Using CRISPR-Cas9 and adeno-associated virus (AAV)-mediated homology-directed repair, we targeted CAR integration into the endogenous human TCR alpha locus (TRAC). TRAC-CAR T cells display dynamic CAR expression that delays exhaustion and improves tumour control in xenograft and immunocompetent models. This work has been critical for the development of allogeneic CAR T cell therapy, as it disrupts the TCR after transgene insertion—a necessary step to limit graft-versus-host disease.
GEMINI leverages a computationally designed protein assembly as an intracellular memory device to record the history of individual cells. GEMINI grows predictably within live cells, capturing cellular events as tree-ring-like fluorescent patterns for imaging-based retrospective readout. Absolute chronological information of activity histories is attainable with hour-level accuracy.
Biology is undergoing a transformation. After centuries of studying life as it evolves naturally, researchers are now using a combination of computation and genome engineering to intervene, generating new proteins and even whole bacteria from scratch. The use of artificial-intelligence tools to design biological components, an approach known as generative biology, is set to turbocharge this area of research. Just last year, scientists used AI-assisted design to produce artificial genes that can be expressed in mammalian cells.
Martschenko's argument is largely that genetic research and data have almost always been used thus far as a justification to further entrench extant social inequalities. But we know the solutions to many of the injustices in our world-trying to lift people out of poverty, for example-and we certainly don't need more genetic research to implement them. Trejo's point is largely that more information is generally better than less.
OpenAI is updating ChatGPT's deep research tool with a full-screen viewer that you can use to scroll through and navigate to specific areas of its AI-generated reports. As shown in a video shared by OpenAI, the built-in viewer allows you to open ChatGPT's reports in a window separate from your chat, while showing a table of contents on the left side of the screen, and a list of sources on the right.
The exponential growth of scientific literature presents an increasingly acute challenge across disciplines. Hundreds of thousands of new chemical reactions are reported annually, yet translating them into actionable experiments becomes an obstacle1,2. Recent applications of large language models (LLMs) have shown promise3,4,5,6, but systems that reliably work for diverse transformations across de novo compounds have remained elusive. Here we introduce MOSAIC (Multiple Optimized Specialists for AI-assisted Chemical Prediction), a computational framework that enables chemists to harness the collective knowledge of millions of reaction protocols.
Generalist models "fail miserably" at the benchmarks used to measure how AI performs scientific tasks, Alex Zhavoronkov, Insilico's founder and CEO, told Fortune. " You test it five times at the same task, and you can see that it's so far from state of the art...It's basically worse than random. It's complete garbage." Far better are specialist AI models that are trained directly on chemistry or biology data.