Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

BACKGROUND: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. OBJECTIVE: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). METHOD: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. RESULTS: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. CONCLUSION: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities

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

Limitations and perceived delays for diagnosis and staging of lung cancer in Portugal: A nationwide survey analysis

Background We aimed to identify the perception of physicians on the limitations and delays for diagnosing, staging and treatment of lung cancer in Portugal. Methods Portuguese physicians were invited to participate an electronic survey (Feb-Apr-2020). Descriptive statistical analyses were performed, with categorical variables reported as absolute and relative frequencies, and continuous variables with non-normal distribution as median and interquartile range (IQR). The association between categorical variables was assessed through Pearson’s chi-square test. Mann-Whitney test was used to compare categorical and continuous variables (Stata v.15.0). Results Sixty-one physicians participated in the study (45 pulmonologists, 16 oncologists), with n = 26 exclusively assisting lung cancer patients. Most experts work in public hospitals (90.16%) in Lisbon (36.07%). During the last semester of 2019, responders performed a median of 85 (IQR 55–140) diagnoses of lung cancer. Factors preventing faster referral to the specialty included poor articulation between services (60.0%) and patients low economic/cultural level (44.26%). Obtaining National Drugs Authority authorization was one of the main reasons (75.41%) for delaying the begin of treatment. The cumulative lag-time from patients’ admission until treatment ranged from 42–61 days. Experts believe that the time to diagnosis could be optimized in around 11.05 days [IQR 9.61–12.50]. Most physicians (88.52%) started treatment before biomarkers results motivated by performance status deterioration (65.57%) or high tumor burden (52.46%). Clinicians exclusively assisting lung cancer cases reported fewer delays for obtaining authorization for biomarkers analysis (p = 0.023). Higher waiting times for surgery (p = 0.001), radiotherapy (p = 0.004), immunotherapy (p = 0.003) were reported by professionals from public hospitals. Conclusions Physicians believe that is possible to reduce delays in all stages of lung cancer diagnosis with further efforts from multidisciplinary teams and hospital administration.This work was supported by AstraZeneca. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Dynamical Boson Stars

The idea of stable, localized bundles of energy has strong appeal as a model for particles. In the 1950s John Wheeler envisioned such bundles as smooth configurations of electromagnetic energy that he called {\em geons}, but none were found. Instead, particle-like solutions were found in the late 1960s with the addition of a scalar field, and these were given the name {\em boson stars}. Since then, boson stars find use in a wide variety of models as sources of dark matter, as black hole mimickers, in simple models of binary systems, and as a tool in finding black holes in higher dimensions with only a single killing vector. We discuss important varieties of boson stars, their dynamic properties, and some of their uses, concentrating on recent efforts.Comment: 79 pages, 25 figures, invited review for Living Reviews in Relativity; major revision in 201

Invasion is a community affair: clandestine followers in the bacterial community associated to green algae, Caulerpa racemosa, track the invasion source

Biological invasions rank amongst the most deleterious components of global change inducing alterations from genes to ecosystems. The genetic characteristics of introduced pools of individuals greatly influence the capacity of introduced species to establish and expand. The recently demonstrated heritability of microbial communities associated to individual genotypes of primary producers makes them a potentially essential element of the evolution and adaptability of their hosts. Here, we characterized the bacterial communities associated to native and non-native populations of the marine green macroalga Caulerpa racemosa through pyrosequencing, and explored their potential role on the strikingly invasive trajectory of their host in the Mediterranean. The similarity of endophytic bacterial communities from the native Australian range and several Mediterranean locations confirmed the origin of invasion and revealed distinct communities associated to a second Mediterranean variety of C. racemosa long reported in the Mediterranean. Comparative analysis of these two groups demonstrated the stability of the composition of bacterial communities through the successive steps of introduction and invasion and suggested the vertical transmission of some major bacterial OTUs. Indirect inferences on the taxonomic identity and associated metabolism of bacterial lineages showed a striking consistency with sediment upheaval conditions associated to the expansion of their invasive host and to the decline of native species. These results demonstrate that bacterial communities can be an effective tracer of the origin of invasion and support their potential role in their eukaryotic host’s adaptation to new environments. They put forward the critical need to consider the 'meta-organism' encompassing both the host and associated micro-organisms, to unravel the origins, causes and mechanisms underlying biological invasions

AFLP analysis reveals high genetic diversity but low population structure in Coccidioides posadasiiisolates from Mexico and Argentina

