Species Interactions Weakly Modify Climate-Induced Tree Co-Occurrence Patterns

Aims: Species distributions are hypothesized to be underlain by a complex association of processes that span multiple spatial scales including biotic interactions, dispersal limitation, fine-scale resource gradients and climate. Species disequilibrium with climate may reflect the effects of non-climatic processes on species distributions, yet distribution models have rarely directly considered non-climatic processes. Here, we use a Joint Species Distribution Model (JSDM) to investigate the influence of non-climatic factors on species co-occurrence patterns and to directly quantify the relative influences of climate and alternative processes that may generate correlated responses in species distributions, such as species interactions, on tree co-occurrence patterns. Location: US Rocky Mountains. Methods: We apply a Bayesian JSDM to simultaneously model the co-occurrence patterns of ten dominant tree species across the Rocky Mountains, and evaluate climatic and residual correlations from the fitted model to determine the relative contribution of each component to observed co-occurrence patterns. We also evaluate predictions generated from the fitted model relative to a single-species modelling approach. Results: For most species, correlation due to climate covariates exceeded residual correlation, indicating an overriding influence of broad-scale climate on co-occurrence patterns. Accounting for covariance among species did not significantly improve predictions relative to a single-species approach, providing limited evidence for a strong independent influence of species interactions on distribution patterns. Conclusions: Overall, our findings indicate that climate is an important driver of regional biodiversity patterns and that interactions between dominant tree species contribute little to explain species co-occurrence patterns among Rocky Mountain trees

Infiltration and short-term movement of nitrogen in a silt-loam soil typical of rice cultivation in Arkansas

Rice production in Arkansas is one of the top three crop commodities in terms of cash receipts. Researchers and farmers report that nitrogen (N) needs to be managed according to a variety of factors with two important ones being soil and fertilizer type. The objectives of this experiment were to determine: 1) the degree to which floodwater-incorporated N applied as urea or as ammonium sulfate infiltrates intact cores (7.2-cm dia., 10-cm depth) containing DeWitt siltloam soil, and 2) the distribution of N during 12 h of ponding. Inorganic-N concentrations were analyzed at 2-cm depth intervals in cores following removal of the flood. Nitrogen from applied fertilizer was recovered as ammonium. Ammonium sulfate-N remained in the top 4 cm of soil with concentrations of 375 µg N g-1 in the surface 2 cm and 300 µg N g-1 at the 2 - 4 cm depth after 12 hr of ponding. At all depth intervals below 4 cm, ammonium sulfate-N remained below 30 µg N g-1. In contrast, after 12 h of ponding, N in soil receiving urea was 105 µg N g-1 in the top 2 cm and 173 µg N g-1 at 2-4 cm. At 4-6, 6-8, and 8-10 cm, N was 109, 108, and 35 µg N g-1, respectively, after 12 h of ponding. These results demonstrate immediate and deeper movement of ammonium into silt loam soil receiving urea as compared to ammonium sulfate, demonstrating how the form of N in fertilizer affects its movement into the soil profile

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage

Radiofrequency Ablation of the Medical Branch Nerve as a Novel Treatment for Posterior Element Pain from Vertebral Compression Fractures: A retrospective Study

Vertebral compression fractures (VCF) from trauma, osteoporosis, or pathologic reasons are a significant cause of severe pain and decreased functionality, both of which pose a considerable functional and financial burden to the patient

Using fMRI to Assess Effectiveness of Olanzapine Treatment for Schizophrenia

Schizophrenia is a complex mental illness with neurobiological underpinnings and misconceptions about violence. Schizophrenia is associated with high levels of creativity and structural traits like fewer D2 receptors. Patients face reduced life expectancy due to cardiovascular diseases and cope through smoking and sedentariness. Treatment involves pharmacological antipsychotics like olanzapine and nonpharmacological approaches. Olanzapine works by antagonizing D2 receptors but has side effects like weight gain and diabetes risk. fMRI is used to study treatment mechanisms and predict response, but research on olanzapine\u27s brain network effects is limited

Combining Google Earth and GIS mapping technologies in a dengue surveillance system for developing countries

