Coupling Watersheds, Estuaries and Regional Oceanography through Numerical Modelling in the Western Iberia: Thermohaline Flux Variability at the Ocean-Estuary Interface

The characterisation of the water and properties exchanges at the estuary-ocean interface is a key information to understand the estuarine plume influence on coastal circulation and in the generation of haline fronts. In this work, the largest eight Portuguese estuaries were modelled using the MOHID Water numerical model for the period 2010–2016. Water fluxes and associated properties were computed numerically at each of the estuary mouths. These results served to estimate the tidal prisms, tidal flows and to describe the annual evolution of water temperature and salinity. Those fluxes could serve to improve the land boundary conditions for regional ocean models. Moreover, the numerical analysis of the estuarine fluxes allow for the better characterisation of the studied systems, as two neighbouring estuaries could present very different fluxes and water properties. Where available, modelling results were compared with stations near the estuary mouth

AID-Targeting and Hypermutation of Non-Immunoglobulin Genes Does Not Correlate with Proximity to Immunoglobulin Genes in Germinal Center B Cells

Upon activation, B cells divide, form a germinal center, and express the activation induced deaminase (AID), an enzyme that triggers somatic hypermutation of the variable regions of immunoglobulin (Ig) loci. Recent evidence indicates that at least 25% of expressed genes in germinal center B cells are mutated or deaminated by AID. One of the most deaminated genes, c-Myc, frequently appears as a translocation partner with the Ig heavy chain gene (Igh) in mouse plasmacytomas and human Burkitt's lymphomas. This indicates that the two genes or their double-strand break ends come into close proximity at a biologically relevant frequency. However, the proximity of c-Myc and Igh has never been measured in germinal center B cells, where many such translocations are thought to occur. We hypothesized that in germinal center B cells, not only is c-Myc near Igh, but other mutating non-Ig genes are deaminated by AID because they are near Ig genes, the primary targets of AID. We tested this “collateral damage” model using 3D-fluorescence in situ hybridization (3D-FISH) to measure the distance from non-Ig genes to Ig genes in germinal center B cells. We also made mice transgenic for human MYC and measured expression and mutation of the transgenes. We found that there is no correlation between proximity to Ig genes and levels of AID targeting or gene mutation, and that c-Myc was not closer to Igh than were other non-Ig genes. In addition, the human MYC transgenes did not accumulate mutations and were not deaminated by AID. We conclude that proximity to Ig loci is unlikely to be a major determinant of AID targeting or mutation of non-Ig genes, and that the MYC transgenes are either missing important regulatory elements that allow mutation or are unable to mutate because their new nuclear position is not conducive to AID deamination

Portuguese recommendations for the use of biological therapies in patients with axial spondyloarthritis - 2016 update

Objective: To update the recommendations for the treatment of axial spondyloarthritis (axSpA) with biological therapies, endorsed by the Portuguese Society of Rheumatology. Methods: These treatment recommendations were formulated by Portuguese rheumatologists based on lite - rature evidence and consensus opinion. At a national meeting, the recommendations included in this document were discussed and updated. A draft of the full text of the recommendations was then circulated and suggestions were incorporated. A final version was again circulated before publication and the level of agreement among Portuguese Rheumatologists was anonymously assessed using an online survey. Results: A consensus was achieved regarding the initiation, assessment of response and switching of biological therapies in patients with axSpA. In total, seven recommendations were produced. The first recommendation is a general statement indicating that biological therapy is not a first-line drug treatment option and should only be used after conventional treatment has failed. The second recommendation is also a ge - neral statement about the broad concept of axSpA adopted by these recommendations that includes both non-radiographic and radiographic axSpA. Recommendations 3 to 7 deal with the definition of active di - sease (including the recommended threshold of 2.1 for the Ankylosing Spondylitis Disease Activity Score [ASDAS] or the threshold of 4 [0-10 scale] for the Bath Ankylosing Spondylitis Disease Activity Index [BASDAI]), conventional treatment failure (nonsteroidal anti-inflammatory drugs being the first-line drug treatment), assessment of response to treatment (based on an ASDAS improvement of at least 1.1 units or a BASDAI improvement of at least 2 units [0-10 scale] or at least 50%), and strategy in the presence of an ina - dequate response (where switching is recommended) or in the presence of long-term remission (where a process of biological therapy optimization can be consi - dered, either a gradual increase in the interval between doses or a decrease of each dose of the biological the - rapy). Conclusion: These recommendations may be used for guidance in deciding which patients with axSpA should be treated with biological therapies. They co - ver a rapidly evolving area of therapeutic intervention. As more evidence becomes available and more biological therapies are licensed, these recommendations will have to be updated

How much leaf area do insects eat? A data set of insect herbivory sampled globally with a standardized protocol

Herbivory is ubiquitous. Despite being a potential driver of plant distribution and performance, herbivory remains largely undocumented. Some early attempts have been made to review, globally, how much leaf area is removed through insect feeding. Kozlov et al., in one of the most comprehensive reviews regarding global patterns of herbivory, have compiled published studies regarding foliar removal and sampled data on global herbivory levels using a standardized protocol. However, in the review by Kozlov et al., only 15 sampling sites, comprising 33 plant species, were evaluated in tropical areas around the globe. In Brazil, which ranks first in terms of plant biodiversity, with a total of 46,097 species, almost half (43%) being endemic, a single data point was sampled, covering only two plant species. In an attempt to increase knowledge regarding herbivory in tropical plant species and to provide the raw data needed to test general hypotheses related to plant–herbivore interactions across large spatial scales, we proposed a joint, collaborative network to evaluate tropical herbivory. This network allowed us to update and expand the data on insect herbivory in tropical and temperate plant species. Our data set, collected with a standardized protocol, covers 45 sampling sites from nine countries and includes leaf herbivory measurements of 57,239 leaves from 209 species of vascular plants belonging to 65 families from tropical and temperate regions. They expand previous data sets by including a total of 32 sampling sites from tropical areas around the globe, comprising 152 species, 146 of them being sampled in Brazil. For temperate areas, it includes 13 sampling sites, comprising 59 species

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