An advanced AI-driven system for synthetic medical data generation and precise segmentation of cardiac MRI to enhance accuracy and efficiency in cardiovascular health.

Researchers at the University of California, Davis have developed an AI-powered framework that bridges the gap between predictive feature analysis and actionable interventions by extracting evidence-based recommendations from scientific literature.

Researchers at the University of California, Davis have developed a nanoparticle system combining photothermal therapy and chemotherapy for enhanced cancer treatment.

Amyloid-β (Aβ) is a protein that is implicated in Alzheimer’s disease. Aβ oligomers aggregate to form amyloid plaques, which are found in the brains of individuals with Alzheimer’s disease. These plaques have high polydispersity; they vary in shape and size. Previously, researchers at UC Santa Cruz demonstrated that using a racemic mixture of Aβ promoted fibril formation, an aggregation that is less neurotoxic than plaques of high polydispersity. Furthermore, these racemic counterparts form rippled β-sheets.

Nucleic acids such as DNA and RNA find many different applications in research. They can act as research reagents, diagnostic agents, therapeutic agents, and more. Nucleic acids are made by enzymes, which are macromolecules that catalyze reactions. Since nucleic acids are so frequently used in research, there is continued interest in finding new and improved ways to synthesize them. Researchers at UC Santa Cruz have developed ways to continuously synthesize nucleic acids without the use of enzymes.

Researchers at the University of California, Davis have engineered dominant negative CD40L mutant polypeptides that inhibit CD40/CD40L-mediated signaling, offering therapeutic potential for inflammatory, immune disorders, and cancer with improved safety profiles.

Researchers at the University of California, Davis have developed a computer-implemented method to identify viral mutations that enhance transmission and predict their prevalence in populations over time.

Clustered regularly interspaced short palindromic repeats (CRISPR) screening is a cornerstone of functional genomics, enabling genome-wide knockout studies to identify genes involved in specific cellular processes or disease pathways. The success of CRISPR screens depends critically on the design of effective guide RNA (gRNA) libraries that maximize on-target activity while minimizing off-target effects. Current CRISPR screening lacks tools that can natively integrate next-generation sequencing (NGS) data for context-specific gRNA design, despite the wealth of genomic and transcriptomic information available from modern sequencing approaches. Traditional gRNA design tools have relied on static libraries with limited genome annotations and outdated scoring methods, lacking the flexibility to incorporate context-specific genomic information. Off-target effects are also a concern, with CRISPR-Cas9 systems tolerating up to three mismatches between single guide RNA (sgRNA) and genomic DNA, potentially leading to unintended mutations that could disrupt essential genes and compromise genomic integrity. Additionally, standard CRISPR library preparation methods can introduce bias through PCR amplification and cloning steps, resulting in non-uniform gRNA representation.

A transgenic zebrafish model enabling controlled pancreatic β-cell ablation to simulate chronic hyperglycemia and study diabetes-related pathology.

Production of chiral chemicals through biotransformation requires an oxidoreductase enzyme and an efficient redox cofactor system comprising electron donors coupled to a dehydrogenase enzyme to regenerate the reduced cofactors.The researchers at the University of California, Irvine (UCI), provide a way to computationally design and optimize hydrogenase enzyme interaction with biomimetic cofactor analogs to improve increase enzymatic efficiency. The group has produced the modified enzyme and show that it is capable of a diverse range of chemical biotransformation.

POEM is a groundbreaking 3D bioprinting technology enabling high-resolution, multi-material, and cell-laden structure fabrication with enhanced cell viability.

A revolutionary method for improving the efficiency and quality of reprogramming adult cells into stem cells or other therapeutically relevant cell types via adhesome gene manipulation.

The rapid and accurate analysis of real-time quantitative polymerase chain reaction (qPCR) data is critical for precise disease diagnostics, genetic research, and pathogen detection. However, manual interpretation is prone to human error, and current automated systems often struggle with noise and variability, leading to misdiagnosis or inaccurate results. Researchers at UC Berkeley have developed a Deep Learning System for Enhanced qPCR Data Analysis that addresses these challenges. The system utilizes an advanced deep learning model to analyze raw qPCR data in real-time, significantly improving diagnostic accuracy by identifying subtle patterns and anomalies that are difficult for human experts or conventional software to detect. This innovative approach leads to more reliable and faster results compared to traditional methods.

