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Rapid antimicrobial susceptibility testing (AST) is a method for quickly determining the most effective antibiotic therapy for patients with bacterial infections. These techniques enable the detection and quantification of antibiotic-resistant and susceptible bacteria metabolites at concentrations near or below ng/mL in complex media. Employing bacterial metabolites as a sensing platform, the system integrates machine learning data analysis processes to differentiate between antibiotic susceptibility and resistance in clinical infections within an hour. With the results, a clinician can prescribe appropriate medicine for the patient's bacterial infection.

Researchers at the University of California, Davis have developed a technology providing the creation of stable analogs of glycosphingosines and gangliosides containing O-acetylated sialic acid for extensive biological and medical applications.

Researchers at the University of California, Davis have developed a technology to expedite COVID-19 diagnosis and treatment using viral spike protein (S-protein) targeted peptides Zika virus envelop protein.

An innovative sulfoxide-containing MS-cleavable cross-linker, DBrASO, specifically designed for cysteine residues and aimed at enhancing protein-protein interactions studies and protein complexes architecture analysis.

An innovative mass spectrometry platform that utilizes sulfoxide-containing MS-cleavable heterobifunctional photoactivated cross-linkers to enhance protein structural elucidation.

A breakthrough technology using insulin-secreting cells and stem cells to enhance wound healing and reduce scar formation.

Aberrant splicing contributes to the etiology of many inherited diseases. Pathogenic variants impact pre-mRNA splicing through a variety of mechanisms. Most notably, variants remodel the cis-regulatory landscape of pre-mRNAs by ablation or creation of splice sites, and auxiliary splicing regulatory sequences such as exonic or intronic splicing enhancers (ESE and ISE, respectively) and splicing silencers (ESS and ISS, respectively). Splicing-sensitive variants cripple the integrity of the gene, resulting in the production of a faulty message that is either unstable or encodes an internally deleted protein. Antisense oligonucleotides (ASOs) are a promising therapeutic modality for rescuing pathogenic aberrant splicing patterns as their direct base pairing abilities make them highly customizable and specific to targets. Although challenges such as toxicity, delivery and stability represent barriers to the clinical translation of ASOs, solutions to these challenges exist, as exemplified by the recent FDA approval of multiple ASO drugs.Generally, ASO's that target splicing mutations are limited to mutations in and around splicing enhancers and exonic mutations are commonly not targeted because of the idea that the mutation causes a significant change in protein function. 

Researchers at the University of California, Davis have developed an innovative method for efficient, high-yield production and easy purification of Human Milk Oligosaccharides (HMOs) using a Multistep One-Pot Multienzyme (MSOPME) process.

Researchers at the University of California, Davis have developed a method for preparing a glycan product containing a nonulosonic acid moiety by means of legionaminic acid transferase fusion proteins

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Researchers at the University of California, Davis have developed a method of using artificial intelligence for assessing the effectiveness or efficacy of drugs that is cheaper, faster, and more accurate than commonly used assay analyses.

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Researchers at UC Irvine have developed methods to facilitate the delivery of a high dose, low energy electron beam or X-ray in a compact manner.

Researchers at UC Irvine have developed an optical detection system for SARS-CoV-2 and other pathogens that features improvements in screening time, cost, sensitivity, and practicality. As vaccine availability, economic pressure, and mental health considerations has gradually returned society to pre-pandemic activities that require frequent and close interactions, it is imperative that SARS-CoV-2 detection systems remain effective.

Researchers at UC Irvine have developed a novel algorithm that more accurately filters raw blood pressure (BP) data collected from continuous non-invasive blood pressure sensors. The algorithm features improvements in eliminating baseline signal drift while maintaining signal integrity and BP estimation accuracy across significant hemodynamic changes.