BACKGROUND: Coccidioides immitis and C. posadasii cause coccidioidomycosis, a disease that is endemic to North and South America, but for Central America, the incidence of coccidioidomycosis has not been clearly established. Several studies suggest genetic variability in these fungi; however, little definitive information has been discovered about the variability of Coccidioides fungi in Mexico (MX) and Argentina (AR). Thus, the goals for this work were to study 32 Coccidioides spp. isolates from MX and AR, identify the species of these Coccidioides spp. isolates, analyse their phenotypic variability, examine their genetic variability and investigate the Coccidioides reproductive system and its level of genetic differentiation. METHODS: Coccidioides spp. isolates from MX and AR were taxonomically identified by phylogenetic inference analysis using partial sequences of the Ag2/PRA gene and their phenotypic characteristics analysed. The genetic variability, reproductive system and level of differentiation were estimated using AFLP markers. The level of genetic variability was assessed measuring the percentage of polymorphic loci, number of effective allele, expected heterocygosity and Index of Association (I(A)). The degree of genetic differentiation was determined by AMOVA. Genetic similarities among isolates were estimated using Jaccard index. The UPGMA was used to contsruct the corresponding dendrogram. Finally, a network of haplotypes was built to evaluate the genealogical relationships among AFLP haplotypes. RESULTS: All isolates of Coccidioides spp. from MX and AR were identified as C. posadasii. No phenotypic variability was observed among the C. posadasii isolates from MX and AR. Analyses of genetic diversity and population structure were conducted using AFLP markers. Different estimators of genetic variability indicated that the C. posadasii isolates from MX and AR had high genetic variability. Furthermore, AMOVA, dendrogram and haplotype network showed a small genetic differentiation among the C. posadasii populations analysed from MX and AR. Additionally, the I(A) calculated for the isolates suggested that the species has a recombinant reproductive system. CONCLUSIONS: No phenotypic variability was observed among the C. posadasii isolates from MX and AR. The high genetic variability observed in the isolates from MX and AR and the small genetic differentiation observed among the C. posadasii isolates analysed, suggest that this species could be distributed as a single genetic population in Latin America

Optimizing the use of systemic corticosteroids in severe asthma (ROSA II project): a national Delphi consensus study

Although the prevalence of severe asthma is not high (5–10% of patients), it is responsible for a large part of the overall disease burden and costs (50–60% of total costs), especially if the condition remains uncontrolled (which occurs in around 40% of cases). Currently, for patients without disease control or presenting frequent exacerbations despite optimal therapy, add-on treatments, traditionally long-acting anticholinergics, oral corticosteroids (OCS), or biologic agents (monoclonal antibodies) are recommended. Nonetheless, the long-term use of oral/systemic corticosteroids (CS) is significantly associated with adverse effects, acute and chronic complications that may decrease health-related quality of life and worsen prognosis, thus requiring additional monitoring and management. Conversely, target therapies (i.e., omalizumab, mepolizumab, reslizumab, benralizumab, and more recently, dupilumab) have been developed grounded on the different phenotypes and endotypes of severe asthma, and are gradually reducing the reliance on OCS (i.e., greater specificity for achieving disease control by reducing the risk of exacerbations and requirements for rescue medication and OCS, with limited adverse events).This work was supported by AstraZeneca.info:eu-repo/semantics/publishedVersio

Charged-particle distributions at low transverse momentum in √s=13 13 TeV pp interactions measured with the ATLAS detector at the LHC

Measurements of distributions of charged particles produced in proton–proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 μb −1 μb−1 . The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators

Search for supersymmetry at √s = 13 TeV in final states with jets and two same-sign leptons or three leptons with the ATLAS detector

A search for strongly produced supersymmetric particles is conducted using signatures involving multiple energetic jets and either two isolated leptons (e or μμ ) with the same electric charge or at least three isolated leptons. The search also utilises b-tagged jets, missing transverse momentum and other observables to extend its sensitivity. The analysis uses a data sample of proton–proton collisions at s√=13s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 corresponding to a total integrated luminosity of 3.2 fb −1−1. No significant excess over the Standard Model expectation is observed. The results are interpreted in several simplified supersymmetric models and extend the exclusion limits from previous searches. In the context of exclusive production and simplified decay modes, gluino masses are excluded at 95%95% confidence level up to 1.1–1.3 TeV for light neutralinos (depending on the decay channel), and bottom squark masses are also excluded up to 540 GeV. In the former scenarios, neutralino masses are also excluded up to 550–850 GeV for gluino masses around 1 TeV