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University of Arizona researchers have developed an ‘attomicroscopy’ technique using a novel ultrafast electron microscope that captures moving electrons in unprecedented detail, paving the way for significant scientific breakthroughs in physics and other fields.

Imagine having a camera so advanced that it can capture freeze-frame images of a moving electron—an object so fast it could orbit the Earth multiple times in just a second. Researchers at the University of Arizona have developed the world’s fastest electron microscope capable of this remarkable feat.

They believe their work will lead to groundbreaking advancements in physics, chemistry, bioengineering, materials sciences, and more.

The future of medicine lies in synthetic biology! In this video, you’ll learn how synthetic biology is used in healthcare and why it can help develop cancer treatments and much more.

Are you interested in furthering the field of biology or medicine? Visit uvu.edu to carve your path.

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#bioink could be used to #Print and #Grow #Lung #Tissue.

Researchers describe their success in creating a mucus-based bioink for 3D printing lung tissue. This advancement could one day help study and treat chronic lung conditions. scitechupdates.com/mucus-based-bi


Lung diseases kill millions of people around the world each year. Treatment options are limited, and animal models for studying these illnesses and experimental medications are inadequate. Now, writing in ACS Applied Bio Materials, researchers describe their success in creating a mucus-based bioink for 3D printing lung tissue. This advancement could one day help study and treat chronic lung conditions.

While some people with lung diseases receive transplants, donor organs remain in short supply. As an alternative, medications and other treatments can be used to manage symptoms, but no cure is available for disorders such as chronic obstructive pulmonary disease and cystic fibrosis. Researchers continue to seek better medications, often relying on testing in rodents. But these animal models may only partially capture the complexities of pulmonary diseases in humans, and they might not accurately predict the safety and efficacy of new drugs.