Paper Session I-C - Technology Advances and Developments in Low Power Gallium Arsenide for Space Applications

The evolution of gallium arsenide (GaAs) technology has developed to the point where it is quite suited for low power operation in space. The preliminary requirements for space-based integrated circuit applications are reviewed, and evidence that a GaAs technology known as complementary heterostructure field effect transistors (CHFETs) has proven to meet the demands of the space environment is presented. Further examples of how the complementary GaAs technology has demonstrated the potential for operation in the Gigahertz frequency range using power supply voltages at or below 2.5 Volts are presented. The analog and digital technological needs for space applications are identified and being met by complementary GaAs technologies when compared to commercial-off-the-shelf (COTS) electronics. Emphasis on the manufacturing costs of low power GaAs technologies when compared to those associated with COTS modified for space applications is addressed. Finally, information by both the Air Force and commercial sector concerning the need for low power GaAs technology insertion into future space-based systems is provided

Perinatal Environmental Tobacco Smoke Exposure in Rhesus Monkeys: Critical Periods and Regional Selectivity for Effects on Brain Cell Development and Lipid Peroxidation

Perinatal environmental tobacco smoke (ETS) exposure in humans elicits neurobehavioral deficits. We exposed rhesus monkeys to ETS during gestation and through 13 months postnatally, or postnatally only (6–13 months). At the conclusion of exposure, we examined cerebrocortical regions and the midbrain for cell damage markers and lipid peroxidation. For perinatal ETS, two archetypal patterns were seen in the various regions, one characterized by cell loss (reduced DNA concentration) and corresponding increases in cell size (increased protein/DNA ratio), and a second pattern suggesting replacement of larger neuronal cells with smaller and more numerous glia (increased DNA concentration, decreased protein/DNA ratio). The membrane/total protein ratio, a biomarker of neurite formation, also indicated potential damage to neuronal projections, accompanied by reactive sprouting. When ETS exposure was restricted to the postnatal period, the effects were similar in regional selectivity, direction, and magnitude. These patterns resemble the effects of prenatal nicotine exposure in rodent and primate models. Surprisingly, perinatal ETS exposure reduced the level of lipid peroxidation as assessed by the concentration of thiobarbituric acid reactive species, whereas postnatal ETS did not. The heart, a tissue that, like the brain, has high oxygen demand, displayed a similar but earlier decrease (2–3 months) in lipid peroxidation in the perinatal exposure model, whereas values were reduced at 13 months with the postnatal exposure paradigm. Our results provide a mechanistic connection between perinatal ETS exposure and neurobehavioral anomalies, reinforce the role of nicotine in these effects, and buttress the importance of restricting or eliminating ETS exposure in young children

Two distinct sequences of blue straggler stars in the globular cluster M30

Stars in globular clusters are generally believed to have all formed at the same time, early in the Galaxy's history. 'Blue stragglers' are stars massive enough that they should have evolved into white dwarfs long ago. Two possible mechanisms have been proposed for their formation: mass transfer between binary companions and stellar mergers resulting from direct collisions between two stars. Recently, the binary explanation was claimed to be dominant. Here we report that there are two distinct parallel sequences of blue stragglers in M30. This globular cluster is thought to have undergone 'core collapse', during which both the collision rate and the mass transfer activity in binary systems would have been enhanced. We suggest that the two observed sequences arise from the cluster core collapse, with the bluer population arising from direct stellar collisions and the redder one arising from the evolution of close binaries that are probably still experiencing an active phase of mass transfer.Comment: Published on the 24th December 2009 issue of Natur

CEBS—Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data

CEBS (Chemical Effects in Biological Systems) is an integrated public repository for toxicogenomics data, including the study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. CEBS contains data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. CEBS is designed to permit the user to query the data using the study conditions, the subject responses and then, having identified an appropriate set of subjects, to move to the microarray module of CEBS to carry out gene signature and pathway analysis. Scope of CEBS: CEBS currently holds 22 studies of rats, four studies of mice and one study of Caenorhabditis elegans. CEBS can also accommodate data from studies of human subjects. Toxicogenomics studies currently in CEBS comprise over 4000 microarray hybridizations, and 75 2D gel images annotated with protein identification performed by MALDI and MS/MS. CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Additionally, clinical chemistry and histopathology findings from over 1500 animals are included in CEBS. CEBS/BID: The BID (Biomedical Investigation Database) is another component of the CEBS system. BID is a relational database used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee (in preparation). BID has been shared with Health Canada and the US Environmental Protection Agency. CEBS is available at http://cebs.niehs.nih.gov. BID can be accessed via the user interface from https://dir-apps.niehs.nih.gov/arc/. Requests for a copy of BID and for depositing data into CEBS or BID are available at http://www.niehs.nih.gov/cebs-df/

Adaptive Challenges, Adaptive Work, and Adaptive Leadership Among Women Living With HIV in the Southern United States: Findings From a Qualitative Study

Women living with HIV have a higher burden of non-AIDS comorbidities and prevalence of chronic conditions. The Adaptive Leadership Framework for Chronic Illness clarifies living with complex health challenges by delineating the technical work of health care providers as well as the adaptive work and leadership behaviors of patients and their providers. We conducted a descriptive, qualitative study of women residing in the Southern United States who were participating in the Women's Interagency HIV Study in North Carolina. Twenty-two participants (mean age = 52.2 years; 90.9% self-identifying as Black or African American) completed semi-structured qualitative interviews. We identified adaptive challenges (e.g., affective and disclosure challenges) and adaptive work and leadership behaviors. Women learned skills to care for their health and support their families and to work with their providers to manage their care. Findings support the importance of identifying leadership behaviors for the purpose of developing person-centered interventions

Influence of family and friend smoking on intentions to smoke and smoking-related attitudes and refusal self-efficacy among 9-10 year old children from deprived neighbourhoods: a cross-sectional study.

