masses of many ions simultaneously.  

UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a novel device for high-throughput label-free analysis of cells.

UCLA researchers in the department of Bioengineering have developed a novel method for quantitative analysis of DNA amplification products.