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Researchers at UC San Diego have developed a dipeptide composed of two arginine (Arg-Arg) that is capable of inducing the assembly of citrate-capped gold nanoparticles (AuNPs-citrate). Surprisingly, the resulting Arg-Arg-AuNPs are stable over time as the peptide protects the particles from degradation. The assemblies can even be dried without any loss of particles. The assembly of AuNPs-citrate changes their optical properties and the color of the suspension turns from red to blue. Importantly, the assemblies can be dissociated with thiolated polyethylene glycol (HS-PEGs) molecules which leads to the recovery of the initial optical properties of the AuNPs, i.e. the red color of the suspension. Surprisingly, we have observed that such dissociation of AuNPs assemblies is not sensitive to the composition of the medium. It can thus be performed in biological fluids such as pure plasma, saliva, urine, bile, cell lysates or even sea water.

Scientists at UCSF have developed a novel class of BCR-ABL inhibitors that engages two binding sites in BCR-ABL simultaneously. This two-site binding (bitopic) mechanism of action is unprecedented against BCR-ABL, one of the most well-validated targets in oncology.

Long read nanopore sequencing can directly sequence RNA molecules, including rRNA, and result in full-length RNA sequences. rRNA sequencing is particularly useful for identifying microbes and full-length rRNA sequencing can identify microbes with post transcriptional modifications that confer antibiotic resistance. Such post transcriptional modifications are invisible to amplification based sequencing or other sequencing techniques that require reverse transcription.Before this technology was developed, there were few if any efficient methods for preparing rRNA libraries for direct RNA sequencing, particularly for microbial identification in either a clinical or an environmental setting.   

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Rhamnolipids (RLs) are a class of bacterially produced biosurfactants that possess antimicrobial as well as surface-active properties. While RLs have broad utility in industry as antimicrobial biosurfactants, their anionic nature limits the efficacy of these molecules in certain applications. Alternatively, rhamnolipid esters (RLEs) exhibit improved properties as nonionic surfactants. However, a major challenge in RLE application in the commercial arena is that, to date, they are only reliably accessed via chemical synthesis, a costly and unsustainable approach.To address this problem, UC Berkeley researchers have developed a novel, reliable microbial source for biosynthesized RLEs enabling their production in an efficient, sustainable, and renewable manner. Additionally, three novel rhamnolipid methyl ester (RLME) congeners have been produced and a new enzyme for RLE production identified. The produced RLEs are expected to be more effective than RLs in many ways, including antifungal activity and hydrocarbon solubilization.

Cardiovascular disease is the leading cause of death both worldwide and in the United States, with associated costs in the U.S. reaching approximately $229 billion, each, in 2017 and 2018. Early detection, which can drastically reduce both rates of death and treatment costs, requires access to facilities and highly-trained physicians that can be difficult to access in rural areas and developing countries—despite their prevalence of cardiovascular disease. Computer-based models that use, e.g., PCG (phonocardiogram), EKG (electrocardiogram), or other cardiac data, are a promising route to bridge the gap in standard-of-care for these underserved areas. However, current algorithms are unable to account for demographic features, such as race, sex, or other characteristics, which are known to affect both the structure of the heart and presentation of heart disease. To address this problem, UC Berkeley researchers have developed a new, cloud-based system for collecting a patient's continuous cardiovascular data, monitoring for and detecting disease, and keeping a doctor informed about the cardiac health of the patient. The system sends an alarm when disease or heart attack are detected. To generate the most accurate diagnoses by taking into account demographic information, the system includes private and ethical dataset collection and model-training techniques.

Plasma medicine has emerged as a promising approach for treatment of biofilm-related and virus infections, assistance in cancer treatment, and treatment of wounds and skin diseases. However, an important challenge arises with the need to adapt control policies, often only determined after each treatment and using limited observations of therapeutic effects. Control policy adaptation that accounts for the variable characteristics of plasma and of target surfaces across different subjects and treatment scenarios is needed. Personalized, point-of-care plasma medicine can only advance efficaciously with new control policy strategies.To address this opportunity, UC Berkeley researchers have developed a novel control scheme for tailored and personalized plasma treatment of surfaces. The approach draws from concepts in deep learning, Bayesian optimization and embedded control. The approach has been demonstrated in experiments on a cold atmospheric plasma jet, with prototypical applications in plasma medicine.