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Category: biotech/medical – Page 243

A research team at the University of Virginia School of Engineering and Applied Science has developed what it believes could be the template for the first building blocks for human-compatible organs printed on demand.

Liheng Cai, an assistant professor of materials science and engineering and chemical engineering, and his Ph.D. student, Jinchang Zhu, have made biomaterials with controlled mechanical properties matching those of various human tissues.

“That’s a big leap compared to existing bioprinting technologies,” Zhu said.

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Researchers from North Carolina State University and Johns Hopkins University have demonstrated a technology capable of a suite of data storage and computing functions – repeatedly storing, retrieving, computing, erasing or rewriting data – that uses DNA rather than conventional electronics. Previous DNA data storage and computing technologies could complete some but not all of these tasks.

“In conventional computing technologies, we take for granted that the ways data are stored and the way data are processed are compatible with each other,” says project leader Albert Keung, co-corresponding author of a paper on the work (Nature Nanotechnology, “A Primordial DNA Store and Compute Engine”). “But in reality, data storage and data processing are done in separate parts of the computer, and modern computers are a network of complex technologies,” Keung is an associate professor of chemical and biomolecular engineering and a Goodnight Distinguished Scholar at NC State.

“DNA computing has been grappling with the challenge of how to store, retrieve and compute when the data is being stored in the form of nucleic acids,” Keung says. “For electronic computing, the fact that all of a device’s components are compatible is one reason those technologies are attractive. But, to date, it’s been thought that while DNA data storage may be useful for long-term data storage, it would be difficult or impossible to develop a DNA technology that encompassed the full range of operations found in traditional electronic devices: storing and moving data; the ability to read, erase, rewrite, reload or compute specific data files; and doing all of these things in programmable and repeatable ways.

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In the past decade, lab-grown blobs of human brain tissue began making news headlines, as they ushered in a new era of scientific discovery and raised a slew of ethical questions.

These blobs — scientifically known as brain organoids, but often called “minibrains” in the news — serve as miniature, simplified models of full-size human brains. These organoids can potentially be useful in basic research, drug development and even computer science.

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Mitochondria in brain cells frequently insert their DNA into the nucleus, potentially impacting lifespan, as those with more insertions were found to die earlier. Stress appears to accelerate this process, suggesting a new way mitochondria influence health beyond energy production.

As direct descendants of ancient bacteria, mitochondria have always been a little alien. Now a study shows that mitochondria are possibly even stranger than we thought.

Mitochondria in our brain cells frequently fling their DNA into the nucleus, the study found, where the DNA becomes integrated into the cells’ chromosomes. And these insertions may be causing harm: Among the study’s nearly 1,200 participants, those with more mitochondrial DNA insertions in their brain cells were more likely to die earlier than those with fewer insertions.

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We’ve all heard about the potential of artificial intelligence in the life sciences field. In 2020, the launch of AlphaFold 2, pioneered by Google DeepMind, took the world by storm and marked a new age in protein structure prediction. But now, AlphaFold 3 is transforming the landscape again. In this news highlight, we explore the new tech, compare it to its predecessor and take a look to the future.

Before the AI revolution, protein structure prediction heavily relied on experimental methods, such as X-ray crystallography, NMR spectroscopy and, later, some complex computational methods like homology modelling. These methods were time consuming and costly, and were a major limiting step in drug discovery and development processes in particular. For years, scientists have been attempting to integrate the latest and greatest AI models into the field, in order to speed up the process and improve accuracy.

Enter AlphaFold, an artificial intelligence tool developed by Google’s DeepMind. The first version of the technology was released in 2018, but it was 2020’s AlphaFold 2 that made headlines – winning the prestigious Critical Assessment of Structure Prediction (CASP) 14 competition. Having gone through multiple major iterations, the most recent release, AlphaFold 3, is set to further transform the protein space. But what does it do, and how may it outperform its predecessor?

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Researchers from the University of California, Irvine have discovered the neurons responsible for “item memory,” deepening our understanding of how the brain stores and retrieves the details of “what” happened and offering a new target for treating Alzheimer’s disease.

Memories include three types…

Finding significantly deepens understanding of crucial component of cognitive function.

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In the quest to develop life-like materials to replace and repair human body parts, scientists face a formidable challenge: Real tissues are often both strong and stretchable and vary in shape and size.

A CU Boulder-led team, in collaboration with researchers at the University of Pennsylvania, has taken a critical step toward cracking that code. They’ve developed a new way to 3D print material that is at once elastic enough to withstand a heart’s persistent beating, tough enough to endure the crushing load placed on joints, and easily shapable to fit a patient’s unique defects.

Better yet, it sticks easily to wet tissue.

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