<p>Abstract</p> <p>Background</p> <p>Dengue fever is a mosquito-borne illness that places significant burden on tropical developing countries with unplanned urbanization. A surveillance system using Google Earth and GIS mapping technologies was developed in Nicaragua as a management tool.</p> <p>Methods and Results</p> <p>Satellite imagery of the town of Bluefields, Nicaragua captured from Google Earth was used to create a base-map in ArcGIS 9. Indices of larval infestation, locations of tire dumps, cemeteries, large areas of standing water, etc. that may act as larval development sites, and locations of the homes of dengue cases collected during routine epidemiologic surveying were overlaid onto this map. Visual imagery of the location of dengue cases, larval infestation, and locations of potential larval development sites were used by dengue control specialists to prioritize specific neighborhoods for targeted control interventions.</p> <p>Conclusion</p> <p>This dengue surveillance program allows public health workers in resource-limited settings to accurately identify areas with high indices of mosquito infestation and interpret the spatial relationship of these areas with potential larval development sites such as garbage piles and large pools of standing water. As a result, it is possible to prioritize control strategies and to target interventions to highest risk areas in order to eliminate the likely origin of the mosquito vector. This program is well-suited for resource-limited settings since it utilizes readily available technologies that do not rely on Internet access for daily use and can easily be implemented in many developing countries for very little cost.</p

The U.S. Arctic Observing Viewer: A Web-Mapping Application for Enhancing Environmental Observation of the Changing Arctic

Although much progress has been made with various Arctic Observing efforts, assessing that progress can be difficult. What data collection efforts are established or underway? Where? By whom? To help meet the strategic needs of programs such as the U.S. Study of Environmental Arctic Change (SEARCH), the Arctic Observing Network (AON), Sustaining Arctic Observing Networks (SAON) and related initiatives, an update has been released for the Arctic Observing Viewer (AOV; http://ArcticObservingViewer.org). This web mapping application and information system has begun to compile the who, what, where, and when for thousands of data collection sites (such as boreholes, ship tracks, buoys, towers, sampling stations, sensor networks, vegetation sites, stream gauges, and observatories) wherever marine, terrestrial, or atmospheric data are collected. Contributing partners for this collaborative resource include the U.S. NSF, ACADIS, ADIwg, AOOS, a2dc, AON, ARMAP, BAID, CAFF, IASOA, INTERACT, and others. While focusing on U.S. activities, the AOV welcomes information exchange with international groups for mutual benefit. Users can visualize, navigate, select, search, draw, print, and more. AOV is founded on principles of interoperability, with open metadata and web service standards, so that agencies and organizations can use AOV tools and services for their own purposes. In this way, AOV will reinforce and complement other distributed yet interoperable cyber-resources and will help science planners, funding agencies, researchers, data specialists, and others to assess status, identify overlap, fill gaps, optimize sampling design, refine network performance, clarify directions, access data, coordinate logistics, collaborate, and more in order to meet Arctic Observing goals.Malgré les progrès réalisés dans le cadre de nombreux efforts d’observation de l’Arctique, les progrès peuvent être difficiles à évaluer. Quelles initiatives de collecte de données sont en cours ou sont établies? À quel endroit? Et qui gère ces initiatives? Pour aider à répondre aux besoins stratégiques de programmes comme ceux de l’organisme américain Study of Environmental Arctic Change (SEARCH), du réseau Arctic Observing Network (AON), des réseaux Sustaining Arctic Observing Networks (SAON) et d’autres programmes connexes, on a procédé à la mise à jour de l’Arctic Observing Viewer (AOV; http://ArcticObservingViewer.org). Ce système d’information jumelé à une application de mappage sur le Web a amorcé la compilation des coordonnées et des renseignements se rapportant à des milliers de sites de collecte de données (comme les trous de forage, les trajets de navires, les bouées, les tours, les stations d’échantillonnage, les réseaux de capteurs, les sites de végétation, les fluviomètres et les observatoires) où des données marines, terrestres ou atmosphériques sont prélevées. Parmi les partenaires qui collaborent à cette ressource, notons U.S. NSF, ACADIS, ADIwg, AOOS, a2dc, AON, ARMAP, BAID, CAFF, IASOA, INTERACT et d’autres encore. Bien que l’AOV se concentre sur les activités américaines, il accepte l’échange d’information avec des groupes internationaux lorsqu’il existe des avantages mutuels. Les utilisateurs peuvent visualiser les données, naviguer dans le système, faire des sélections et des recherches, dessiner, imprimer et ainsi de suite. L’AOV fonctionne moyennant des principes d’interopérabilité, avec des métadonnées ouvertes et des normes de service sur le Web afin que les organismes et les organisations puissent utiliser les outils et les services de l’AOV pour leurs propres fins. De cette façon, l’AOV sera en mesure de consolider et de compléter d’autres cyberressources à la fois réparties et interopérables, en plus d’aider les planificateurs de la science, les bailleurs de fonds, les chercheurs, les spécialistes des données et d’autres encore à évaluer les statuts, à repérer les dédoublements, à combler les écarts, à optimiser les plans d’échantillonnage, à raffiner le rendement des réseaux, à clarifier les consignes, à accéder aux données, à coordonner la logistique, à collaborer et ainsi de suite afin de répondre aux objectifs d’observation de l’Arctique

