Yu and his team of researchers trained a machine-learning algorithm to do the work by showing it pictures of samples gathered during brain surgery, and then checking its work against those patients’ diagnoses. Getting that information, however, currently requires time-consuming testing. Surgeons use information about the genetic profile of a glioma tumor when deciding how much tissue to remove from a patient’s brain, as well as whether to implant wafers coated in a cancer-fighting drug. Only 17% of people with glioblastoma survive their second year after being diagnosed, according to the American Association of Neurological Surgeons. While glioma varies in severity, an aggressive form called glioblastoma can lead to death in less than six months if untreated. Surgeons use detailed diagnoses to guide them while they operate, Yu said, and the ability to get them rapidly could improve patients’ outcomes and spare them from multiple surgeries. The tool - called the Cryosection Histopathology Assessment and Review Machine, or CHARM - studies images to quickly pick out the genetic profile of a kind of tumor called glioma, a process that currently takes days or weeks, said Kun-Hsing Yu, senior author of a report released Friday in the journal Med. Ph.D., Neuroscience, Field Neurosciences Institute of Restorative Neurology, 2013ī.A.(Bloomberg) - An artificial-intelligence tool has shown promise at helping doctors fight aggressive brain tumors by identifying characteristics that help guide surgery. Kirchstein NRSA Postdoctoral Scholar, Institute for Regenerative Cures, Stem Cell Program, 2016
University of California, Davis, Medical Center, Stem Cell Program These platforms can turn on or enhance transcription of a gene, transcriptionally silence expression, cause permanent epigenetic changes, or remove a piece of DNA via targeted double stranded breaks essentially allowing for custom modifications to be made at the genomic level. They have used known information regarding JHD and CDKL5 deficiency to guide construction of potent, precise gene modifying modalities- CRISPR/Cas9 and TALE.
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These goals specifically address: A) how to deliver these potent therapeutics to maximize the biodistribution in the central nervous system B) how to increase the specificity of each construct to limiting off-target effects and C) how to minimize the immune response to increase safety and the therapeutic potential of this approach. His current research focuses on two major goals 1) The therapeutic application of transcription activator-like effector (TALE) and clustered regularly interspaced short palindrome repeats (CRISPR) to modify gene expression in genetically-linked pediatric neurological diseases and 2) the development of delivery systems that can safely and efficaciously target the central nervous system with our novel gene editing platforms. His team builds on the existing strengths and expertise at UC Davis and utilizes the necessary resources to develop a therapeutic pipeline in which precision medicine can be used to identify novel disease causing genetic variants to advance Precision Neurotherapeutics to clinical applications. Patient-derived samples can be used to create in vitro neuronal disease-in-a-dish models using novel induced neuron techniques. Gene variants linked to disease phenotype are examined for “actionable domains” for which we create therapeutic artificial transcription factors. His lab is identifying candidate sequences through whole genome sequencing and transcriptomics using a bioinformatics approach for structural variation discovery and genotyping that identify underlying common genetic variants. His research team focuses on genetically-linked neurological disorders such as CDKL5 deficiency (rare intractable pediatric epilepsy), Angelman’s Syndrome, and Huntington’s disease that are targetable with gene editing molecules in addition to some forms of brain cancer. He has focused on therapeutic development for neurodegenerative diseases, brain injury, and some forms of brain cancer. in Neuroscience from Central Michigan University and the University of Nantes.
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