13 research outputs found

    The cystic fibrosis microbiome in an ecological perspective and its impact in antibiotic therapy

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    The recent focus on the cystic fibrosis (CF) complex microbiome has led to the recognition that the microbes can interact between them and with the host immune system, affecting the disease progression and treatment routes. Although the main focus remains on the interactions between traditional pathogens, growing evidence supports the contribution and the role of emergent species. Understanding the mechanisms and the biological effects involved in polymicrobial interactions may be the key to improve effective therapies and also to define new strategies for disease control. This review focuses on the interactions between microbe-microbe and host-microbe, from an ecological point of view, discussing their impact on CF disease progression. There are increasing indications that these interactions impact the success of antimicrobial therapy. Consequently, a new approach where therapy is personalized to patients by taking into account their individual CF microbiome is suggested.Portuguese Foundation for Science and Technology (FCT), the strategic funding of UID/BIO/04469/2013-CEB and UID/EQU/00511/2013-LEPABE units. This study was also supported by FCT and the European Community fund FEDER, through Program COMPETE, under the scope of the Projects “DNA mimics” PIC/IC/82815/2007, RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462), “BioHealth—Biotechnology and Bioengineering approaches to improve health quality”, Ref. NORTE-07-0124-FEDER-000027 and NORTE-07-0124-FEDER-000025—RL2_ Environment and Health, co-funded by the Programa Operacional Regional do Norte (ON.2 – O Novo Norte), QREN, FEDER. The authors also acknowledge the grant of Susana P. Lopes (SFRH/BPD/95616/2013) and of the COST-Action TD1004: Theragnostics for imaging and therapy

    TRY plant trait database – enhanced coverage and open access

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    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

    Imaging in neurooncology

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    Imaging in Neurooncology

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    Summary: Imaging in patients with brain tumors aims toward the determination of the localization, extend, type, and malignancy of the tumor. Imaging is being used for primary diagnosis, planning of treatment including placement of stereotaxic biopsy, resection, radiation, guided application of experimental therapeutics, and delineation of tumor from functionally important neuronal tissue. After treatment, imaging is being used to quantify the treatment response and the extent of residual tumor. At follow-up, imaging helps to determine tumor progression and to differentiate recurrent tumor growth from treatment-induced tissue changes, such as radiation necrosis. A variety of complementary imaging methods are currently being used to obtain all the information necessary to achieve the abovementioned goals. Computed tomography and magnetic resonance imaging (MRI) reveal mostly anatomical information on the tumor, whereas magnetic resonance spectroscopy and positron emission tomography (PET) give important information on the metabolic state and molecular events within the tumor. Functional MRI and functional PET, in combination with electrophysiological methods like transcranial magnetic stimulation, are being used to delineate functionally important neuronal tissue, which has to be preserved from treatment-induced damage, as well as to gather information on tumor-induced brain plasticity. In addition, optical imaging devices have been implemented in the past few years for the development of new therapeutics, especially in experimental glioma models. In summary, imaging in patients with brain tumors plays a central role in the management of the disease and in the development of improved imaging-guided therapies

    Spatial Mobility, Family Dynamics, and Housing Transitions

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    This paper summarizes theoretical approaches and empirical research on the links between partnership and family dynamics on the one hand and spatial mobility and housing transitions on the other. Spatial mobility includes residential relocations and commuting. We consider three types of partnerships—living apart together, unmarried and married co-residential unions—and the transitions between them. We also consider separations and the death of a partner. Moreover, we pay attention to childbirth and its consequences for relocation decisions and housing. We differentiate spatial mobility according to distance and direction; housing transitions are considered mainly with respect to changes in ownership status and housing quality (e.g. size of the accommodation). In line with the adjustment perspective on spatial mobility, this paper demonstrates that spatial mobility is a means for individuals and households to adjust their housing situation and their place of residence to requirements of a changing household size and composition as well as to demands of the labor market. At the same time, spatial mobility seems to be more than a mere adjustment process of individuals or households: it is also a determinant of life course changes

    Räumliche Mobilität, Familiendynamik und Wohnen

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    The global spectrum of plant form and function:enhanced species-level trait dataset

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    The global spectrum of plant form and function: enhanced species-level trait dataset.

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    Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date
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