260 research outputs found

    Modern Advancement in Biotechnological Applications for Wastewater Treatment through Microalgae: a Review

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    ABSTRACT: Microalgae are microscopic organisms that have a broad range of applications, from wastewater treatment, CO2 mitigation to therapeutic proteins, and pharmaceuticals. Recently, the combination of wastewater treatment-based microalgae and the use of the obtained biomass as biofertilizers/stimulants/pesticides have been highly emphasized for their use in the agriculture field. Biofertilizers are a need of today's agriculture practices due to the increasing demand for food to feed a hungry planet while avoiding chemical contamination by the over-application of synthetic fertilizers. There is a constant need for modern techniques for the use of microalgae in a sustainable manner to harness their products to their full extent. Various types of bioreactors are available on the market, each with its own advantages and disadvantages, which, based on their efficiency, can be used for microalgae cultivation. This review aims at reporting recent developments in microalgae biotechnology, especially related to CO2 mitigation, wastewater purification, biofuel, feedstock, future food, therapeutic proteins, pharmaceuticals, and biofertilizers, highlighting some of the current research in this field and future development priorities.info:eu-repo/semantics/publishedVersio

    Diffusion-weighted imaging: determination of the best pair ofb-values to discriminate breast lesions

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    In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T. METHODS: 152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm−2. ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types. RESULTS: Considering the cut-off values 1.46 and 1.49 × 103mm2 s−1, the pairs 50, 1000 and 200, 800 s mm−2 showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm−2 with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10−3 mm2 s−1 for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10−3 mm2 s−1; confidence interval 95%: (−0.0036; 0.0186); p = 0.18]. CONCLUSION: The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm−2.info:eu-repo/semantics/publishedVersio

    Hydrogen bond arrangement is shown to differ in coexisting phases of aqueous two-phase systems

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    Analysis by attenuated total reflection-Fourier transform infrared spectroscopy shows that each coexisting phase in aqueous two-phase systems has a different arrangement of hydrogen bonds. Specific arrangements vary for systems formed by different solutes. The hydrogen bond arrangement is shown to correlate with differences in hydrophobic and electrostatic properties of the different phases of five specific systems, four formed by two polymers and one by a single polymer and salt. The results presented here suggest that the arrangement of hydrogen bonds may be an important factor in phase separation.P.P.M. acknowledges University of Aveiro, CICECO-Aveiro Institute of Materials for funding in the framework of the project UIDB/5011/2020 and UIDP/50011/2020, financed by national funds through the FCT/MEC contract foreseen in the numbers 4, 5, and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19.publishe

    Mycobacterium leprae diversity and population dynamics in medieval Europe from novel ancient genomes.

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    Funder: Max-Planck SocietyFunder: St John’s College, CambridgeFunder: Fondation Raoul FollereauFunder: University of Zurich’s University Research Priority Program “Evolution in Action: From Genomes to Ecosystems”Funder: the Senckenberg Centre for Human Evolution and Palaeoenvironment (S-HEP) at the University of TübingenBackgroundHansen's disease (leprosy), widespread in medieval Europe, is today mainly prevalent in tropical and subtropical regions with around 200,000 new cases reported annually. Despite its long history and appearance in historical records, its origins and past dissemination patterns are still widely unknown. Applying ancient DNA approaches to its major causative agent, Mycobacterium leprae, can significantly improve our understanding of the disease's complex history. Previous studies have identified a high genetic continuity of the pathogen over the last 1500 years and the existence of at least four M. leprae lineages in some parts of Europe since the Early Medieval period.ResultsHere, we reconstructed 19 ancient M. leprae genomes to further investigate M. leprae's genetic variation in Europe, with a dedicated focus on bacterial genomes from previously unstudied regions (Belarus, Iberia, Russia, Scotland), from multiple sites in a single region (Cambridgeshire, England), and from two Iberian leprosaria. Overall, our data confirm the existence of similar phylogeographic patterns across Europe, including high diversity in leprosaria. Further, we identified a new genotype in Belarus. By doubling the number of complete ancient M. leprae genomes, our results improve our knowledge of the past phylogeography of M. leprae and reveal a particularly high M. leprae diversity in European medieval leprosaria.ConclusionsOur findings allow us to detect similar patterns of strain diversity across Europe with branch 3 as the most common branch and the leprosaria as centers for high diversity. The higher resolution of our phylogeny tree also refined our understanding of the interspecies transfer between red squirrels and humans pointing to a late antique/early medieval transmission. Furthermore, with our new estimates on the past population diversity of M. leprae, we gained first insights into the disease's global history in relation to major historic events such as the Roman expansion or the beginning of the regular transatlantic long distance trade. In summary, our findings highlight how studying ancient M. leprae genomes worldwide improves our understanding of leprosy's global history and can contribute to current models of M. leprae's worldwide dissemination, including interspecies transmissions

    Mycobacterium leprae diversity and population dynamics in medieval Europe from novel ancient genomes

