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PURPOSE In patients with septic shock, to (1) determine the incidence of adrenal insufficiency (AI), (2) observe the effects of glucocorticoid therapy on outcome in those with impaired adrenal function, and (3) investigate a possible correlation between adrenal function and peripheral cytokine levels. PATIENTS AND METHODS Twenty-one patients admitted to(More)
Uch37 is a de-ubiquitylating enzyme that is functionally linked with the 26S proteasome via Rpn13, and is essential for metazoan development. Here, we report the X-ray crystal structure of full-length human Uch37 at 2.95 Å resolution. Uch37's catalytic domain is similar to those of all UCH enzymes characterized to date. The C-terminal extension is(More)
Supervised machine learning is a branch of artificial intelligence concerned with automatically inducing predictive models from labeled data. Such learning approaches are useful for many interesting real-world applications, but particularly shine for tasks involving the automatic organization, extraction, and retrieval of information from large collections(More)
Future Work As a next step we hope to apply the CRF framework to other MRI analysis problems. We hope to see if our method can perform atlas free anatomical segmentation. Using the results of the image analysis for prediction of events such as onset of Alzheimer's is another future possibility. The real impact of automatic segmentation can be realized by(More)
In line with institutions across the United States, the Computer Science Department at Swarthmore College has faced the challenge of maintaining a demographic composition of students that matches the student body as a whole. To combat this trend, our department has made a concerted effort to revamp our introductory course sequence to both attract and retain(More)
MOTIVATION One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed ACMI (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout.(More)
A major bottleneck in high-throughput protein crystallography is producing protein-structure models from an electron-density map. In previous work, we developed Acmi, a probabilistic framework for sampling all-atom protein-structure models. Acmi uses a fully connected, pairwise Markov random field to model the 3D location of each non-hydrogen atom in a(More)
Several methods for automatically constructing a protein model from an electron-density map require searching for many small protein-fragment templates in the density. We propose to use the spherical-harmonic decomposition of the template and the maps density to speed this matching. Unlike other template-matching approaches, this allows us to eliminate(More)
An important problem in high-throughput protein crystallography is constructing a protein model from an electron-density map. Previous work by some of this paper’s authors [1] describes an automated approach to this otherwise time-consuming process. An important step in the previous method requires searching the density map for many small template(More)