We present a DNA self-assembly based molecular data writing strategy to enable parallel movable-type printing for scalable DNA storage.
Memorial Sloan Kettering Cancer Center-led researchers have identified a small molecule called gliocidin that kills glioblastoma cells without damaging healthy cells, potentially offering a new therapeutic avenue for this aggressive brain tumor.
Glioblastoma remains one of the most lethal primary brain tumors, with current therapies failing to significantly improve patient survival rates. Glioblastoma is difficult to treat for several reasons. The tumor consists of many different types of cells, making it difficult for treatments to target them all effectively.
There are few genetic changes in the cancer for drugs to target, and the tumor creates an environment that weakens the body’s immune response against it. Even getting medications near targets in the brain is challenging because the protective blood-brain barrier blocks entry for most potential drug treatments.
Researchers at University of California San Diego analyzed the genomes of hundreds of malaria parasites to determine which genetic variants are most likely to confer drug resistance.
The findings, published in Science, could help scientists use machine learning to predict antimalarial drug resistance and more effectively prioritize the most promising experimental treatments for further development. The approach could also help predict treatment resistance in other infectious diseases, and even cancer.
“A lot of drug resistance research can only look at one chemical agent at a time, but what we’ve been able to do here is create a roadmap for understanding antimalaria drug resistance across more than a hundred different compounds,” said Elizabeth Winzeler, Ph.D., a professor at UC San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences and the Department of Pediatrics at UC San Diego School of Medicine.
Free ebook #freeisgood — 50th Anniversary Edition ~ Thomas S. Kuhn.
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“One of the most influential books of the 20th century,” the landmark study in the history of science with a new introduction by philosopher Ian Hacking (Guardian, UK).First published in 1962, Thomas Kuhn’s The Structure of Scientific Revolutions” reshaped our understanding of the scientific enterprise and human inquiry in general.” In it, he challenged long-standing assumptions about scientific progress, arguing that transformative ideas don’t arise from the gradual process of experimentation and data accumulation, but instead occur outside of “normal science.” Though Kuhn was writing when physics ruled the sciences, his ideas on how scientific revolutions bring order to the anomalies that amass over time in research experiments are still instructive in today’s biotech age (Science).
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Australian researchers have created building blocks out of DNA to construct a series of nano-scale objects and shapes, from a rod and a square to an infinitesimally small dinosaur.
The approach turns DNA into a modular material for building nanostructures – thousands of times narrower than a human hair. Developed by researchers from the University of Sydney Nano Institute and published in the journal Science Robotics, it suggests exciting possibilities for future use of nanobot technology.
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This video explores fascinating engineering solutions hiding in plain sight — ingenious designs that solve complex problems through elegant simplicity. From shoes that expand when stretched to windshields with hidden patterns, discover how everyday objects incorporate remarkable engineering innovations.
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A quiet revolution is brewing in labs around the world, where scientists’ use of AI is growing exponentially. One in three postdocs now use large language models to help carry out literature reviews, coding, and editing. In October, the creators of our AlphaFold 2 system, Demis Hassabis and John Jumper became Nobel Laureates in Chemistry for using AI to predict the structure of proteins, alongside the scientist David Baker, for his work to design new proteins. Society will soon start to feel these benefits more direct ly, with drugs and materials designed with the help of AI currently making their way through development.
In this essay, we take a tour of how AI is transforming scientific disciplines from genomics to computer science to weather forecasting. Some scientists are training their own AI models, while others are fine-tuning existing AI models, or using these models’ predictions to accelerate their research. Scientists are using AI as a scientific instrument to help tackle important problems, such as designing proteins that bind more tightly to disease targets, but are also gradually transforming how science itself is practised.
Researchers at the University of Twente, Netherlands, have made an advancement in bioprinting technology that could transform how we create vascularized tissues. Their innovative bioink, recently featured in Advanced Healthcare Materials, introduces a way to precisely guide the growth and organization of tiny blood vessels within 3D-bioprinted tissues. The tiny blood vessels mimic the intricate networks found in the human body.
3D-printed organs have the potential to revolutionize medicine by providing solutions for organ failure, and tissue damage and developing new therapies. But a major challenge is ensuring these printed tissues receive enough nutrients and oxygen, which is critical for their survival and function. Without blood vessels, these tissues can’t efficiently obtain nutrients or remove waste, limiting their effectiveness. Therefore, the ability to 3D-bioprint blood vessels is a crucial advancement.
Tissue engineers could already position blood vessels during the bioprinting process, but these vessels often remodel unpredictably when cultured in the lab or implanted in the body, reducing the effectiveness of the engineered tissue. The programmable bioink developed by the University of Twente team addresses this issue by providing dynamic control over vessel growth and remodeling over time. This opens new possibilities for creating engineered tissues with long-term functionality and adaptability.
Mechanical switches and protein meshes – this is a new way of looking at one of our most feared diseases.