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    Background: Hansen’s disease (leprosy), widespread in medieval Europe, is today mainly prevalent in tropical and subtropical regions with around 200,000 new cases reported annually. Despite its long history and appearance in historical records, its origins and past dissemination patterns are still widely unknown. Applying ancient DNA approaches to its major causative agent, Mycobacterium leprae, can significantly improve our understanding of the disease’s complex history. Previous studies have identified a high genetic continuity of the pathogen over the last 1500 years and the existence of at least four M. leprae lineages in some parts of Europe since the Early Medieval period. Results: Here, we reconstructed 19 ancient M. leprae genomes to further investigate M. leprae’s genetic variation in Europe, with a dedicated focus on bacterial genomes from previously unstudied regions (Belarus, Iberia, Russia, Scotland), from multiple sites in a single region (Cambridgeshire, England), and from two Iberian leprosaria. Overall, our data confirm the existence of similar phylogeographic patterns across Europe, including high diversity in leprosaria. Further, we identified a new genotype in Belarus. By doubling the number of complete ancient M. leprae genomes, our results improve our knowledge of the past phylogeography of M. leprae and reveal a particularly high M. leprae diversity in European medieval leprosaria. Conclusions: Our findings allow us to detect similar patterns of strain diversity across Europe with branch 3 as the most common branch and the leprosaria as centers for high diversity. The higher resolution of our phylogeny tree also refined our understanding of the interspecies transfer between red squirrels and humans pointing to a late antique/early medieval transmission. Furthermore, with our new estimates on the past population diversity of M. leprae, we gained first insights into the disease’s global history in relation to major historic events such as the Roman expansion or the beginning of the regular transatlantic long distance trade. In summary, our findings highlight how studying ancient M. leprae genomes worldwide improves our understanding of leprosy’s global history and can contribute to current models of M. leprae’s worldwide dissemination, including interspecies transmissions

    Quantitative differential proteomics of yeast extracellular matrix: there is more to it than meets the eye

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    Background: Saccharomyces cerevisiae multicellular communities are sustained by a scaffolding extracellular matrix, which provides spatial organization, and nutrient and water availability, and ensures group survival. According to this tissue-like biology, the yeast extracellular matrix (yECM) is analogous to the higher Eukaryotes counterpart for its polysaccharide and proteinaceous nature. Few works focused on yeast biofilms, identifying the flocculin Flo11 and several members of the HSP70 in the extracellular space. Molecular composition of the yECM, is therefore mostly unknown. The homologue of yeast Gup1 protein in high Eukaryotes (HHATL) acts as a regulator of Hedgehog signal secretion, therefore interfering in morphogenesis and cell-cell communication through the ECM, which mediates but is also regulated by this signalling pathway. In yeast, the deletion of GUP1 was associated with a vast number of diverse phenotypes including the cellular differentiation that accompanies biofilm formation. Methods: S. cerevisiae W303-1A wt strain and gup1Δ mutant were used as previously described to generate biofilmlike mats in YPDa from which the yECM proteome was extracted. The proteome from extracellular medium from batch liquid growing cultures was used as control for yECM-only secreted proteins. Proteins were separated by SDS-PAGE and 2DE. Identification was performed by HPLC, LC-MS/MS and MALDI-TOF/TOF. The protein expression comparison between the two strains was done by DIGE, and analysed by DeCyder Extended Data Analysis that included Principal Component Analysis and Hierarchical Cluster Analysis. Results: The proteome of S. cerevisiae yECM from biofilm-like mats was purified and analysed by Nano LC-MS/MS, 2D Difference Gel Electrophoresis (DIGE), and MALDI-TOF/TOF. Two strains were compared, wild type and the mutant defective in GUP1. As controls for the identification of the yECM-only proteins, the proteome from liquid batch cultures was also identified. Proteins were grouped into distinct functional classes, mostly Metabolism, Protein Fate/Remodelling and Cell Rescue and Defence mechanisms, standing out the presence of heat shock chaperones, metalloproteinases, broad signalling cross-talkers and other putative signalling proteins. The data has been deposited to the ProteomeXchange with identifier PXD001133.Conclusions: yECM, as the mammalian counterpart, emerges as highly proteinaceous. As in higher Eukaryotes ECM, numerous proteins that could allow dynamic remodelling, and signalling events to occur in/and via yECM were identified. Importantly, large sets of enzymes encompassing full antagonistic metabolic pathways, suggest that mats develop into two metabolically distinct populations, suggesting that either extensive moonlighting or actual metabolism occurs extracellularly. The gup1Δ showed abnormally loose ECM texture. Accordingly, the correspondent differences in proteome unveiled acetic and citric acid producing enzymes as putative players in structural integrity maintenance.This work was funded by the Marie Curie Initial Training Network GLYCOPHARM (PITN-GA-2012-317297), and by national funds from FCT I.P. through the strategic funding UID/BIA/04050/2013. Fábio Faria-Oliveira was supported by a PhD scholarship (SFRH/BD/45368/2008) from FCT (Fundação para a Ciência e a Tecnologia). We thank David Caceres and Montserrat MartinezGomariz from the Unidad de Proteómica, Universidad Complutense de Madrid – Parque Científico de Madrid, Spain for excellent technical assistance in the successful implementation of all proteomics procedures including peptide identification, and Joana Tulha from the CBMA, Universidade do Minho, Portugal, for helping with the SDS-PAGE experiments, and the tedious and laborious ECM extraction procedures. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium, via the PRIDE partner repository, with the dataset identifier PXD001133. We would like to thank the PRIDE team for all the help and support during the submission process.info:eu-repo/semantics/publishedVersio

    CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

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    Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

    Mapping density, diversity and species-richness of the Amazon tree flora

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    Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution
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