Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces

The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated features are lacking. In this paper, we propose a method that fits an ordinal response model to predict an ordinal outcome for high-dimensional covariate spaces. Our method penalizes some covariates (high-throughput genomic features) without penalizing others (such as demographic and/or clinical covariates). We demonstrate the application of our method to predict the stage of breast cancer. In our model, breast cancer subtype is a nonpenalized predictor, and CpG site methylation values from the Illumina Human Methylation 450K assay are penalized predictors. The method has been made available in the ordinalgmifs package in the R programming environment

Extending the Macroeconomic Impacts Forecasting Capabilities of the National Energy Modeling System

To comprehensively model the macroeconomic impacts that result from changes in long-term energy-economy forecasts, the United States Department of Energy’s National Energy Technology Laboratory (NETL) partnered with West Virginia University’s (WVU) Regional Research Institute to develop the NETL/WVU econometric input-output (ECIO) model. The NETL/WVU ECIO model is an impacts forecasting model that functions as an extension of the U.S. energy-economic models available from the United States (U.S.) Energy Information Administration’s National Energy Modeling System (NEMS) and the U.S. Environmental Protection Agency’s Market Allocation (MARKAL) model. The ECIO model integrates a macroeconomic econometric forecasting model and an input-output accounting framework along derived forecast scenarios detailing a baseline of the U.S. energy-economy and an alternative forecast on how power generation resources can meet future levels of energy demand to generate estimates of the impacts to gross domestic product, employment, and labor income. This manuscript provides an overview of the model design, assumptions, and standard outputs

PucC and LhaA direct efficient assembly of the light-harvesting complexes in <i>Rhodobacter sphaeroides</i>

The mature architecture of the photosynthetic membrane of the purple phototroph Rhodobacter sphaeroides has been characterised to a level where an atomic-level membrane model is available, but the roles of the putative assembly proteins LhaA and PucC in establishing this architecture are unknown. Here we investigate the assembly of light-harvesting LH2 and reaction centre-light-harvesting1-PufX (RC-LH1-PufX) photosystem complexes using spectroscopy, pull-downs, native gel electrophoresis, quantitative mass spectrometry and fluorescence lifetime microscopy to characterise a series of lhaA and pucC mutants. LhaA and PucC are important for specific assembly of LH1 or LH2 complexes, respectively, but they are not essential; the few LH1 subunits found in ΔlhaA mutants assemble to form normal RC-LH1-PufX core complexes showing that, once initiated, LH1 assembly round the RC is cooperative and proceeds to completion. LhaA and PucC form oligomers at sites of initiation of membrane invagination; LhaA associates with RCs, bacteriochlorophyll synthase (BchG), the protein translocase subunit YajC and the YidC membrane protein insertase. These associations within membrane nanodomains likely maximise interactions between pigments newly arriving from BchG and nascent proteins within the SecYEG-SecDF-YajC-YidC assembly machinery, thereby co-ordinating pigment delivery, the co-translational insertion of LH polypeptides and their folding and assembly to form photosynthetic complexes. LhaA and PucC form oligomers at the sites where invagination of the cytoplasmic membranes is initiated, and they play important roles in photosystem assembly in the purple phototrophic bacterium Rhodobacter sphaeroides. Establishing the architecture of the photosynthetic membrane involves interplay between LhaA, reaction centre complexes, bacteriochlorophyll synthase, the protein translocase subunit YajC, and the YidC membrane protein insertase. These associations likely coordinate the delivery of pigments and the membrane insertion, folding and assembly of photosystem polypeptides

Case Report: Color as a Therapeutic Intervention

Peer reviewedFinal Accepted Versio

Colour and Odour Drive Fruit Selection and Seed Dispersal by Mouse Lemurs

Animals and fruiting plants are involved in a complex set of interactions, with animals relying on fruiting trees as food resources, and fruiting trees relying on animals for seed dispersal. This interdependence shapes fruit signals such as colour and odour, to increase fruit detectability, and animal sensory systems, such as colour vision and olfaction to facilitate food identification and selection. Despite the ecological and evolutionary importance of plant-animal interactions for shaping animal sensory adaptations and plant characteristics, the details of the relationship are poorly understood. Here we examine the role of fruit chromaticity, luminance and odour on seed dispersal by mouse lemurs. We show that both fruit colour and odour significantly predict fruit consumption and seed dispersal by Microcebus ravelobensis and M. murinus. Our study is the first to quantify and examine the role of bimodal fruit signals on seed dispersal in light of the sensory abilities of the disperser