Location, location, location: the evolutionary history of CD1 genes and the NKR-P1/ligand systems

CD1 genes encode cell surface molecules that present lipid antigens to various kinds of T lymphocytes of the immune system. The structures of CD1 genes and molecules are like the major histocompatibility complex (MHC) class I system, the loading of antigen and the tissue distribution for CD1 molecules are like those in the class II system, and phylogenetic analyses place CD1 between class I and class II sequences, altogether leading to the notion that CD1 is a third ancient system of antigen presentation molecules. However, thus far, CD1 genes have only been described in mammals, birds and reptiles, leaving major questions as to their origin and evolution. In this review, we recount a little history of the field so far and then consider what has been learned about the structure and functional attributes of CD1 genes and molecules in marsupials, birds and reptiles. We describe the central conundrum of CD1 evolution, the genomic location of CD1 genes in the MHC and/or MHC paralogous regions in different animals, considering the three models of evolutionary history that have been proposed. We describe the natural killer (NK) receptors NKR-P1 and ligands, also found in different genomic locations for different animals. We discuss the consequence of these three models, one of which includes the repudiation of a guiding principle for the last 20 years, that two rounds of genome-wide duplication at the base of the vertebrates provided the extra MHC genes necessary for the emergence of adaptive immune system of jawed vertebrates

On-Farm Corn Row Spacing Trials

Over the past several decades there has been a shift in corn row spacing from the traditional 40-in. rows that were needed so horses could fit between the rows, to 38-in., 36-in., and the most popular 30-in. rows. The narrow row spacing usually has resulted in increased yields due to it allowing more space between the plants within the row. More recently there has been interest in seeing if a narrower row spacing (15-in. or 20-in.) will further increase corn yield

Rural men getting through adversity: stories of resilience

The aim of this study was to identiy the factors that have helped rural men to move through adversity. A total of ten men from Queensland took part in the study. Participants shared their experiences through in-depth, unstructured interviews. The participants shared a diverse range of difficulties in their lives, but on analysis it become apparent that there were similarities in how the participants overcame those difficult times. Two major themes identified in the study were: the individual and inner strength and support and strategies

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Wave-Breaking Turbulence in the Ocean Surface Layer

AbstractObservations of winds, waves, and turbulence at the ocean surface are compared with several analytic formulations and a numerical model for the input of turbulent kinetic energy by wave breaking and the subsequent dissipation. The observations are generally consistent with all of the formulations, although some differences are notable at winds greater than 15 m s−1. The depth dependence of the turbulent dissipation rate beneath the waves is fit to a decay scale, which is sensitive to the choice of vertical reference frame. In the surface-following reference frame, the strongest turbulence is isolated within a shallow region of depths much less than one significant wave height. In a fixed reference frame, the strong turbulence penetrates to depths that are at least half of the significant wave height. This occurs because the turbulence of individual breakers persists longer than the dominant period of the waves and thus the strong surface turbulence is carried from crest to trough with the wave orbital motion.</jats:p

Rural men and mental health: their experiences and how they managed

There is a growing awareness that a primary source of information about mental health lies with the consumers. This article reports on a study that interviewed rural men with the aim of exploring their mental health experiences within a rural environment. The results of the interviews are a number of stories of resilience and survival that highlight not only the importance of exploring the individuals' perspective of their issues, but also of acknowledging and drawing on their inner strengths. Rural men face a number of challenges that not only increase the risk of mental illness but also decrease the likelihood of them seeking and/or finding professional support. These men's stories, while different from each other, have a common thread of coping. Despite some support from family and friends participants also acknowledged that seeking out professional support could have made the recovery phase easier. Mental health nurses need to be aware, not only of the barrier to professional support but also of the significant resilience that individuals have and how it can be utilised

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Bayesian correlated clustering to integrate multiple datasets

Motivation: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct – but often complementary – information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured via parameters that describe the agreement among the datasets. Results: Using a set of 6 artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real S. cerevisiae datasets. In the 2-dataset case, we show that MDI’s performance is comparable to the present state of the art. We then move beyond the capabilities of current approaches and integrate gene expression, ChIP-chip and protein-protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques – as well as to non-integrative approaches – demonstrate that MDI is very competitive, while also providing information that would be difficult or impossible to extract using other methods