Researchers at the University of California, Davis have developed methods that combine immunotherapeutic agents with dual inhibitors to enhance cancer treatment efficacy and prolong patient survival.

High-conversion-ratio power converters used in compact Point-of-Load (PoL) applications, such as data centers or portable electronics, often face the challenge of large size and weight due to the necessary energy-storage components, particularly flying capacitors, while also struggling with switching losses that reduce efficiency. This innovation, developed by UC Berkeley researchers, addresses these issues with a novel regulating hybrid switched-capacitor (HSC) power converter topology referred to as a "Dual Inductor Switching Bus Converter" (DISB converter). The DISB converter combines an initial 2:1 switched-capacitor conversion stage with a Symmetric Dual-Inductor Hybrid (SDIH) conversion stage, capitalizing on the benefits of both. The initial 2:1 voltage reduction significantly reduces the overall volume and weight of the flying capacitors, while the SDIH stage contributes a reduced component count and an excellent switch stress figure of merit. Crucially, a proposed auxiliary circuit block enables near-zero-voltage conditions (partial soft-switching) within the initial 2:1 stage, which significantly improves the converter's overall efficiency.

Traditional environmental policymaking often struggles to efficiently target interventions to achieve multiple, complex air quality goals simultaneously across a geographic area. This innovation, developed by UC Berkeley researchers, addresses this challenge by providing a sophisticated, multi-objective optimization method for targeted reduction of air pollution. The method generates a comprehensive mitigation pathway by integrating several modules: a forward module to model pollutant concentrations, a target concentration surface that defines the policy goals, a prioritization module to assess uncertainty and importance via a prioritization covariance matrix, and a Bayesian inversion module to estimate optimum emissions required to meet the target. This systematic, data-driven approach culminates in a mitigation pathway that guides the performance of specific pollution control measures, offering a significant advantage over conventional, less targeted policy-making by ensuring resources are directed where they will have the maximum environmental impact.

Current methods for treating nervous system disorders often rely on generalized approaches that may not optimally address the individual patient's specific pathology, leading to suboptimal outcomes. This innovation, developed by UC Berkeley researchers, provides a method to identify the most critical, or "influential," nodes within a patient's functional connectivity network derived from time-series data of an organ or organ system. The method involves obtaining multiple time-series datasets from an affected organ/system, using them to map the functional connectivity network, and then determining the most influential nodes within that network. By providing this specific and personalized information to a healthcare provider, a treatment can be prescribed that precisely targets the respective organ corresponding to these influential nodes. This personalized, data-driven approach offers a significant advantage over conventional treatments by focusing intervention on the most impactful biological targets, potentially leading to more effective and efficient patient care.

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Researchers at the University of California, Davis have developed a biosensor technology for rapid, sensitive detection, purification, and identification of nucleic acids in complex biological fluids.

CRISPR-derived nucleases offer unprecedented precision and ease of use for targeting specific genomic sites. However, the efficient delivery of gene editing tools into plant cells remains a significant hurdle. Current methods rely on a laborious and time-consuming tissue culture pipeline and can induce undesirable changes to the genome and epigenome. To circumvent these limitations, one alternative is to use plant viral vectors for the delivery of compact gene editors and their guide RNA (gRNA). UC Berkeley and UC Davis inventors found that the use of tobacco rattle virus (TRV) vectors to deliver reRNA and variant TnpB proteins to plants results in surprisingly high efficiencies of genome editing not only in the infiltrated cells, but also systemically (e.g., seeds and non-infiltrated leaves). Delivery via TRV caused systemic viral spread into the shoot apical and floral meristematic regions, leading to unexpectedly high efficiencies of genome editing in non-infiltrated cells (i.e., spread of genome editing), for example, surprisingly high efficiencies of genome editing in non-infiltrated systemic leaves as well as in the germline (e.g., seeds).

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