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A novel RT assay for detecting chemical adducts on RNA, utilizing fluorescence quenching to indicate the presence of modifications.

Innovative cell lines enabling precise genetic modifications to advance research in gene function, disease modeling, and potential therapeutic interventions.

A novel motorized tool designed to precisely deliver retinal tissue during transplantation, enhancing outcomes for patients with retinal degeneration.

An advanced geometric method for comprehensive 3D cardiac strain analysis, enhancing diagnosis and monitoring of myocardial diseases.

A novel device leveraging centrifugal microfluidics to accelerate bacterial growth and rapidly determine antibiotic susceptibility.

This technology offers a sophisticated approach to detecting coronavirus infections, including COVID-19, and assessing immunity through advanced biochip systems

Nucleic acid therapies hold vast therapeutic potential. FDA approved therapies include mRNA vaccines against SARS-COV2 and CRISPR/CAS9 treatment to treat sickle cell.  Both therapies use non-viral methods to deliver designer nucleic acid therapies to cells. However, a limitation of these approaches is the lack of organ and cell-specific delivery. Controlling gene delivery and expression in various cell subsets is challenging. UC Berkeley researchers have shown that the nanoscale topology of CpG oligodeoxynucleotide (CpG-ODN) motifs can be used to stimulate various immune cell subsets and alter gene expression from exogenously delivered mRNA in distinct immune cell subsets. CpG-ODNs of different classes are known to induce different inflammatory profiles in immune cells based on the structure and nanoscale topology of the short DNA strand. The researchers have found novel nanostructures which can be used to present or deliver CpGs to various cell subsets and regulate gene expression in these subsets.

This technology enables precise, selective manipulation of magnetically barcoded materials, distinguishing them from background magnetic materials

Advances in biological research have been greatly influenced by the development of organoids, a specialized form of 3D cell culture. Created from pluripotent stem cells, organoids are effective in vitro models in replicating the structure and progression of organ development, providing an exceptional tool for studying the complexities of biology. Among these, cerebral cortex organoids (hereafter "organoid") have become particularly instrumental in providing valuable insights into brain formation, function, and pathology. Despite their potential, organoid experiments present several challenges. Organoids require a rigorous, months-long developmental process, demanding substantial resources and meticulous care to yield valuable data on aspects of biology such as neural unit electrophysiology, cytoarchitecture, and transcriptional regulation. Traditionally the data has been difficult to collect on a more frequent and consistent basis, which limits the breadth and depth of modern organoid biology. Generating and measuring organoids depend on media manipulations, imaging, and electrophysiological measurements. Historically are labor- and skill-intensive processes which can increase risks associated with experimental validity, reliability, efficiency, and scalability.

Achieving precise and tunable control over endogenous gene expression in eukaryotic cells remains a significant challenge, particularly for therapeutic applications or detailed biological studies where fine-tuning is required rather than complete on/off switching. This innovation, developed by UC Berkeley researchers, addresses this by providing a novel, programmable method for transcriptional tuning. The innovation is a two-domain fusion protein comprising the transcriptional repression domain (TRD) of the methyl-CpG-binding domain (MBD) protein MeCP2 linked to a dead Cas9 (dCas9) domain. When combined with a single guide RNA (sgRNA) that targets a specific endogenous gene, this fusion protein partially inhibits, or "tunes," the expression of that gene. Unlike traditional methods like RNAi or full CRISPR interference (CRISPRi), which often aim for complete knockdown, this system offers a highly specific and titratable way to dial down gene expression, providing a distinct advantage in studies requiring subtle modulation of gene dosage or for developing dose-dependent therapeutic strategies.

This invention developed by UC Berkeley researchers provides a novel FRET-Cal Screening Platform to identify positive and negative modulators of membrane signaling proteins. The platform addresses the need for efficient and reliable methods to screen for compounds that can control the activity of these receptors. The technology utilizes a receptor protein with a Förster resonance energy transfer (FRET) pair, composed of a donor and acceptor fluorophore, to screen for candidate compounds. The FRET pair allows for the direct measurement of changes in protein conformation upon binding, providing a highly sensitive and specific method for identifying potential modulators. This platform offers a significant advantage over traditional screening methods by providing a high-throughput, real-time assay for drug discovery and therapeutic development.