Do primary care medical homes facilitate care transitions after psychiatric discharge for patients with multiple chronic conditions?

Primary-care-based medical homes may facilitate care transitions for persons with multiple chronic conditions (MCC) including serious mental illness. The purpose of this manuscript is to assess outpatient follow-up rates with primary care and mental health providers following psychiatric discharge by medical home enrollment and medical complexity

Demographic trade-offs predict tropical forest dynamics

Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs—the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests

Do Medical Homes Offer Improved Diabetes Care for Medicaid Enrollees with Co-occurring Schizophrenia?

To determine whether Medicaid recipients with co-occurring diabetes and schizophrenia that are medical-home-enrolled are more likely to receive guideline-concordant diabetes care than those who are not medical-home-enrolled, controlling for confounders

Testing for Network and Spatial Autocorrelation

Testing for dependence has been a well-established component of spatial statistical analyses for decades. In particular, several popular test statistics have desirable properties for testing for the presence of spatial autocorrelation in continuous variables. In this paper we propose two contributions to the literature on tests for autocorrelation. First, we propose a new test for autocorrelation in categorical variables. While some methods currently exist for assessing spatial autocorrelation in categorical variables, the most popular method is unwieldy, somewhat ad hoc, and fails to provide grounds for a single omnibus test. Second, we discuss the importance of testing for autocorrelation in data sampled from the nodes of a network, motivated by social network applications. We demonstrate that our proposed statistic for categorical variables can both be used in the spatial and network setting

Modeling species' distributions to improve conservation in semiurban landscapes: Koala case study

Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (Phascolarctos cinereus) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however, anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity

Links between plant and fungal communities across a deforestation chronosequence in the Amazon rainforest

Understanding the interactions among microbial communities, plant communities and soil properties following deforestation could provide insights into the long-term effects of land-use change on ecosystem functions, and may help identify approaches that promote the recovery of degraded sites. We combined high-throughput sequencing of fungal rDNA and molecular barcoding of plant roots to estimate fungal and plant community composition in soil sampled across a chronosequence of deforestation. We found significant effects of land-use change on fungal community composition, which was more closely correlated to plant community composition than to changes in soil properties or geographic distance, providing evidence for strong links between above- and below-ground communities in tropical forests. © 2014 International Society for Microbial Ecology All rights reserved

Teaching appropriate interactions with pharmaceutical company representatives: The impact of an innovative workshop on student attitudes

BACKGROUND: Pharmaceutical company representatives (PCRs) influence the prescribing habits and professional behaviour of physicians. However, the skills for interacting with PCRs are not taught in the traditional medical school curriculum. We examined whether an innovative, mandatory workshop for third year medical students had immediate effects on knowledge and attitudes regarding interactions with PCRs. METHODS: Surveys issued before and after the workshop intervention solicited opinions (five point Likert scales) from third year students (n = 75) about the degree of bias in PCR information, the influence of PCRs on prescribing habits, the acceptability of specific gifts, and the educational value of PCR information for both practicing physicians and students. Two faculty members and one PCR led the workshop, which highlighted typical physician-PCR interactions, the use of samples and gifts, the validity and legal boundaries of PCR information, and associated ethical issues. Role plays with the PCR demonstrated appropriate and inappropriate strategies for interacting with PCRs. RESULTS: The majority of third year students (56%, 42/75) had experienced more than three personal conversations with a PCR about a drug product since starting medical school. Five percent (4/75) claimed no previous personal experience with PCRs. Most students (57.3%, 43/75) were not aware of available guidelines regarding PCR interactions. Twenty-eight percent of students (21/75) thought that none of the named activities/gifts (lunch access, free stethoscope, textbooks, educational CD-ROMS, sporting events) should be restricted, while 24.0% (8/75) thought that students should be restricted only from sporting events. The perceived educational value of PCR information to both practicing physicians and students increased after the workshop intervention from 17.7% to 43.2% (chi square, p = .0001), and 22.1% to 40.5% (p = .0007), respectively. Student perceptions of the degree of bias of PCR information decreased from 84.1% to 72.9% (p = .065), but the perceived degree of influence on prescribing increased (44.2% to 62.1% (p = .02)). CONCLUSIONS: Students have exposure to PCRs early in their medical training. A single workshop intervention may influence student attitudes toward interactions with PCRs. Students were more likely to acknowledge the educational value of PCR interactions and their impact on prescribing after the workshop intervention

