Microplastic contamination and ecological status of freshwater ecosystems: a case study in two northern Portuguese rivers

Background: Most European rivers have not yet achieved “good” ecological status. In addition, the presence and abundance of microplastics (MPs) in freshwater is a matter of great concern to the scientific community. Methodology: This study assesses the ecological status of four sampling sites of Selho (S1–S4) and Costa-Couros (C1–C4) rivers (Guimarães, Portugal), and the abundance of MPs in sediments and benthic macroinvertebrates (Oligochaeta) from those sites. Results: All sites of both rivers under higher pressure did not reach a “good” ecological status (S2–S3, C2–C4) based on the macroinvertebrate community. High levels of nutrients were observed at all sites in both rivers (except C2), especially phosphorus. In the Oligochaeta’s gut of Costa-Couros river, the high number of MPs seems to be associated with their weight (95.25 ± 25.61 to 1069.00 ± 385.30 MPs g/fresh weight), suggesting the existence of malnutrition and digestive disorders, whereas the highest number of MPs in gut (134.00 ± 30.36 to 558.6 ± 100.70 MPs g/fresh weight) were found for the heaviest organisms of Selho. Conclusions: Thus, sites with higher ecological status do not necessarily have lower abundance of MPs. In the sediments, urbanization seems to be the main driver for MP contamination. MP contamination is pervasive across the sediments and Oligochaeta’s gut in both rivers. Since MPs have the potential to cause harm to environmental and human health, it is essential to monitor not only the ecological status of freshwaters, but also emerging pollutants such as MPs.This study was financially supported by the Guimarães City Council, by the Ministry of the Environment and Climate Action (Portugal) through the project “Aqualastic: Educar, Reduzir e Valorizar”, by the Foundation for Science and Technology (FCT) and the POPH/FSE (Human Potential Operational Program/European Social Fund) through funds of CESAM (UIDP/50017/2020; UIDB/50017/2020; LA/P/0094/2020), and by the project comPET (POCI-01-0145-FEDER-030361)

How do Graphene Composite Surfaces Affect the Development and Structure of Marine Cyanobacterial Biofilms?

The progress of nanotechnology has prompted the development of novel marine antifouling coatings. In this study, the influence of a pristine graphene nanoplatelet (GNP)-modified surface in cyanobacterial biofilm formation was evaluated over a long-term assay using an in vitro platform which mimics the hydrodynamic conditions that prevail in real marine environments. Surface characterization by Optical Profilometry and Scanning Electron Microscopy has shown that the main difference between GNP incorporated into a commercially used epoxy resin (GNP composite) and both control surfaces (glass and epoxy resin) was related to roughness and topography, where the GNP composite had a roughness value about 1000 times higher than control surfaces. The results showed that, after 7 weeks, the GNP composite reduced the biofilm wet weight (by 44%), biofilm thickness (by 54%), biovolume (by 82%), and surface coverage (by 64%) of cyanobacterial biofilms compared to the epoxy resin. Likewise, the GNP-modified surface delayed cyanobacterial biofilm development, modulated biofilm structure to a less porous arrangement over time, and showed a higher antifouling effect at the biofilm maturation stage. Overall, this nanocomposite seems to have the potential to be used as a long-term antifouling material in marine applications. Moreover, this multifactorial study was crucial to understanding the interactions between surface properties and cyanobacterial biofilm development and architecture over time

Nursing knowledge on skin ulcer healing: a living scoping review protocol

Objective: This review aims to continuously map the nursing knowledge on skin ulcer healing in any context of care. Introduction: Chronic wounds are an increasing concern for society and health care providers. Pressure ulcers and venous ulcers, among others, have devastating effects on morbidity and quality of life and require a systematic approach. The nursing process is an important method that allows a better organization and overall care quality for a systematic and continuous professional approach to nursing management of skin ulcers. The integration of this nursing knowledge in informatics systems creates an opportunity to embed decision-support models in clinical activity, promoting evidence-based practice. Inclusion criteria: This scoping review will consider articles on nursing data, diagnosis, interventions, and outcomes focused on people with skin ulcers in all contexts of care. This review will include quantitative, qualitative, and mixed methods study designs as well as systematic reviews and dissertations. Methods: JBI’s scoping review guidance, as well as the Cochrane Collaboration’s guidance on living reviews, will be followed to meet the review’s objective. Screening of new literature will be performed regularly, with the review updated according to new findings. The search strategy will map published and unpublished studies. The databases to be searched include MEDLINE, CINAHL, Scopus, JBI Evidence Synthesis, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and PEDro. Searches for unpublished studies will include OpenGrey and Reposito´ rios Cientı´ficos de Acesso Aberto de Portugal. Studies published in English and Portuguese since 2010 will be considered for inclusion.info:eu-repo/semantics/publishedVersio

Nursing knowledge of people with paresis of voluntary muscles: a living scoping review protocol

Objective: This review aims to continuously map the nursing knowledge about people with paresis of voluntary muscles in any context of care. Introduction: Muscle paresis is a condition that significantly impacts quality of life. Nurses have a crucial role in managing this condition, particularly paresis of voluntary movement muscles. However, nursing knowledge about patients with paresis of voluntary muscles is dispersed, hampering the integration of evidence within the structure of information systems. Mapping how the nursing process components are identified is the first step in creating a Nursing Clinical Information Model for this condition, capable of integrating evidence into information systems. Inclusion criteria: This scoping review will consider studies focusing on the nursing process regarding people with paresis of voluntary muscles in all care contexts. The review will include quantitative, qualitative, and mixed-methods study designs, systematic reviews, clinical guidelines, dissertations, and theses. Methods: The review process will follow JBI's scoping review guidance, as well as the Cochrane Collaboration's guidance on living reviews. Screening of new literature will be performed regularly, with the review being updated according to new findings. The search strategy will map published and unpublished studies. The databases to be searched will include MEDLINE, CINAHL, Scopus, JBI Evidence Synthesis, and the Cochrane Central Register of Controlled Trials. Searches for unpublished studies will include OpenGrey and Repositorios Cientificos de Acesso Aberto de Portugal. Studies published in English and Portuguese from 1975 will be considered for inclusion.info:eu-repo/semantics/publishedVersio

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states

SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal

Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. Methods By applying recent phylodynamic models that allow integration of individual-based travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland), which were consistent with the countries with the highest connectivity with Portugal. Although most introductions were estimated to have occurred during early March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the first cases were confirmed. Conclusions Here we conclude that the earlier implementation of measures could have minimized the number of introductions and subsequent virus expansion in Portugal. This study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team, IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation (https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing guidance on the implementation of the phylodynamic models; Joshua L. Cherry (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health) for providing guidance with the subsampling strategies; and all authors, originating and submitting laboratories who have contributed genome data on GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. This study is co-funded by Fundação para a Ciência e Tecnologia and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost