Novel enzymes for IgG-specific glycosynthesis.
The global monoclonal antibodies market is experiencing significant growth due to the rising prevalence of chronic diseases such as cancer and cardiovascular conditions. However, existing technologies for modifying IgG antibodies, such as glycosynthases, often suffer from unwanted hydrolytic activity, leading to inefficiencies. A key unmet need remains the development of technologies to optimize monoclonal antibody glycosylation, ensuring better clinical outcomes.
Emory researchers have developed enzymes that enhance the regulation of antibody-mediated immune responses. These enzymes, known as glycosynthases, exhibit improved transglycosylation functions and reduced residual hydrolytic activity. This advancement was achieved through a novel residue mutation, resulting in IgG-specific glycosynthases with reduced residual glycan hydrolysis. This invention addresses the need for more precise and efficient glycosylation of IgG antibodies, which is essential for improving therapeutic effectiveness and reducing inflammation in autoimmune diseases. By enhancing the glycosynthase function of EndoS2D184M, this technology offers a more effective approach to antibody-based treatments.
Liquid crystal technology with variable pre-tilt control for advanced optics and displays.
Patents
U.S. 8,654,281
The technology pertains to the field of mm-wave signal amplification, particularly through the use of reversed feedback amplifiers and cascaded amplifier structures. It addresses the challenges of amplifying signals in the mm-wave frequency bands, crucial for applications like wireless communications and radar systems. The technology overcomes the limitations of traditional amplifiers by employing a unique topology that includes a MOSFET (metal-oxide-semiconductor field-effect transistor) with specific passive components to achieve maximum gain operation and compensate for passive losses.
This innovation focuses on the potential therapeutic use of Allopregnanolone (ALLO), a natural neurosteroid, to treat hypoxic ischemic (HI) brain injury in premature infants. ALLO, naturally produced in the placenta during brain development, is absent in premature infants, which contributes to the neurological deficits observed in HI cases. The proposed solution involves administering ALLO to enhance brain development, promote cell survival, and reduce neuroinflammation and glutamate excitotoxicity. In preclinical studies using a neonatal mouse model, ALLO treatment showed promising results in protecting brain cells, improving motor function, and restoring cognitive abilities. ALLO treated mice exhibited better neurogenesis, reduced inflammation, and protection against mitochondrial damage, which is crucial for overall brain health. These findings suggest that ALLO has significant potential to decrease the incidence and severity of CP in premature infants by promoting brain repair and minimizing injury from HI.
Background:
Hypoxic ischemic (HI) brain injury in premature infants is a leading cause of cerebral palsy (CP). Each year, 40,000 premature infants suffer from major cognitive deficits, with 7,000 developing CP. Currently, there are no effective therapies that can reverse or reduce the long-term brain damage caused by HI. Existing treatments focus on managing symptoms or reducing secondary complications, but they do not target the root causes of the injury. By administering Allopregnanolone (ALLO), a natural neurosteroid essential for brain development, this approach aims to promote neurogenesis, neuroregeneration, and protect against inflammation and mitochondrial damage, offering a direct method to restore brain function. Mouse model studies of ALLO show potential to develop a promising therapeutic option for preventing or reducing the severity of HI and CP in infants.
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This digital twin-based architecture predicts, detects, and prioritizes faults in buildings. Facilities management systems help ensure the efficient and safe operation of constructed facilities. When a fault eventually arises, it requires time, money, and resources to diagnose and fix. Being able to predict necessary maintenance saves more money than standard preventative or corrective maintenance1. Current facility management systems are constrained by high implementation failure rates, difficulties in data and system integration, insufficient support for predictive maintenance, and basic data visualization features.
Researchers at the University of Florida have developed a fault detection framework that integrates criticality analysis with digital replicates of the facility, known as digital twins, to predict and diagnose necessary maintenance. Identifying the fault at early stages reduces downtime and streamlines the process of diagnosing and correcting. This process enhances existing fault detection and diagnosis systems by monitoring the output of assets. When the most critical faults are first identified the system prioritizes them, considering the cost and impact of downtime and loss of functionality and visually displays the list and necessary measures in a convenient user interface.