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Distribution and Molecular Evolution of Bacillus anthracis Genotypes in Namibia

The recent development of genetic markers for Bacillus anthracis has made it possible to monitor the spread and distribution of this pathogen during and between anthrax outbreaks. In Namibia, anthrax outbreaks occur annually in the Etosha National Park (ENP) and on private game and livestock farms. We genotyped 384 B. anthracis isolates collected between 1983–2010 to identify the possible epidemiological correlations of anthrax outbreaks within and outside the ENP and to analyze genetic relationships between isolates from domestic and wild animals. The isolates came from 20 animal species and from the environment and were genotyped using a 31-marker multi-locus-VNTR-analysis (MLVA) and, in part, by twelve single nucleotide polymorphism (SNP) markers and four single nucleotide repeat (SNR) markers. A total of 37 genotypes (GT) were identified by MLVA, belonging to four SNP-groups. All GTs belonged to the A-branch in the cluster- and SNP-analyses. Thirteen GTs were found only outside the ENP, 18 only within the ENP and 6 both inside and outside. Genetic distances between isolates increased with increasing time between isolations. However, genetic distance between isolates at the beginning and end of the study period was relatively small, indicating that while the majority of GTs were only found sporadically, three genetically close GTs, accounting for more than four fifths of all the ENP isolates, appeared dominant throughout the study period. Genetic distances among isolates were significantly greater for isolates from different host species, but this effect was small, suggesting that while species-specific ecological factors may affect exposure processes, transmission cycles in different host species are still highly interrelated. The MLVA data were further used to establish a model of the probable evolution of GTs within the endemic region of the ENP. SNR-analysis was helpful in correlating an isolate with its source but did not elucidate epidemiological relationships

Phylogenetic Constraints Do Not Explain the Rarity of Nitrogen-Fixing Trees in Late-Successional Temperate Forests

Symbiotic nitrogen (N)-fixing trees are rare in late-successional temperate forests, even though these forests are often N limited. Two hypotheses could explain this paradox. The 'phylogenetic constraints hypothesis' states that no late-successional tree taxa in temperate forests belong to clades that are predisposed to N fixation. Conversely, the 'selective constraints hypothesis' states that such taxa are present, but N-fixing symbioses would lower their fitness. Here we test the phylogenetic constraints hypothesis.Using U.S. forest inventory data, we derived successional indices related to shade tolerance and stand age for N-fixing trees, non-fixing trees in the 'potentially N-fixing clade' (smallest angiosperm clade that includes all N fixers), and non-fixing trees outside this clade. We then used phylogenetically independent contrasts (PICs) to test for associations between these successional indices and N fixation. Four results stand out from our analysis of U.S. trees. First, N fixers are less shade-tolerant than non-fixers both inside and outside of the potentially N-fixing clade. Second, N fixers tend to occur in younger stands in a given geographical region than non-fixers both inside and outside of the potentially N-fixing clade. Third, the potentially N-fixing clade contains numerous late-successional non-fixers. Fourth, although the N fixation trait is evolutionarily conserved, the successional traits are relatively labile.These results suggest that selective constraints, not phylogenetic constraints, explain the rarity of late-successional N-fixing trees in temperate forests. Because N-fixing trees could overcome N limitation to net primary production if they were abundant, this study helps to understand the maintenance of N limitation in temperate forests, and therefore the capacity of this biome to sequester carbon