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.
Cortical Labs in Melbourne taught a dish of lab-grown neurons to play Pong in 2022. Now it has built what it describes as the world's first code-deployable biological computer, running on living human tissue rather than silicon chips, which is happily playing the 1993 shooter Doom. At first it didn't know how to move, aim or shoot. Then it would shoot two enemies and stop. So it's definitely learning.
It was another detail that the rest of the family apparently knew but had never told me; they thought I already knew. The biology mattered less to me than the secret. Dad had been adopted, it turned out. A classic affliction of the 1950s, in which young, unmarried couples were forced to give away their newborn babies.
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.
Scientists in the laboratory of Rendong Yang, PhD, associate professor of Urology, have developed a new large language model that can interpret transcriptomic data in cancer cell lines more accurately than conventional approaches, as detailed in a recent study published in Nature Communications. Long-read RNA sequencing technologies have transformed transcriptomics research by detecting complex RNA splicing and gene fusion events that have often been missed by conventional short-read RNA-sequencing methods.
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.
Last November, the UK government announced a bold plan to phase out animal testing in some areas of research. Animal tests for skin irritation are scheduled for elimination this year, and some studies on dogs should be slashed by 2030. The long-term vision is 'a world where the use of animals in science is eliminated in all but exceptional circumstances'.
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.
The newly released documents from the Justice Department shine additional light on how the convicted child sex criminal exhibited a fascination with transhumanism, a controversial movement in science and philosophy with a eugenicist mission: using cutting edge technology, including genetic engineering and AI, to advance the biology of the human race. They also reinforce how serious Epstein was about pursuing these ideas.
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.