Preemptive detection, diagnosis, and prioritization of structural faults in buildings and constructed facilities
This framework consists of a three-layer system: the information, application, and service and visualization layers, where the output from each layer feeds into the next. The first layer collects data from various sources, including machine outputs and sensor outputs, containing data related to the managed asset. The contents of the first layer serve as the input for the second layer, which processes the data. The second layer processes the collected data from the first layer to perform fault detection, diagnosing issues, predicting faults, and generating an alarm if necessary. The output from the second layer is then interpreted and visualized by the third layer, which displays the results in a prioritized manner and can predict potential failures over time.
These permanently ionic, viologen-based polymers of intrinsic microporosity (PIMs) serve as as a standalone supercapacitor electrode material with energy-storing applications. There is a growing demand for electrically powered automobiles, consumer electronics, medical devices and other high-power density applications. However, the ability to meet these needs is challenging due to the limitations of current nonporous viologen energy storage materials. Current ionic high-capacity energy storage relies on electrochemical capacitive energy storage, operating by accumulating ions at an electrically active interface under an applied bias. A first-class material design is significant for super-capacitive purposes, especially for short-term energy storage. At the device level, the porous polymers function as standalone supercapacitor electrode materials. The microporous material is also useful for battery applications, with the current global market valued at US $7.0 billion and projected to grow to US $17.2 billion1. As car manufacturers increasingly shift toward electric vehicles, the demand for supercapacitors in regenerative braking systems is rising dramatically.
Researchers at the University of Florida have designed microporous polymers with super-capacitive properties, transforming energy storage at the material level. This innovation in synthesis and at the device-level design helps reduce manufacturing costs while preserving the large-scale fabrication advantages. These polymers can be used in numerous applications and offer competitive advantages over non-porous viologen polymers.
Viologen-based polymers of intrinsic microporosity enable supercapacitive energy storage for applications like battery storage, regenerative braking, burst-mode power, and airplane takeoff thrust
Organic energy storage materials are highly attractive for high-power density applications, owing to their synthetic tunability, compatibility with biological environments and are derived from widely available precursors. However, traditional organic supercapacitors often fall short in terms of cycling stability, power density, and manufacturability, all crucial in deployment. Researchers at the University of Florida have developed viologen-based polymers with intrinsic microporosity, designed for high-efficiency energy storage applications.
Viologen-based polymers contain permanent voids that contribute to their porous design. Spirobisindane diamine (SBIDA) serves as the contorted unit of the polymer, responsible for creating energy-storing pores. Imperfect stacking of the polymer chains leads to the formation of pores in between The synthetic protocol begins with SBIDA synthesis, after which the resulting diamine is reduced. The products include a mixture of two regioisomers, which do not require purification. A final reaction with additional reagents results in a high yield of over 80%. Carbon dioxide isotherms confirm microporosity of the polymers due to the low pressure observed during CO2 uptake. Additionally, high capacities are retained after 10,000 charge-discharge cycles. These polymers are significant for superapacitive purposes, particularly for short-term energy storage.
Unique sequences eliciting broadly neutralizing antibodies (bNAbs) against human immunodeficiency virus (HIV) that could be used to develop effective mRNA-based and other types of HIV vaccine.
Problem:
Despite decades of research, there is currently no vaccine to prevent HIV infection. A major goal of HIV vaccine programs is to generate bNAbs, which broadly bind to proteins on the outer surface of the virus and can neutralize diverse HIV strains. This is critical as HIV is known for its high variability and ability to evade the immune system.
Solution:
Engineered HIV surface proteins were tested in monkeys and found to elicit potent levels of bNAbs against multiple diverse strains of HIV. This is the first example of the consistent elicitation of bNAbs in any outbred animal model. These surface protein sequences can be used to design a potentially efficacious HIV vaccine.
