Researchers at Stanford University have discovered a first-in-class covalent inhibitor that binds to activated Fis1 and prevents mitochondrial fission and dysfunction.
Stanford researchers have developed a strategy for generating chimeric transcription factors that enables exhaustion-resistant CAR-T cells and can be generalized to a wide range of cell therapies.
Stanford scientists have developed a novel method to accelerate the development of T cell target probes known as Rapid Identification of Peptide-ligands from Protein Antigen (RIPPA).
Stanford and Northwestern scientists have discovered that Platelet Factor 4 (PF4) is a biomarker for lymphatic diseases, such as lipedema and lymphedema, and can reliably differentiate them from obesity, which is a common misdiagnosis.
Researchers in the laboratories of Nathanael Gray and Gerald Crabtree at Stanford University have developed and synthesized new small molecule chemotherapeutics for targeted (and potentially less toxic) treatment of cancers having high BCL6 levels including lymphomas and other
Aging is one of the leading causes that is associated with brain dysfunction, degeneration, and disease. Progressive inflammation in the brain due to age adversely affects brain function and increases susceptibility to neurodegenerative diseases like Alzheimer's disease.
Stanford researchers have created a system that enables efficient fabrication of complex three-dimensional (3D) nanostructures via triplet-triplet-annihilation upconversion (TTA-UC).
?-thalassemia is a devastating blood disorder caused by mutations in the HBB gene encoding ?-globin, where treatment involves lifelong, costly management of the resulting lack of hemoglobin and hemolytic anemia.
Stanford scientists have developed a novel approach to help patients with short bowel syndrome by using intestinal lengthening. The solution involves injecting a degradable hydrogel into the intestinal wall to narrow the lumen and enable the confinement of a coiled spring.
Researchers in the Murmann Mixed Signal Group have developed a pipelined chip architecture with inverted residual and linear bottlenecks-based networks for energy efficient Machine Learning inference on edge devices.
Researchers at Stanford University have developed a method which integrates cell barcoding and high-throughput sequencing to quantify tumor growth in genetically engineered mouse models of human cancer (called 'Tuba-seq” for Tumor barcoding coupled with seq
Summary
Researchers at Stanford have developed a method enabling quantification of intracellular protein levels using oligonucleotide-barcoded antibodies.
Stanford scientists have created software, referred to as Symbolica, for automating model development for multiscale systems that can accelerate the generation of multi-physical models by 10^5 times what can be completed by hand.