Palliative Care Providers and Administrators' Perspectives on Integration of Community-Based Palliative Care & Policy Regarding the Social Determinants of Health

The purpose of this qualitative study is to describe the perspectives of palliative care providers and administrators regarding barriers to providing community-based palliative care. Thirteen participants were interviewed using a semi-structured interview guide. The USDHHS social determinants of health framework guided the data analysis. The results yielded policy implications

Baseline aquatic faunal survey of Avon Park Air Force Range, Florida: fishes, mollusks, and crayfishes

This report presents results of the first systematic study of the diversity and distribution of fishes and mussels in Avon Park Air Force Range (APR). We also provide information on crayfishes and aquatic snails taken during our fish and mussel sampling activities. Our surveys documented the presence of 46 species of fishes (43 native and 3 nonindigenous), 9 species of mussels (including 8 native and 1 nonindigenous species), 5 species of aquatic snails, and two crayfish species. (347 page document

Development of a Miniaturized Hollow-Waveguide Gas Correlation Radiometer for Trace Gas Measurements in the Martian Atmosphere

We present preliminary results in the development of a miniaturized gas correlation radiometer (GCR) for column trace gas measurements in the Martian atmosphere. The GCR is designed as an orbiting instrument capable of mapping multiple trace gases and identifying active regions on the Mars surface

Spillovers from Foreign Direct Investment in Central and Eastern Europe. An index for measuring a country’s potential to benefit from technology spillovers

In the paper, we construct a composite indicator to estimate the potential of four Central and Eastern European countries (the Czech Republic, Hungary, Poland and Slovakia) to benefit from productivity spillovers from foreign direct investment (FDI) in the manufacturing sector. Such transfers of technology are one of the main benefits of FDI for the host country, and should also be one of the main determinants of FDI incentives offered to investing multinationals by governments, but they are difficult to assess ex ante. For our composite index, we use six components to proxy the main channels and determinants of these spillovers. We have tried several weighting and aggregation methods, and we consider our results robust. According to the analysis of our results, between 2003 and 2007 all four countries were able to increase their potential to benefit from such spillovers, although there are large differences between them. The Czech Republic clearly has the most potential to benefit from productivity spillovers, while Poland has the least. The relative positions of Hungary and Slovakia depend to some extent on the exact weighting and aggregation method of the individual components of the index, but the differences are not large. These conclusions have important implication both the investment strategies of multinationals and government FDI policies

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets.</p> <p>Methods</p> <p>Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF) are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles.</p> <p>Results</p> <p>In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and the biological analysis of the identified significant genes and their related pathways demonstrated that these genes play a prominent role in AD and relate the activation patterns to AD phenotypes. It is validated that the combination of these two methods is efficient.</p> <p>Conclusions</p> <p>Unsupervised matrix factorization methods provide efficient tools to analyze high-throughput microarray dataset. According to the facts that different unsupervised approaches explore correlations in the high-dimensional data space and identify relevant subspace base on different hypotheses, integrating these methods to explore the underlying biological information from microarray dataset is an efficient approach. By combining the significant genes identified by both ICA and NMF, the biological analysis shows great efficient for elucidating the molecular taxonomy of Alzheimer’s disease and enable better experimental design to further identify potential pathways and therapeutic targets of AD.</p

Managing the Socially Marginalized: Attitudes Towards Welfare, Punishment and Race

Welfare and incarceration policies have converged to form a system of governance over socially marginalized groups, particularly racial minorities. In both of these policy areas, rehabilitative and social support objectives have been replaced with a more punitive and restrictive system. The authors examine the convergence in individual-level attitudes concerning welfare and criminal punishment, using national survey data. The authors\u27 analysis indicates a statistically significant relationship between punitive attitudes toward welfare and punishment. Furthermore, accounting for the respondents\u27 racial attitudes explains the bivariate relationship between welfare and punishment. Thus, racial attitudes seemingly link support for punitive approaches to opposition to welfare expenditures. The authors discuss the implications of this study for welfare and crime control policies by way of the conclusion

(Mis)perceptions of ethnic group size and consequences for community expectations and cooperation with law enforcement

