Researchers at Stanford University have discovered a way to enhance the effectiveness of CAR-T cell therapeutics through inducing a more memory-like phenotype.
Stanford scientists have discovered that blocking an immune receptor signal can lead to increased fat uptake and weight reduction in patients suffering from obesity and associated diseases.
Stanford researchers have discovered RNA signatures that can be used to predict patient outcomes and identify optimal treatments in acute myeloid leukemia.
Researchers at Stanford have created a method to differentiate human pluripotent stem cells (hPSCs) into >90% pure hematopoietic stem cell (HSC)-like cells, which serve as progenitors to blood and immune cells.
Stanford researchers have developed an innovative approach for accurate and automated cell classification on H&E-stained images using multiplexed immunofluorescence (mIF) imaging, eliminating human annotations, and enhancing biological interpretability in histopathology.
A new deep-learning system called Atomic Rotationally Equivariant Scorer (ARES) significantly improves the prediction of RNA structures over previous artificial intelligence (AI) models.
The cost of DNA and RNA sequencing have decreased in recent years to aid effective research and clinical applications; however, the labor time and throughput of preparing DNA and RNA sequencing libraries remains a challenge.
Stanford researchers have found that a chemokine receptor antagonist can reduce immunosuppression in the tumor microenvironment and thereby delay tumor progression.
Inherently, the telomeres located at the ends of chromosomes shorten during each cycle of DNA replication and cell division, eventually topping DNA replication and leading to cell senescence and death.
Stanford researchers have developed easyBAT, a simplified solution integrating a microfluidic sample preparation device with a fully automated analysis pipeline for rapid, accurate and accessible solution for food allergy diagnosis at the point-of-care.
Researchers in the Noh Lab have developed a gait based, emotion recognition system using geophone sensors that are attached to the floor. People's gait changes under various emotions creating distinct structural vibration patterns.
Stanford researchers have developed a new technology, Variant-FlowFISH, to enable high-throughput, highly sensitive measurements of how variants, introduced via CRISPR, affect gene expression.