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Stanford researchers have used cryogenic 3D imaging at the National Center for X-ray Tomography (NCXT) to identify a new pathway for clearing misfolded proteins from cells. This work presents a potential therapy target for age-related disorders like Alzheimer, Parkinson, and Huntington Diseases. To deal with these problem proteins, which can disrupt normal functions and can [...]

It was great to see the biological soft X-ray tomography community reunited in Minneapolis during the M&M meeting 2023. We had several insightful talks and we saw the progresses made by X-ray imaging in the past years. Thanks for all who joined the workshop B08.1 and ad majora! You can download and visualize talks and [...]

For the first time, scientists have peered deeply inside a pancreatic cell and observed it packaging insulin and responding to a drug treatment, an intimate look at the mechanisms responsible for preventing diabetes. A team of scientists — led by researchers at the Bridge Institute at the USC Michelson Center for Convergent Bioscience — have developed advanced [...]

SXT data sheds light on diabetes Different imaging approaches provide unique layers of information on cellular structure. Soft X-ray tomography provides a map of organelles within an intact cell, while cryo-electron tomography provides high-resolution windows into specific cellular neighborhoods within a cell. (Illustration/Katya Kadyshevskaya) For the first time, scientists have peered deeply inside a pancreatic [...]

A major challenge in studying infectious diseases is identifying the changes cells undergo following invasion by pathogens. A highly sensitive technique developed in the early 2000s at the National Center for X-ray Tomography (NCXT), a facility based at Berkeley Lab’s Advanced Light Source (ALS), takes cellular imaging to the next level by sculpting three-dimensional scans [...]

When bacteria are put in different environments, such as one that is more acidic or anaerobic, their genes start to adapt remarkably quickly. They’re able to do so because the proteins making up their chromosome can pack and unpack rapidly. Now, a Berkeley Lab-led team of researchers has been able to capture this process at [...]

Typical machine learning methods used to analyze experimental imaging data rely on tens or hundreds of thousands of training images. But Daniël Pelt and James Sethian of Berkeley Lab’s Center for Advanced Mathematics for Energy Research Applications (CAMERA) have developed what they call a “Mixed-Scale Dense Convolution Neural Network” (MS-D) that “learns” much more quickly [...]