RetSynth is a comprehensive tool for rapidly identifying all optimal and sub-optimal pathways for the bioproduction of high value target compounds
Mouse monoclonal anti-TLT-1 antibody for platelet research and preclinical studies of CVD and other thrombotic and inflammatory disorders.
UCSF investigators have developed a series of recombinant monoclonal antibodies against these target proteins. These antibodies could be applied as both diagnostic and therapeutic agents in the myriad of cancer types driven by RAS oncogenes.
The current state of the art
The market for Brain function monitoring is growing rapidly as a result of the increased incidence of neurological and neurodegenerative disorders. At a CAGR of 6.2%, the market is estimated to grow from USD 6.3 billion to 8.6 billion.
Problems with the current art
The current methods of monitoring brain function have restricted application. For example, the Glasgow Coma Scale (GCS) tests the patient’s consciousness to assess crude gross brain measurement and monitoring. An intracranial monitoring device, monitoring changes of intracranial pressure (ICP), is invasive. On the other hand, non-invasive methods such as traditional ultrasound are not sensitive to small and moderate changes of ICP.
A method that provides sensitive, non-invasive, and automated monitoring of brain function is lacking.
Advantages of our invention:
Scientist at AU developed a novel automated system and device that monitor brain function and changes in mass casualty environment, critical care transported of an injured patient and during surgical operations surgery. It utilizes stimulus and response sensors on the head of the subject and employs multiple test modals to calculate brain function score (GCS) or intracranial pressure changes. As a result, the system gives a rapid and sensitive reference as to the overall brain function. Data is graphically displayed, providing easy visualization and interpretation by a health care provider, enabling monitoring multiple patients simultaneously.
Non-provisional Application US16/562,776
Application Date 09/07/2018
Lead Inventor: Matt Lyon, MD https://www.augusta.edu/faculty/directory/view.php?id=MLYON
Deriving cardiomyocytes (CMs) from human embryonic stem cells (hESC-CMs) is a promising approach for generating an ideal and unlimited source of CMs. However, hESC-CMs do not possess the ability to contract like their adult counterpart due to their immature Ca2+ handling properties or the near absence of Ca2+-induced Ca2+ release (CICR) mechanisms.
Researchers at the University of California, Davis developed a method to improve the functional efficacy of stem cell-derived cardiomyocytes by manipulating specific Ca2+ handling properties of the cells. These manipulated hESC-CMs are expected to perform better than immature hESC-CMs currently used for cell replacement therapy, since their contractile force may better simulate the force found in vivo and render them better candidates for cell replacement therapy.
Instead of relying on one electrochemical signature, the proposed method uses multiple signatures to avoid false negative cases while providing more reliable and earlier Li-plating detection. This ML framework distinguishes Li-plating from normal solid electrolyte interface (SEI) dominant battery degradation. It uses a variety of physically meaningful signatures including capacity loss, coulombic efficiency, end of charge rest voltage, and post-charge open circuit voltage relaxation profiles. This framework is directly applicable to full cells without any special measurement requirements or additional sensors , and the classification can be made as early as 25 life cycles.
Challenge: Automated emotional recognition and environmental adaptation
Mental health challenges such as post-traumatic stress, autism spectrum disorders, and aging-related cognitive decline are difficult to treat, and access to trained therapists is limited. Existing sleep and meditation pods can sooth healthy individuals, but are not capable of recognizing and adapting to emotional responses.
The Technology: Interactive Emotive Spaces
Emotive booths, kiosks, and other adaptive structures interact with individual users by deriving a perceived emotional state associated with physiological data received from the user and dynamically using this perceived emotional state to control the shape and other characteristics of the environment in a manner intended to elicit emotional responses and improve mental health. This technology can augment caregiver efforts and enable greater productivity and independence of users.
• Machine learning enhances real-time emotional recognition overall and for individual users.
• Real-time changes to space to alter mood based on detected emotional state.
• Systems can be placed in homes or institutions (e.g., schools, police departments, libraries) for use when live therapists are not available.
• Physical and data privacy measures can allow for optional anonymity or user-authorized personalization and data access by a provider.
Provisional U.S. patent application has been filed.