Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT.

Objective: To evaluate whether an imaging classifier for radiology practice can improve lung nodule classification and follow-up.

Methods: A machine learning classifier was developed and trained using imaging data from the National Lung Screening Trial (NSLT) to produce a malignancy risk score (malignancy Similarity Index [mSI]) for individual lung nodules. In addition to NLST cohorts, external cohorts were developed from a tertiary referral lung cancer screening program data set and an external nonscreening data set of all nodules detected on CT.

SWITCH-China: A Systems Approach to Decarbonizing China's Power System.

We present an integrated model, SWITCH-China, of the Chinese power sector with which to analyze the economic and technological implications of a medium to long-term decarbonization scenario while accounting for very-short-term renewable variability. On the basis of the model and assumptions used, we find that the announced 2030 carbon peak can be achieved with a carbon price of ∼$40/tCO2. Current trends in renewable energy price reductions alone are insufficient to replace coal; however, an 80% carbon emission reduction by 2050 is achievable in the Intergovernmental Panel on Climate Change Target Scenario with an optimal electricity mix in 2050 including nuclear (14%), wind (23%), solar (27%), hydro (6%), gas (1%), coal (3%), and carbon capture and sequestration coal energy (26%).

SunShot solar power reduces costs and uncertainty in future low-carbon electricity systems.

The United States Department of Energy's SunShot Initiative has set cost-reduction targets of $1/watt for central-station solar technologies. We use SWITCH, a high-resolution electricity system planning model, to study the implications of achieving these targets for technology deployment and electricity costs in western North America, focusing on scenarios limiting carbon emissions to 80% below 1990 levels by 2050. We find that achieving the SunShot target for solar photovoltaics would allow this technology to provide more than a third of electric power in the region, displacing natural gas in the medium term and reducing the need for nuclear and carbon capture and sequestration (CCS) technologies, which face technological and cost uncertainties, by 2050.

WND-CHARM: Multi-purpose image classification using compound image transforms.

We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image.

CENP-V is required for centromere organization, chromosome alignment and cytokinesis.

The mechanism of mitotic chromosome condensation is poorly understood, but even less is known about the mechanism of formation of the primary constriction, or centromere. A proteomic analysis of mitotic chromosome scaffolds led to the identification of CENP-V, a novel kinetochore protein related to a bacterial enzyme that detoxifies formaldehyde, a by-product of histone demethylation in eukaryotic cells. Overexpression of CENP-V leads to hypercondensation of pericentromeric heterochromatin, a phenotype that is abolished by mutations in the putative catalytic site.

Quantitative image analysis reveals distinct structural transitions during aging in Caenorhabditis elegans tissues.

Aging is associated with functional and structural declines in many body systems, even in the absence of underlying disease. In particular, skeletal muscles experience severe declines during aging, a phenomenon termed sarcopenia. Despite the high incidence and severity of sarcopenia, little is known about contributing factors and development.

Wndchrm - an open source utility for biological image analysis.

Background: Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening.

Methods: Wndchrm is an open source utility for biological image analysis.

Sarcopenia in the Caenorhabditis elegans pharynx correlates with muscle contraction rate over lifespan.

In muscles, sarcopenia, the loss of muscle mass, is the major cause of aging-related functional decline and frailty. Several factors are correlated with sarcopenia during aging, including contraction-related cellular injury, oxidative stress, endocrine changes and reduced regenerative potential. However the involvement of these factors has not been experimentally investigated.

The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging.

The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.