2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153772/1/acr24131.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153772/2/acr24131_am.pd

Repetitive Elements May Comprise Over Two-Thirds of the Human Genome

Transposable elements (TEs) are conventionally identified in eukaryotic genomes by alignment to consensus element sequences. Using this approach, about half of the human genome has been previously identified as TEs and low-complexity repeats. We recently developed a highly sensitive alternative de novo strategy, P-clouds, that instead searches for clusters of high-abundance oligonucleotides that are related in sequence space (oligo “clouds”). We show here that P-clouds predicts >840 Mbp of additional repetitive sequences in the human genome, thus suggesting that 66%–69% of the human genome is repetitive or repeat-derived. To investigate this remarkable difference, we conducted detailed analyses of the ability of both P-clouds and a commonly used conventional approach, RepeatMasker (RM), to detect different sized fragments of the highly abundant human Alu and MIR SINEs. RM can have surprisingly low sensitivity for even moderately long fragments, in contrast to P-clouds, which has good sensitivity down to small fragment sizes (∼25 bp). Although short fragments have a high intrinsic probability of being false positives, we performed a probabilistic annotation that reflects this fact. We further developed “element-specific” P-clouds (ESPs) to identify novel Alu and MIR SINE elements, and using it we identified ∼100 Mb of previously unannotated human elements. ESP estimates of new MIR sequences are in good agreement with RM-based predictions of the amount that RM missed. These results highlight the need for combined, probabilistic genome annotation approaches and suggest that the human genome consists of substantially more repetitive sequence than previously believed

Survival and Growth of Yeast without Telomere Capping by Cdc13 in the Absence of Sgs1, Exo1, and Rad9

Maintenance of telomere capping is absolutely essential to the survival of eukaryotic cells. Telomere capping proteins, such as Cdc13 and POT1, are essential for the viability of budding yeast and mammalian cells, respectively. Here we identify, for the first time, three genetic modifications that allow budding yeast cells to survive without telomere capping by Cdc13. We found that simultaneous inactivation of Sgs1, Exo1, and Rad9, three DNA damage response (DDR) proteins, is sufficient to allow cell division in the absence of Cdc13. Quantitative amplification of ssDNA (QAOS) was used to show that the RecQ helicase Sgs1 plays an important role in the resection of uncapped telomeres, especially in the absence of checkpoint protein Rad9. Strikingly, simultaneous deletion of SGS1 and the nuclease EXO1, further reduces resection at uncapped telomeres and together with deletion of RAD9 permits cell survival without CDC13. Pulsed-field gel electrophoresis studies show that cdc13-1 rad9Δ sgs1Δ exo1Δ strains can maintain linear chromosomes despite the absence of telomere capping by Cdc13. However, with continued passage, the telomeres of such strains eventually become short and are maintained by recombination-based mechanisms. Remarkably, cdc13Δ rad9Δ sgs1Δ exo1Δ strains, lacking any Cdc13 gene product, are viable and can grow indefinitely. Our work has uncovered a critical role for RecQ helicases in limiting the division of cells with uncapped telomeres, and this may provide one explanation for increased tumorigenesis in human diseases associated with mutations of RecQ helicases. Our results reveal the plasticity of the telomere cap and indicate that the essential role of telomere capping is to counteract specific aspects of the DDR