Researchers at the University of California, Davis have developed engineered amyloid fibrils composed of modified β-solenoid proteins fused with pathogen-binding domains that provide ultra-sensitive, stable, and versatile platforms for detecting viruses and other pathogens.

Researchers at the University of California, Davis, have created a technology that uses engineered polynucleotides to deliver both an antigen and an enzyme that breaks down amino acids. This approach is designed to boost long-lasting memory T-cell responses, providing stronger protection against infectious diseases and cancer.

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Antibiotic resistance is a major issue in infectious disease treatment and prevention. In bacteria, the type III secretion system (T3SS) secretes effector proteins in the host cell, allowing the pathogen to infect. The T3SS is largely found on pathogens and not beneficial bacteria, so targeting the T3SS might have an advantage over using classic antibiotics, which disturb the beneficial human microbiome.

Researchers at the University of California, Davis have developed a technology that introduces vaccines that express macrophage-suppressing molecules to significantly enhance inflammatory T-cell functions for improved immune responses.

Researchers at the University of California, Davis have developed a potential therapeutic strategy aiming at disrupting intercellular communication of pathogens using quorum sensing molecules and silicon-based pharmacophores.

Progressive Multifocal Leukoencephalopathy (PML) is a devastating and often fatal demyelinating disease of the central nervous system caused by the reactivation of the JC virus (JCV). In immunocompromised patients, the absence of effective T cell surveillance allows the virus to infect and lyse oligodendrocytes, leading to irreversible neurological damage. UC Berkeley researchers have developed a method for discovering and engineering antigen-specific T cell receptors (TCRs) that specifically target JCV.

Researchers at the University of California, Davis have developed a vaccine platform utilizing non-replicating, metabolically active Cyborg Bacterial Pathogens to combat multi-antibiotic-resistant bacteria.

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.

Manual interpretation of real-time quantitative PCR (RT-qPCR) data is prone to human error, noise, and variability, leading to potential misdiagnosis or test redundancies. UC Berkeley researchers have developed a novel deep learning framework that significantly improves diagnostic accuracy by fusing Long Short-Term Memory (LSTM) networks with Vision Transformers (ViT). This hybrid architecture captures both sequential fluorescence patterns and structural amplification dynamics from raw time-series data and image-based renderings. By leveraging a uniquely curated dataset of over 24,000 verified samples, the system accurately discriminates between true-positive and true-negative samples, predicts viral dilutions, and forecasts patient re-test outcomes, providing an objective tool for early triage and increased laboratory throughput.

A novel approach to significantly enhance vancomycin's effectiveness against drug-resistant pathogens by conjugating it with a minimal teixobactin pharmacophore.