Patterns of habitat use of the endangered fish species Saramugo, Anaecypris hispanica, and the invasive Bleak, Alburnus alburnus: implications for native fish fauna conservation.

The Bleak (Alburnus alburnus) is an invasive fish occurring in high density in many streams and rivers of the Iberian Peninsula, namely in the Guadiana basin. Considering its invasive success, the coexistence with native species can led to negative impacts. Although this species has been considering a biological threat, there is still a lack of knowledge on many aspects of its bio-ecology in Mediterranean climate streams. This study was developed under the Life Project for the Conservation of Saramugo (Anaecypris hispanica) in the Guadiana River Basin and aimed to evaluate the potential impact of the Bleak on the Saramugo populations, considering the patterns of habitat use and distribution. Data were collected in the Guadiana river basin during the spring of 2015 and 2016. The patterns of habitat use, habitat preferences and overlap were quantified. The spatio-temporal variability of the Bleak captures was also evaluated. Saramugo exhibited habitat preferences for deep pools, medium/deep runs and fast riffles and the Bleak showed preference for medium /deep pools and medium/deep runs, resulting in a high habitat overlap between both species. Substrate type and vegetation elements were important for both species, though with distinct preferences. The Bleak performed seasonal movements in the river network that seems related to a dispersal strategy to assure the occupation of new stream areas. The obtained results contribute to support decision-making on the implementation of effective measures that selectively benefit the native fish fauna conservation

Polymorphisms in host immunity modulating genes and risk of invasive aspergillosis: results from the aspBIOmics consortium

Recent studies suggest that immune-modulating single nucleotide polymorphisms (SNPs) influence the risk of developing cancer-related infections. Here, we evaluated whether 36 SNPs within 14 immune-related genes are associated with the risk of Invasive Aspergillosis (IA) and whether genotyping of these variants might improve disease risk prediction. We conducted a case-control association study of 781 immunocompromised patients, 149 of whom were diagnosed with IA. Association analysis showed that the IL4Rrs2107356 and IL8rs2227307 SNPs were associated with an increased risk of IA (OR=1.92, 95%CI: 1.20-3.09 and OR=1.73, 1.06-2.81) whereas the IL12Brs3212227 and IFN?rs2069705 variants were significantly associated with a decreased risk of developing the infection (OR=0.60, 0.38-0.96 and OR=0.63, 0.41-0.97). An allogeneic hematopoietic stem cell transplantation (allo-HSCT)-stratified analysis revealed that the effect observed for the IL4Rrs2107356 and IFN?rs2069705 SNPs was stronger in allo-HSCT (OR=5.63, 1.20-3.09 and OR=0.24, 0.10-0.59) than in non-HSCT patients, suggesting that the presence of these SNPs may render patients more vulnerable to infection especially under severe and prolonged immunosuppressive conditions. Importantly, in vitro studies revealed that carriers of the IFN?rs2069705C allele showed a significantly increased macrophage-mediated neutralisation of fungal conidia (P=0.0003) and, under stimulation conditions, produced higher levels of IFN? mRNA (P=0.049) and IFN? and TNFa cytokines (PLPS-96h=0.057, PPHA-96h=0.036 and PLPS+PHA-96h=0.030 and PPHA -72h=0.045, PLPS+PHA-72h=0.018, PLPS-96h=0.058 and PLPS+PHA -96h=0.0058, respectively). Finally, we also observed that the addition of SNPs significantly associated with IA to a model including clinical variables led to a substantial improvement in the discriminatory ability to predict the disease (AUC=0.659 vs. AUC=0.564, PLR=5.2•10-4 and P50.000Perm=9.34•10-5). These findings suggest that the IFN?rs2069705 SNP influences the risk of IA and that predictive models built with IFN?, IL8, IL12p70 and VEGFa variants might be used to predict disease risk and to implement risk-adapted prophylaxis or diagnostic strategies.This study was supported by grants PI12/02688 from the Fondo de Investigaciones Sanitarias (Madrid, Spain), PIM2010EPA-00756 from the ERA-NET PathoGenoMics (0315900A), and the Collaborative Research Center/Transregio 124 FungiNet. C.C. is supported by the Fundação para a Ciência e Tecnologia, Portugal (SFRH/BPD/96176/2013). This study also was supported by a donation of Consuelo González Moreno, an acute myeloid leukemia survivor. We thank Astella Pharma Inc. for supporting this work.info:eu-repo/semantics/publishedVersio

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

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Workgroup 2 Position Paper, APPLY COST Action CA17132

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