Networks of excitable cells play a fundamental role in life, from the beating heart to the conscious brain.
In the time it takes to drink your coffee, experts in the field will explain how they are using Axion's technology to better understand life's circuitry.
Pour yourself a cup of coffee and learn more about life's circuitry.
The neuromuscular junction is the synapse formed between a motor neuron and a muscle fiber. Diseases that impair the functioning of muscles, either directly or indirectly via motor neurons, are referred to as neuromuscular disorders. Neuromuscular disorders include ALS, myasthenia gravis, and the muscular dystrophies such as Duchenne's. Collectively these disorders exceed an incidence of 1 in 3,000.
Although there is a strong genetic understanding of many of these disorders, the poor translatability of animal models to humans has hindered the development of treatments for these diseases. Consequently, there is a need for a model that more faithfully recapitulates the physiology of the human neuromuscular junction. In this Coffee Break Webinar, Elliot Swartz (UCLA) discusses how he is building a light controlled hiPSC model of a neuromuscular junction to help better understand neuromuscular disorders.
Autism, also known as autism spectrum disorder, is a range of conditions classified as neurodevelopmental disorders. Individuals diagnosed with autism show challenges with social skills, repetitive behaviors, speech and nonverbal communication. Autism is estimated to affect about 1% of people, or 62.2 million globally. While specific causes of autism have yet to be found, there is a strong genetic basis to the disorder.
The genetics of autism are complex meaning better methods are required to help understand the genetic risk factors that underlie autism. In this Coffee Break Webinar, Dr. Michael Nestor (The Hussman Institute for Autism) discusses how studying the spontaneous firing activity of patient-derived iPSC neurons in an MEA assay is helping to build a model of autism.
Neurotoxicity is a leading cause of pharmaceutical compound attrition. Drug-induced seizures can deprive the brain of oxygen resulting in brain injury and an increased incidence of mortality. These seizures are the result of excessive and synchronous firing of cortical neurons in the brain.
Improved assays are required to identify seizurogenic compounds in drug discovery. Microelectrode array assays have emerged as a promising tool to predict seizure risk by measuring drug-induced changes to the spontaneous firing activity of neural networks in vitro. In this Coffee Break Webinar, Dr. Benjamin Bader (NeuroProof) discusses how artificial intelligence-based machine-learning can be applied to these neural MEA datasets to improve the prediction of seizure risk.
In our daily lives we are exposed to thousands of commercially used chemicals. Many of these chemicals are not toxic at typical exposure levels, but for thousands of chemicals, toxicological information is lacking. The National Academy of Sciences report on ‘‘Toxicity testing in the 21st century’’ highlighted the need for efficient methods to screen chemicals (e.g. insecticides) for their potential to cause toxicity.
When screening compounds for the potential to disrupt the nervous system, measuring neural activity is crucial, since many neurotoxins are known to disrupt ion channel, and receptor activity in the absence of other biochemical or structural changes to the cell. In this Coffee Break Webinar, Dr Lorena Saavedra (NeuCyte) discusses how measuring compound-induced changes to the spontaneous firing activity of human stem cell-derived neural cells in an MEA assay helped detect potentially harmful neurological side effects of compounds such as pyrethroid insecticides.
“Man on Fire” syndrome, also known as Inherited Erythromelalgia (IEM), is a chronic pain syndrome characterized by burning pain in the hands and feet. The chronic pain of most patients with IEM cannot be relieved by common pain killers making this disease a major unmet medical need.
Precision Medicine is an approach that tailors the prescribed medical treatment to the individual’s genetic makeup. In this Coffee Break Webinar, Dr Yang Yang (Purdue University) discusses advances in the treatment of IEM using a pharmacogenomic approach. The drug responsiveness of different genetic mutations associated with IEM were probed in an in vitro Maestro MEA assay, with the results helping to predict the effective treatment of these IEM patients in the clinic.
This precision medicine approach, guided by genomic analysis and functional profiling, provides a promising new way to extinguish the fire of the burning man.
Trends in cardiac safety testing, as exemplified by CiPA and JiCSA, emphasize a move beyond surrogate measures of Proarrhythmia. The hiPSC-cardiomyocyte and multiwell microelectrode array (CM-MEA) assay offers an ideal approach to evaluate proarrhythmic indicators in vitro. Join Axion BioSystems' Daniel Millard for this Coffee Break Webinar as he discusses advances in arrhythmia detection using Local Extracellular Action Potential (LEAP) technology to support next-generation CM-MEA assays.
Sixty-five million people world-wide suffer from epilepsy. Epilepsy is characterized by seizures, which are the result of excessive nerve activity in the brain. This condition is a range of disorders that vary from mild to severe, some of which can be life-threatening. While treatments are available, finding the optimal medication for any patient involves a period of trial-and-error during which both doctor and patient will try to find a solution that improves their quality of life. Unfortunately for one-third of people with epilepsy, the available treatments will not work. The need to better understand the underlying causes and develop better treatments for epilepsy are clear.
Join Columbia University's Mike Boland and K. Melodi McSweeney for this Coffee Break Webinar as they discuss the power of utilizing genetically engineered mice to explore the neuronal networks associated with epilepsy. With a better understanding of these brain networks it could be possible to classify different types of epilepsy, allowing the most effective medication to be prescribed first time.