Landry was recognized for her work on engineering nanosensors to image molecules in the body, focusing on neuromodulators such as dopamine in the brain. The fellowship, established in 1934, honors “early-career scholars whose achievements mark them as among the very best scientific minds working today.” Read more in Berkeley News.
New Insight about Antidepressants
Researchers at the Oregon Health & Science University (OHSU) Vollum Institute have discovered how chemically diverse drugs used to treat depression and anxiety disorders interact with the protein that transports serotonin in the brain. Jonathan Coleman and Eric Gouaux used X-ray crystallography techniques at two U.S. Department of Energy national user facilities to collect data: Molecular research was carried out at the Biosciences’ Berkeley Center for Structural Biology, beamline 5.0.2, located at the Advanced Light Source; and at the Advanced Photon Source (APS), at Argonne National Laboratory. Their findings, published in the January 29 issue of the journal Nature Structural & Molecular Biology, could open the way for the development of additional forms of antidepressants collectively known as selective serotonin reuptake inhibitors, or SSRIs.
‘Minimalist’ Machine Learning Algorithms Analyze Images from Sparse Data
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 from a remarkably small training set. One promising application of MS-D is in understanding the internal structure and morphology of biological cells to identify, for example, differences between healthy and diseased cells. In one such project in Carolyn Larabell’s lab, the method needed data from just seven cells to determine the cell structure.
Using Nature’s Blueprint for Sustainable Indigo Dyeing Process
Indigo has been prized since antiquity for its vibrancy and deep blue hue and, for more than a century, its unique properties have been leveraged to produce the popular textile blue denim. However, the dyeing process requires chemical steps that are environmentally damaging. A team of researchers in the Molecular Biophysics and Integrated Bioimaging (MBIB) and Biological Systems and Engineering (BSE) Divisions, at JBEI, and UC Berkeley have developed a promising sustainable indigo dyeing process that relies on genetically engineered bacteria, mimicking the natural biochemical protecting group strategy employed by the Japanese indigo plant Polygonum tinctorium.
Crystallization Screen Created by Berkeley Lab Biosciences Scientists Reaches the Market
X-ray crystallography has been the most successful technique used to solve macromolecular structures, contributing several thousand new entries to the Protein Data Bank (PDB) every year. The protein crystal is the critical starting point for X-ray data collection, and consequently, its properties are correlated with the quality of the data and the level of detail that can be extracted for a macromolecular structure. However, proteins require solutions of specific composition to form crystals for structure determination studies. These specifications are usually determined from exposing the protein to several different solutions in a crystallization screen.
A team of researchers in the Molecular Biophysics and Integrated Bioimaging (MBIB) Division led by Paul Adams and Jose Henrique Pereira have developed a new crystal screen, the Berkeley Screen, with 96 conditions proven to be highly effective at producing crystals for structural determination. The Berkeley Screen is now available to the wider crystallography community commercially.
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