Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded

Iterative Evolution of Sympatric Seacow (Dugongidae, Sirenia) Assemblages during the Past ∼26 Million Years

Extant sirenians show allopatric distributions throughout most of their range. However, their fossil record shows evidence of multispecies communities throughout most of the past ∼26 million years, in different oceanic basins. Morphological differences among co-occurring sirenian taxa suggest that resource partitioning played a role in structuring these communities. We examined body size and ecomorphological differences (e.g., rostral deflection and tusk morphology) among sirenian assemblages from the late Oligocene of Florida, early Miocene of India and early Pliocene of Mexico; each with three species of the family Dugongidae. Although overlapping in several ecomorphological traits, each assemblage showed at least one dominant trait in which coexisting species differed. Fossil sirenian occurrences occasionally are monotypic, but the assemblages analyzed herein show iterative evolution of multispecies communities, a phenomenon unparalleled in extant sirenian ecology. As primary consumers of seagrasses, these communities likely had a strong impact on past seagrass ecology and diversity, although the sparse fossil record of seagrasses limits direct comparisons. Nonetheless, our results provide robust support for previous suggestions that some sirenians in these extinct assemblages served as keystone species, controlling the dominance of climax seagrass species, permitting more taxonomically diverse seagrass beds (and sirenian communities) than many of those observed today

A supermatrix analysis of genomic, morphological, and paleontological data from crown Cetacea

<p>Abstract</p> <p>Background</p> <p>Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters.</p> <p>Results</p> <p>We combined new nuclear DNA sequences, including segments of six genes (~2800 basepairs) from the functionally extinct Yangtze River dolphin, with an expanded morphological matrix and published genomic data. Diverse analyses of these data resolved the relationships of 74 taxa that represent all extant families and 11 extinct families of Cetacea. The resulting supermatrix (61,155 characters) and its sub-partitions were analyzed using parsimony methods. Bayesian and maximum likelihood (ML) searches were conducted on the molecular partition, and a molecular scaffold obtained from these searches was used to constrain a parsimony search of the morphological partition. Based on analysis of the supermatrix and model-based analyses of the molecular partition, we found overwhelming support for 15 extant clades. When extinct taxa are included, we recovered trees that are significantly correlated with the fossil record. These trees were used to reconstruct the timing of cetacean diversification and the evolution of characters shared by "river dolphins," a non-monophyletic set of species according to all of our phylogenetic analyses.</p> <p>Conclusions</p> <p>The parsimony analysis of the supermatrix and the analysis of morphology constrained to fit the ML/Bayesian molecular tree yielded broadly congruent phylogenetic hypotheses. In trees from both analyses, all Oligocene taxa included in our study fell outside crown Mysticeti and crown Odontoceti, suggesting that these two clades radiated in the late Oligocene or later, contra some recent molecular clock studies. Our trees also imply that many character states shared by river dolphins evolved in their oceanic ancestors, contradicting the hypothesis that these characters are convergent adaptations to fluvial habitats.</p

Reduction in field emergence and seedbank density of Galinsoga quadriradiata and other weeds after contrasting false seedbed strategies in organic vegetable fields

Mechanical weed control in low competitive, organic vegetable production systems is challenging, particularly in fields with large populations of Galinsoga spp. (Asteraceae). Various false seedbed techniques are used prior to crop planting or sowing to prevent weed emergence, albeit with variable success. This study investigated the impact of machinery type (flamer, hoe and harrow), number of passes (2 and 4), tillage depth (1-4 cm) and intensity (double and single hoeing, and hoeing with or without additional harrowing) on weed emergence and seedbank density in 0-5 cm topsoil of organic vegetable fields. False seedbed machinery that did not or minimally disturb the soil was most appropriate for preventive control of Galinsoga quadriradiata (Hairy galinsoga) and total weed seeds, with reductions in seedling emergence up to 99% and 73%, respectively, for flaming, and 74% and 67%, respectively, for 1 cm deep hoeing, 1 month after false seedbed creation. Compared with 1 cm deep hoeing, 1 cm deep harrowing was 16% less effective in the control of emerged seedlings, while flaming was highly effective in preventing weed seedling emergence, even after a low number of passes. Tillage intensity was less important than tillage depth for the reduction in weed emergence and seedbank density. Overall, tillage was more effective for seedbank reduction than flaming