58 research outputs found
Modelling the Dynamics of Feral Alfalfa Populations and Its Management Implications
BACKGROUND: Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. METHODOLOGY/PRINCIPAL FINDINGS: We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. CONCLUSIONS/SIGNIFICANCE: Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be applied to other perennial herbaceous plants with similar life-history characteristics
Conditional meta-analysis stratifying on detailed HLA genotypes identifies a novel type 1 diabetes locus around TCF19 in the MHC
The human leukocyte antigen (HLA) class II genes HLA-DRB1, -DQA1 and -DQB1 are the strongest genetic factors for type 1 diabetes (T1D). Additional loci in the major histocompatibility complex (MHC) are difficult to identify due to the region’s high gene density and complex linkage disequilibrium (LD). To facilitate the association analysis, two novel algorithms were implemented in this study: one for phasing the multi-allelic HLA genotypes in trio families, and one for partitioning the HLA strata in conditional testing. Screening and replication were performed on two large and independent datasets: the Wellcome Trust Case–Control Consortium (WTCCC) dataset of 2,000 cases and 1,504 controls, and the T1D Genetics Consortium (T1DGC) dataset of 2,300 nuclear families. After imputation, the two datasets have 1,941 common SNPs in the MHC, of which 22 were successfully tested and replicated based on the statistical testing stratifying on the detailed DRB1 and DQB1 genotypes. Further conditional tests using the combined dataset confirmed eight novel SNP associations around 31.3 Mb on chromosome 6 (rs3094663, p = 1.66 × 10−11 and rs2523619, p = 2.77 × 10−10 conditional on the DR/DQ genotypes). A subsequent LD analysis established TCF19, POU5F1, CCHCR1 and PSORS1C1 as potential causal genes for the observed association
Changes in grassland management and linear infrastructures associated to the decline of an endangered bird population
European grassland birds are experiencing major population declines, mainly due to changes in
farmland management. We analyzed the role of habitat availability, grazing management and
linear infrastructures (roads and power lines) in explaining spatial and temporal variation in the
population density of little bustards (Tetrax tetrax) in Portugal, during a decade in which the species
population size halved. We used data from 51 areas (totaling ca. 1,50,000 ha) that were sampled
in two different periods (2003–2006 and 2016). In 2003–2006, when the species occurred at high
densities, habitat availability was the only factor affecting spatial variation in bustard density. In the
2016 survey, variation in density was explained by habitat availability and livestock management,
with reduced bird numbers in areas with higher proportions of cattle. Population declines across the
study period were steeper in areas that initially held higher densities of bustards and in areas with a
higher proportion of cattle in the total stocking rate. Areas with higher densities of power lines also
registered greater density declines, probably due to avoidance behavior and to increased mortality.
Overall, our results show little bustards are currently lacking high quality grassland habitat, whose
persistence depends on extensive grazing regimes and low linear infrastructure densitiesinfo:eu-repo/semantics/publishedVersio
Enhancement strategies for transdermal drug delivery systems: current trends and applications
Patient Safety in Internal Medicine
AbstractHospital Internal Medicine (IM) is the branch of medicine that deals with the diagnosis and non-surgical treatment of diseases, providing the comprehensive care in the office and in the hospital, managing both common and complex illnesses of adolescents, adults, and the elderly. IM is a key ward for Health National Services. In Italy, for example, about 17.3% of acute patients are discharged from the IM departments. After the epidemiological transition to chronic/degenerative diseases, patients admitted to hospital are often poly-pathological and so requiring a global approach as in IM. As such transition was not associated—with rare exceptions—to hospital re-organization of beds and workforce, IM wards are often overcrowded, burdened by off-wards patients and subjected to high turnover and discharge pressure. All these factors contribute to amplify some traditional clinical risks for patients and health operators. The aim of our review is to describe several potential errors and their prevention strategies, which should be implemented by physicians, nurses, and other healthcare professionals working in IM wards
Relationship of cardiac oxygen usage, adenosine content, and coronary resistance in dogs.
Population biology of salt marsh and sand dune annuals
Annuals represent a significant component of the vegetation of coastal salt marshes and sand dunes. From many points of view, the two habitats might appear to have little in common. Yet both are characterized by episodes of low water potential, marked spatial and temporal heterogeneity and a zonation which, within certain limits, reflects successional change. There are also similarities of distribution. Annuals are dominant usually in the pioneer stages; the Salicornia-dominated low marsh areas are perhaps analogues with strandline ephemeral populations (e.g. Cakile maritima) on the fore-dunes. In mature stages, annuals are associated with small gaps in the matrix of perennials, at least some of these arising from drought or disturbance. Nevertheless populations can reach very high densities. The most striking contrast is phenological; only summer annuals are found on marshes, whereas winter annuals predominate on dunes (except for the strandline). Similarly there is a difference in species richness. Rather few species of annual are typical of marshes while a great many are found on dunes. Properties of the seed bank, survival, reproduction and population regulation are compared in marsh and dune annuals, with special reference to Cakile, Salicornia, Rhinanthus and Vulpia. Interpretations are suggested which take account of environmental predictability and heterogeneity. Finally, the general applicability of simple mathematical models of these populations in the different coastal habitats is considered
Mortality Risks Associated With Emergency Admissions During Weekends and Public Holidays: An Analysis of Electronic Health Records
Mortality risks associated with emergency admissions during weekends and public holidays: electronic health records study
Background: Higher mortality is associated with weekend hospital admission, but the contributions of varying illness severity and admission time to this ‘weekend effect’ remain unexplored. Methods: We analysed unselected emergency admissions to four Oxford University NHS hospitals, UK, January 2006-December 2014. The primary outcome was death within 30-days of admission (in/out of hospital), adjusted for multiple confounders in Cox models including or excluding test results. Findings: 257,596 individuals underwent 503,938 emergency admissions. 18,313 (4·8%) weekday and 6,070 (5·1%) weekend emergency admissions died within 30-days (p<0·0001). 9,347 individuals underwent 9,707 public holiday emergency admissions. 559 (5·8%) died within 30-days (p<0·0001 vs weekday). 15 routine haematology/biochemistry test results were highly prognostic for mortality. In 271,465 (53·9%) admissions with complete data, adjusting for test results explained 33% (95% CI 21%-70%) of the excess mortality associated with emergency admission on Saturdays (vs Wednesdays), 52% (lower 95% CI limit 34%) on Sundays and 87% (lower 95% CI limit 45%) on public holidays after adjusting for standard patient characteristics. Excess mortality was predominantly restricted to admissions between 11am-3pm (interaction p=0·04). No hospital workload measure was independently associated with mortality (p>0.06). Interpretation: Adjusting for routine test results substantially reduced excess mortality associated with weekend/public holiday emergency admission. Adjusting for patient-level factors not available in our study could further reduce the residual excess mortality, which clustered around midday on Saturday/Sunday. Hospital workload was not associated with mortality. Together, these findings suggest that the ‘weekend effect’ arises from patient-level differences at admission rather than reduced hospital staffing or services
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