The Austin inaugural lecture was held on October 25th, 2022, and delivered by Prof. Tommy Kaplan from the Department of Developmental Biology and Cancer Research at IMRIC and the School of Computer Science and Engineering. During his presentation, Prof. Kaplan emphasized the significance of DNA methylation, which influences the function of genes in our bodies. He presented a map, created by his team, that illustrates the variations of this process across different cells. This map offers insights that could potentially enhance our understanding of diseases and improve early detection. Furthermore, he introduced an innovative method devised by his team that estimates a person's age by analyzing their blood DNA. Impressively, this method can predict age with an accuracy of approximately two years, which can have applications in aging research and forensic science. He wrapped up his talk by discussing how alterations in our DNA can provide clues regarding our actual age and overall well-being.
The second Austin lecture was held on January 23, 2024, and was delivered by Prof. Shahar Arzy from the Department of Medical Neurobiology at IMRIC, Faculty of Medicine of the Hebrew University, and the Department of Neurology at the Hadassah Medical Center. In his lecture, titled 'New Insights into Alzheimer's Disease in the Era of Computational and Data Revolutions,' Prof. Arzy explored the evolving understanding of Alzheimer’s disease (AD), traditionally dominated by the amyloid hypothesis. This hypothesis, which posits a linear progression from amyloid accumulation to tau deposition, neurodegeneration, and cognitive decline, has shaped AD research for over three decades. However, its partial explanatory power and the general failure of anti-amyloid drugs have opened the door to novel, more nuanced approaches. Prof. Arzy discussed the emergence of probabilistic, multifactorial, and network-based models, powered by the recent advances in data science and computational methods. He offered an integrative perspective, combining cognitive, neurobiological, clinical, and computational approaches, to provide a broader and more comprehensive understanding of Alzheimer's disease.