BACKGROUND: Smoking often starts in early adolescence and addiction can occur rapidly. For effective smoking prevention there is a need to identify at risk groups of preadolescent children and whether gender-specific intervention components are necessary. This study aimed to examine associations between mother, father, sibling and friend smoking and cognitive vulnerability to smoking among preadolescent children living in deprived neighbourhoods. METHODS: Cross-sectional data was collected from 9-10 year old children (n =1143; 50.7% girls; 85.6% White British) from 43 primary schools in Merseyside, England. Children completed a questionnaire that assessed their smoking-related behaviour, intentions, attitudes, and refusal self-efficacy, as well as parent, sibling and friend smoking. Data for boys and girls were analysed separately using multilevel linear and logistic regression models, adjusting for individual cognitions and school and deprivation level. RESULTS: Compared to girls, boys had lower non-smoking intentions (P = 0.02), refusal self-efficacy (P = 0.04) and were less likely to agree that smoking is 'definitely' bad for health (P < 0.01). Friend smoking was negatively associated with non-smoking intentions in girls (P < 0.01) and boys (P < 0.01), and with refusal self-efficacy in girls (P < 0.01). Sibling smoking was negatively associated with non-smoking intentions in girls (P < 0.01) but a positive association was found in boys (P = 0.02). Boys who had a smoking friend were less likely to 'definitely' believe that the smoke from other people's cigarettes is harmful (OR 0.57, 95% CI: 0.35 to 0.91, P = 0.02). Further, boys with a smoking friend (OR 0.38, 95% CI: 0.21 to 0.69, P < 0.01) or a smoking sibling (OR 0.45, 95% CI: 0.21 to 0.98) were less likely to 'definitely' believe that smoking is bad for health. CONCLUSION: This study indicates that sibling and friend smoking may represent important influences on 9-10 year old children's cognitive vulnerability toward smoking. Whilst some differential findings by gender were observed, these may not be sufficient to warrant separate prevention interventions. However, further research is needed

Exploring Resilience among Black Women Living with HIV in the Southern United States: Findings from a Qualitative Study

Black women living with HIV (WLWH) face individual and sociostructural challenges. Despite these challenges, many exemplify remarkable levels of resilience and coping. Yet, research on resilience and coping in this population is limited. Twenty Black WLWH in the Southern United States completed semi-structured interviews that explored challenges facing WLWH. We identified six themes related to resilience and coping: self-acceptance, disclosure, self-compassion, social support, will to live, and service. Of these, social support was a driving protective element and an essential component to building and sustaining resilience and coping. Women who experienced positive support often expressed a will to live as well as a desire to support other WLWH. Resilience and social support were characterized by patterns of reciprocity, in that they were mutually sustaining, stabilizing, and strengthening

The Effect of Pre-Injury Anti-Platelet Therapy on the Development of Complications in Isolated Blunt Chest Wall Trauma: A Retrospective Study

INTRODUCTION: The difficulties in the management of the blunt chest wall trauma patient in the Emergency Department due to the development of late complications are well recognised in the literature. Pre-injury anti-platelet therapy has been previously investigated as a risk factor for poor outcomes following traumatic head injury, but not in the blunt chest wall trauma patient cohort. The aim of this study was to investigate pre-injury anti-platelet therapy as a risk factor for the development of complications in the recovery phase following blunt chest wall trauma. METHODS: A retrospective study was completed in which the medical notes were analysed of all blunt chest wall trauma patients presenting to a large trauma centre in Wales in 2012 and 2013. Using univariate and multivariable logistic regression analysis, pre-injury platelet therapy was investigated as a risk factor for the development of complications following blunt chest wall trauma. Previously identified risk factors were included in the analysis to address the influence of confounding. RESULTS: A total of 1303 isolated blunt chest wall trauma patients presented to the ED in Morriston Hospital in 2012 and 2013 with complications recorded in 144 patients (11%). On multi-variable analysis, pre-injury anti-platelet therapy was found to be a significant risk factor for the development of complications following isolated blunt chest wall trauma (odds ratio: 16.9; 95% confidence intervals: 8.2-35.2). As in previous studies patient age, number of rib fractures, chronic lung disease and pre-injury anti-coagulant use were also found to be significant risk factors. CONCLUSIONS: Pre-injury anti-platelet therapy is being increasingly used as a first line treatment for a number of conditions and there is a concurrent increase in trauma in the elderly population. Pre-injury anti-platelet therapy should be considered as a risk factor for the development of complications by clinicians managing blunt chest wall trauma

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p