Technology:
The inventors engineered mutations into the HIV envelope glycoprotein expressed on the surface of the virus. A version of HIV adapted for monkeys expressing the mutated envelope glycoproteins was tested to identify mutations that efficiently caused priming, boosting, and antibody affinity maturation of B cell precursors to produce bNAbs. When used to immunize monkeys, the mutated envelope glycoprotein elicited broad and potent bNAbs as early as 16-24 weeks post infection and at a far higher frequency than with the native envelope glycoprotein.
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Docket # 24-10697
This invention introduces a new class of UV-curable Disulfide Glass (DSG) photoresists and photopolymer resins, designed for high-quality optical component fabrication and complex 3D printing. This polymer features exceptional optical transparency across the visible and infrared spectrum, coupled with robust thermomechanical properties, making it ideal for precision plastic optics. DSG offers a high refractive index (RI) and can be processed into thick, defect-free optical components, such as windows, lenses, and prisms. Its superior transparency surpasses common plastics like PMMA (Plexiglass) while maintaining cost-efficiency. The versatile processing capabilities of DSG allow for the fabrication of precision optical devices using established industrial techniques like diamond turning.
Background:
Traditional commodity optical plastics like PMMA and polycarbonate have limitations in refractive index, optical clarity, and processability. PMMA offers excellent transparency but falls short on refractive index, while polycarbonate exhibits high birefringence and becomes hazy in thicker forms. Other options, such as epoxy resins and perfluorinated polymers, either suffer from poor optical clarity or pose environmental concerns. DSG addresses these gaps by offering high RI and superior optical clarity without relying on environmentally harmful substances. Additionally, unlike existing materials, DSG can be processed into thick, transparent components without introducing haze or significant optical losses.
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This is an advanced software tool that analyzes functional neuroimaging data to map brain oscillations and predict optimal task timing across cognitive domains. By integrating MRI-based connectivity data with user input, it provides insight into the understanding of how different brain states interact. This predictive software intends to provide recommendations for optimized task completion in several cognitive avenues including psychomotor vigilance, emotional regulation, and cognitive performance. Additionally, this software has the possibility to be applied in diagnostics as a measure of circadian abnormality within various sleep disorders. This method offers a novel approach to predicting brain oscillations at both the individual and population level. G.L.O.B.E may be applied in conjunction with open-source machine learning approaches to predict MRI global efficiency based on completely novel EEG measures.
Background:
Circadian rhythm sleep disorders (CRSDs) are conditions where the internal circadian rhythms are not properly aligned with the external environment. A report published in 2024 by the National Council on Aging, Inc. revealed that around 30% of adults experience symptoms of insomnia, with 10% having insomnia that affects their daily activities. Traditional methods for assessing cognitive performance and sleep-related brain activity rely on broad statistical models that often lack personalization. Recently, the rise of sleep tracking applications has been prominent as sleep science makes headway in the analysis of sleep with novel technologies. This new software uses functional MRI data to offer personalized prediction of optimized times for specific tasks in the user’s life. This advanced approach looks to new markers, individual brain oscillations, with an advanced mathematical model for interpretation of sleep data.
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This invention improves acousto-optic devices by increasing their interaction length, allowing for better diffraction efficiency and higher resolution holographic displays with a wider field of view. By using an ultra-thin semiconductor film, the acoustoelectric effect amplifies surface acoustic waves, making them last longer and improving acousto-optic performance. This approach results in improved diffraction efficiency and a greater number of resolvable spots, supporting the development of transparent spatial light modulators for holography, particularly for augmented reality.
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Acousto-optic modulators (AOMs) work well for holographic displays because they have a large bandwidth, but they are limited by a short interaction length, which reduces efficiency and resolution. Pixelated spatial light modulators (SLMs) are another option, but they lose resolution when handling color. Increasing the interaction length of AOMs is important, but current methods struggle due to acoustic loss in thin-film materials. Improving display performance requires either the difficult challenge of reducing SLM pixel size or extending the interaction length of an AOM. In thin film photonic platforms, acoustic loss is the limiting factor in extending the interaction length. Thus, the ability to control acoustic attenuation would create efficient acousto-optic modulators. This invention addresses that issue by using acoustoelectric amplification, which reduces acoustic dissipation and improves the quality of holographic displays.
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