The changing composition of race and ethnic group size has been noted for Western nations over the last 15 years. Analysis of this change has linked fear of crime and attitudes toward immigrants and prejudice. Changes in ethnic composition are associated with movement of White residents out of traditionally White communities, rising ethnic tension as the ethnic mix shifts, and a heightened sense of injustice regarding the justice system. (Mis)perceptions of ethnic groups size shape attitudes toward minority groups, as well as policy, practice, and individual behavior in the context of the community. This study seeks to understand the extent of such misperceptions in the Australian context and whether misperceptions of race and ethnic composition are associated with beliefs and attitudes toward formal and informal social control. Utilizing Blalock’s racial threat hypothesis, this study analyzes whether perceived relative ethnic group size is associated with self-reported willingness to cooperate with police as a way to minimize perceived threat. Findings suggest that respondents overestimate the size of minority populations while underestimating the majority White composition and that these misperceived distortions in ethnic group size have consequences for informal and formal social control

Change in school ethnic diversity and intergroup relations: The transition from segregated elementary to mixed secondary school for majority and minority students

This research examined the impact of a change in school diversity on school children’s intergroup relations. A longitudinal survey tracked 551 White British and Asian British students (Mage = 11.32) transitioning from elementary (time 1) to secondary (time 2) school in an ethnically segregated town in the United Kingdom. We estimated a multivariate, multilevel model. A cross-sectional comparison of segregated schools and a mixed elementary school at time 1 revealed that both Asian and White British in the mixed school reported more positive intergroup relations. A longitudinal analysis found that the transition from segregated elementary to mixed secondary schools was associated with Asian British developing more positive intergroup relations. White British reported overall less positive intergroup relations, although only trust decreased, evidence from other measures remains inconclusive. The findings are important for understanding early stages of diversity exposure, and the impact of changing diversity levels on majority and minority groups

Effects of Long-Term Pioglitazone Treatment on Peripheral and Central Markers of Aging

BACKGROUND: Thiazolidinediones (TZDs) activate peroxisome proliferator-activated receptor gamma (PPARgamma) and are used clinically to help restore peripheral insulin sensitivity in Type 2 diabetes (T2DM). Interestingly, long-term treatment of mouse models of Alzheimer\u27s disease (AD) with TZDs also has been shown to reduce several well-established brain biomarkers of AD including inflammation, oxidative stress and Abeta accumulation. While TZD\u27s actions in AD models help to elucidate the mechanisms underlying their potentially beneficial effects in AD patients, little is known about the functional consequences of TZDs in animal models of normal aging. Because aging is a common risk factor for both AD and T2DM, we investigated whether the TZD, pioglitazone could alter brain aging under non-pathological conditions. METHODS AND FINDINGS: We used the F344 rat model of aging, and monitored behavioral, electrophysiological, and molecular variables to assess the effects of pioglitazone (PIO-Actos® a TZD) on several peripheral (blood and liver) and central (hippocampal) biomarkers of aging. Starting at 3 months or 17 months of age, male rats were treated for 4-5 months with either a control or a PIO-containing diet (final dose approximately 2.3 mg/kg body weight/day). A significant reduction in the Ca2+-dependent afterhyperpolarization was seen in the aged animals, with no significant change in long-term potentiation maintenance or learning and memory performance. Blood insulin levels were unchanged with age, but significantly reduced by PIO. Finally, a combination of microarray analyses on hippocampal tissue and serum-based multiplex cytokine assays revealed that age-dependent inflammatory increases were not reversed by PIO. CONCLUSIONS: While current research efforts continue to identify the underlying processes responsible for the progressive decline in cognitive function seen during normal aging, available medical treatments are still very limited. Because TZDs have been shown to have benefits in age-related conditions such as T2DM and AD, our study was aimed at elucidating PIO\u27s potentially beneficial actions in normal aging. Using a clinically-relevant dose and delivery method, long-term PIO treatment was able to blunt several indices of aging but apparently affected neither age-related cognitive decline nor peripheral/central age-related increases in inflammatory signaling

The Proteomic Code: a molecular recognition code for proteins

<p>Abstract</p> <p>Background</p> <p>The Proteomic Code is a set of rules by which information in genetic material is transferred into the physico-chemical properties of amino acids. It determines how individual amino acids interact with each other during folding and in specific protein-protein interactions. The Proteomic Code is part of the redundant Genetic Code.</p> <p>Review</p> <p>The 25-year-old history of this concept is reviewed from the first independent suggestions by Biro and Mekler, through the works of Blalock, Root-Bernstein, Siemion, Miller and others, followed by the discovery of a Common Periodic Table of Codons and Nucleic Acids in 2003 and culminating in the recent conceptualization of partial complementary coding of interacting amino acids as well as the theory of the nucleic acid-assisted protein folding.</p> <p>Methods and conclusions</p> <p>A novel cloning method for the design and production of specific, high-affinity-reacting proteins (SHARP) is presented. This method is based on the concept of proteomic codes and is suitable for large-scale, industrial production of specifically interacting peptides.</p