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As of June 2020, the pandemic caused by SARS-CoV-2 infections (Coronaviral Disease 2019 (Covid-19)) caused about 9 million infections and about 460,000 deaths worldwide. The pandemic is expected to expand in the late 2020, particularly, because of the lack of a therapeutically effective treatment for the disease.   UC Berkley researchers have discovered compositions and methods treating an RNA virus infection such as SARS-CoV-2 infections by administering combined effective amounts of an RNA-dependent RNA polymerase inhibitor, such as remdesivir, and a second therapeutic agent for treating infection with an RNA virus.


As of June 2020, the pandemic caused by SARS-CoV-2 infections (Coronaviral Disease 2019 (Covid-19)) caused about 9 million infections and about 460,000 deaths worldwide. The pandemic is expected to expand in the late 2020, particularly, because of the lack of a therapeutically effective treatment for the disease. Therefore, methods of treating SARS-CoV-2 infection are desired.   UC Berkeley inventors have developed methods of treating a SARS-CoV-2 infection in a patient infected with SARS-CoV-2 by administering to the patient a therapeutically effective amount of an inhibitor of lipogenesis. The inhibitor of lipogenesis can be an inhibitor of a lipogenic enzyme or an activator of 5’AMP-activated protein kinase (AMPK).  

Brown Adipose Tissue Myosin II Activators for Metabolic Therapy

The inventors have uncovered a novel brown adipose tissue (BAT) activation pathway based on cellular tension generated by actomyosin. Initial tests of predicted myosin II activators show the ability to increase the expression of uncoupling protein 1 (UCP1), a pivotal determinant of uncoupled respiration, in murine and human brown and beige cells. This strategy could be the foundation for a novel strategy to treat obesity-associated disorders such as type-2 diabetes, cardiovascular disease, and non-alcoholic fatty liver disease.

High Performance Iron Electrocoagulation Systems for Removing Water Contaminants

The inventors have developed an iron electrocoagulation (Fe-EC) system for arsenic removal. The system offers a highly effective, low cost, robust method for removing arsenic from groundwater used for drinking, at community scale (10,000 liters per day).The main advance of this invention is to replace the assembly of inter-digited flat steel plates with an assembly of spiral-wound or folded and inter-digited two steel sheets separated only with perforated insulating spacers. This substantially reduces the energy consumption in comparison to other Fe-EC reactors, and allows for larger flow rates for a given reactor size than the standard inter-digited flat plate configuration. This advance is possible because the system relies on: externally added (ppm quantities) of oxidizer (H2O2), and a newly-discovered effect that allows consistent iron dissolution at high current densities. High current density also produces copious quantities of micro-bubbles of H2 gas, which flushes the space between the electrodes continuously during operation, preventing the clogging that has defeated earlier attempts.In a typical Fe-EC reactor, parallel inter-digited plates of mild steel are inserted into the contaminated water and a small DC voltage is applied between alternate plates to promote anodic dissolution of F(0) metal to release Fe(II) ions into the contaminated water. The Fe(II) ions react with dissolved oxygen in the water to produce Fe(III) that is used to capture the contaminants. Typically, an assembly of flat inter-digited parallel steel plates, with nearest neighbor spaced 2 cm to 5 cm, is used in Fe-EC reactors. Occasionally, externally added or in-situ produced oxidants may be used (e.g. externally added strong oxidants such as H2O2, O3, Chlorine, Permanganate, etc., or in-situ produced strong oxidants such as H2O2 using carbon based cathodes). 

Traceless Linker for Aliphatic Amines that Rapidly and Quantitatively Fragment

The inventors have developed a traceless linker (TRAILER), which can for the first time modify aliphatic amines and release them rapidly and quantitatively after disulfide reduction. TRAILER can reversibly modify the lysine residues on the Cas9 protein, with the cell penetrating peptide Arg10, and is able to generate a self-delivering Cas9 RNP that can edit cells without transfection reagents.Reduction sensitive linkers have the potential to transform the field of drug delivery due to their ease of use and selective cleavage in intracellular environments. However, despite their compelling attributes, using reduction sensitive linkers for biomolecule conjugation reactions has been challenging in the past, because linkers have not been developed that can efficiently modify aliphatic amines and release them rapidly and completely after reduction. Previous efforts to develop reduction sensitive self-immolative linkers for aliphatic amines have been stymied due to their poor leaving group ability and high pKa values. 

Combination Of Air Lubrication And Super Hydrophobic Frictional Drag Reduction

This technology combines air layer frictional drag reduction (ALDR) with super hydrophobic surfaces (SHS) to achieve frictional drag reduction of ALDR with significantly reduced gas flux. Thus, enabling increased net energy savings. The stable air layer is achieved with lesser gas flux when utilizing a SHS.Periodic air layers may replenish SHS, enabling drag reduction with reduced energy cost. Combinations of SHS and regular or other non-SHS surface may be used to control spreading of gas, thus facilitating formation of ALDR using discrete gas injection points better than previously achievable. Such surface variations could also be used to preferentially guide gas towards or away from propulsion, depending on desired outcome. By controlling ALDR regionally or globally on a surface, with or without SHS, this technology modifies flow around a hull. This mediates forces on partially or fully submerged objects, enabling control of flow patterns, resistance, steering, and/or dynamics.

Multi-Agent Navigation And Communication Systems

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions. However, as the number of autonomous vehicles on the road increases the complexity of the computations needed to safely operate all of the autonomous vehicles grows rapidly. across multiple vehicles, this creates a very large volume of computations that must be performed very quickly (e.g., in real or near-real time).   Thus, treating each autonomous vehicle as an independent entity may result in inefficient use of computing resources, as many redundant data collections and computations may be performed (e.g., two vehicles in close proximity may be performing computations related to the same detected object). To address this issue, researches at UC Berkeley proposed algorithms for the management and exchange of shared information across nearby and distant vehicles.According to the proposed arrangement, autonomous vehicles may share data collected by their respective sensor systems with other autonomous vehicles and adjust their operations accordingly in a manner that is more computationally efficient. This can not only increase safety but at the same time reduce computational load required by each individual vehicle.

Temporal And Spectral Dynamic Sonar System For Autonomous Vehicles

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions.  Critical to the performance of autonomous vehicles is the ability to detect other objects in the autonomous vehicle’s vicinity and adjust accordingly. To do so, many autonomous vehicles utilize a variety of sensors, including sonar. Although these sensor systems have been shown to improve the safety of autonomous vehicles by reducing collisions, the sensor systems tend to be computationally inefficient.  For instance, the sensor systems may generate large volumes of data that must be processed quickly (e.g., in real or near-real time).  The performance of excessive computations may delay the identification and deployment of necessary resources and actions and/or increase the cost of hardware on the vehicle making it less financially appealing to the consumer. Researches at UC Berkeley proposed algorithms for temporally and spectrally adaptive sonar systems for autonomous vehicles. These allow utilization of existing sonar system in an adaptive manner and in interface with existence hardware/software employed on autonomous vehicles.