Revealing a drug’s mechanism of action (MOA) is costly and time-consuming. In this study, we used deep learning to extract temporal mitochondrial phenotypic features after exposure to drugs with known MOAs using re-identification algorithms. The trained model could then predict the MOAs of unidentified substances, facilitating phenotypic screening-based drug discovery and repurposing. This is a…

Saturday, Sept. 7, 7:00-11:00 p.m. McKinney, Texas — Step back in time and experience a night of prehistoric proportions at the Heard Natural Science Museum & Wildlife Sanctuary! Join us for an epic adults-only (ages 21+) evening under the stars featuring the original 90’s blockbuster “Jurassic Park.” But hold onto your fossils because this isn’t…

Abstract Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA) is crucial, yet current approaches are costly and low-throughput. Here we present an approach for MOA identification by profiling changes in mitochondrial phenotypes. By temporally imaging mitochondrial morphology and membrane potential, we established a pipeline for monitoring time-resolved mitochondrial images, resulting…

Abstract Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures…

A scanning microscope at Center for Quantum Nanoscience in Ewha Womans University, Seoul.Credit: Caroline Hommel, QNS With more researchers per capita and a higher spend on research and development than any leading country in the Nature Index, it’s clear that South Korea invests heavily in science. But its ‘bang for buck’ — judged by pitting…

Malte Elson is blunt when it comes to science’s ability to self-correct. “The way we currently treat errors doesn’t work,” he says. To prove his point, Elson, a psychologist at the University of Bern, highlights a well-known 2010 paper1 by economists Carmen Reinhart and Kenneth Rogoff at Harvard University in Cambridge, Massachusetts. “This paper became…

Last month, UK researchers welcomed the appointment of one of their own as science minister, the ultimate position of power in British research. Patrick Vallance is a former government science adviser who became a household name during the COVID-19 pandemic. Following the Labour Party’s landslide election win on 4 July, Prime Minister Keir Starmer, who…

Abstract Artificial intelligence (AI) researchers currently believe that the main approach to building more general model problems is the big AI model, where existing neural networks are becoming deeper, larger and wider. We term this the big model with external complexity approach. In this work we argue that there is another approach called small model…

Abstract Artificial intelligence (AI) researchers currently believe that the main approach to building more general model problems is the big AI model, where existing neural networks are becoming deeper, larger and wider. We term this the big model with external complexity approach. In this work we argue that there is another approach called small model…

An event highlighting the convergence of art, science and nature returns Saturday to Bernheim Forest and Arboretum in Clermont. CONNECT at Bernheim, an annual event, is scheduled from 5:33 p.m. to 11:33 p.m. × This page requires Javascript. Javascript is required for you to be able to read premium content. Please enable it in your…