Intensification of methane production from waste frying oil in a biogas-lift bioreactor

"Available online 31 December 2020"Biogas upgrading from anaerobic digestion of waste frying oils (WFO) was accessed in this study. For that, two bioreactors (Rb-biogas-lift bioreactor with gas and liquid recirculation, Rc-control reactor with liquid recirculation) were fed three times per week, with a mixture of WFO, glycerol and volatile fatty acids (VFA). Rb produced 1.4 times more biogas with higher methane content (79%) than Rc (67%). Higher relative abundance of hydrogenotrophic methanogens (34%-39%) was observed in Rb, when compared to Rc (16%-21%). The relative abundance of Sprochaetia class, which includes some homoacetogens/syntrophic acetate oxidizing genera, was also higher in Rb. This work shows that biogas recirculation applied in the biogas-lift bioreactor facilitated WFO degradation, most probably due to the selective enrichment of hydrogenotrophic methanogens. Recirculation of CO2 present in the biogas and reverse homoacetogenesis (i.e. syntrophic acetate oxidation) seem to be the main factors involved in the stimulation of hydrogenotrophic methanogenesis.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte.info:eu-repo/semantics/publishedVersio

A survey of the clinicopathological and molecular characteristics of patients with suspected Lynch syndrome in Latin America

Background: Genetic counselling and testing for Lynch syndrome (LS) have recently been introduced in several Latin America countries. We aimed to characterize the clinical, molecular and mismatch repair (MMR) variants spectrum of patients with suspected LS in Latin America. Methods: Eleven LS hereditary cancer registries and 34 published LS databases were used to identify unrelated families that fulfilled the Amsterdam II (AMSII) criteria and/or the Bethesda guidelines or suggestive of a dominant colorectal (CRC) inheritance syndrome. Results: We performed a thorough investigation of 15 countries and identified 6 countries where germline genetic testing for LS is available and 3 countries where tumor testing is used in the LS diagnosis. The spectrum of pathogenic MMR variants included MLH1 up to 54%, MSH2 up to 43%, MSH6 up to 10%, PMS2 up to 3% and EPCAM up to 0.8%. The Latin America MMR spectrum is broad with a total of 220 different variants which 80% were private and 20% were recurrent. Frequent regions included exons 11 of MLH1 (15%), exon 3 and 7 of MSH2 (17 and 15%, respectively), exon 4 of MSH6 (65%), exons 11 and 13 of PMS2 (31% and 23%, respectively). Sixteen international founder variants in MLH1, MSH2 and MSH6 were identified and 41 (19%) variants have not previously been reported, thus representing novel genetic variants in the MMR genes. The AMSII criteria was the most used clinical criteria to identify pathogenic MMR carriers although microsatellite instability, immunohistochemistry and family history are still the primary methods in several countries where no genetic testing for LS is available yet. Conclusion: The Latin America LS pathogenic MMR variants spectrum included new variants, frequently altered genetic regions and potential founder effects, emphasizing the relevance implementing Lynch syndrome genetic testing and counseling in all of Latin America countries.Radium Hospital Foundation (Oslo, Norway) in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript, Helse Sør-Øst (Norway) in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript, the French Association Recherche contre le Cancer (ARC) in the analysis, and interpretation of data, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (Gefluc) in the analysis, and interpretation of data, the Association Nationale de la Recherche et de la Technologie (ANRT, CIFRE PhD fellowship to H.T.) in the analysis, and interpretation of data and by the OpenHealth Institute in the analysis, and interpretation of data. Barretos Cancer Hospital received financial support by FINEP-CT-INFRA (02/2010)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

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.Keywords: Social–ecological systems, Tropical forests, Land use, Interdisciplinary research, Sustainability, Trade-off

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