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

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

El sindicalismo frente al Mercosur

The Coordinadora de Centrales Sindicales del Cono Sur [Coordinator of the Trade Union Centrals of the Southern Cone] has contributed to the development of Mercosur. Instead of assuming a defensive posture, limited to the specific themes of work and social protection, it has adopted a broad strategy which includes documents, proposals and actions designed to promote productive integration and the development of a supranational institutionality. However, it has advanced little in the implementation of concrete plans for protecting the worker: for instance, there is no Mercosur program for monitoring labor conditions. There is a need to give priority to the theme in the trade unions of each of the participant countries, advance in articulating the relations between the respective trade union centrals and design appropriate strategies for confronting the multinational firms.La Coordinadora de Centrales Sindicales del Cono Sur ha contribuido al desarrollo del Mercosur. En lugar de fijar una posición defensiva, relacionada con los temas específicos de trabajo y protección social, ha impulsado una estrategia amplia que incluye documentos, propuestas y acciones orientadas a promover la integración productiva y el desarrollo de la institucionalidad supranacional. Sin embargo, ha obtenido pocos avances en la implementación de planes concretos que garanticen la protección del trabajo; no hay, por ejemplo, un programa de fiscalización laboral del Mercosur. Es necesario ubicar el tema entre las prioridades de los sindicatos de cada país, profundizar la articulación entre las centrales sindicales y diseñar estrategias adecuadas para enfrentar a las empresas transnacionales

Comparing the continuous geboes score with the Robarts Histopathology Index: definitions of histological remission and response and their relation to faecal calprotectin levels

Background and Aims: The histological status of ulcerative colitis [UC] patients in clinical and endoscopic remission has gained space as an important prognostic marker and a key component of disease monitoring. Our main aims were to compare two histological indexes-the continuous Geboes score [GS] and the Robarts Histopathology index [RHI]-regarding their definitions of histological remission and response, and the ability of faecal calprotectin [FC] levels to discriminate between these statuses. Methods: This was an analysis of three prospective cohorts including 422 patients previously enrolled in other studies. Results: The two continuous scores [GS and RHI] were shown to be significantly correlated [correlation coefficient of 0.806, p < 0.001] and particularly close regarding their definition of histological response: 95% and 88% of all patients classified as having/not having [respectively] histological response according to RHI also did so according to GS. Moreover, median FC levels in patients with histological response were lower than those in patients without histological response [GS: 73.00 vs 525.00, p < 0.001; RHI: 73.50 vs 510.00, p < 0.001]; a similar trend was observed when FC levels of patients in histological remission were compared to those of patients with histological activity [GS: 76.00 vs 228.00, p < 0.001; RHI: 73.50 vs 467.00, p < 0.001]. FC levels allowed us to exclude the absence of histological remission [according to RHI] and absence of histological response [according to RHI and GS], with negative predictive values varying from 82% to 96%. However, optimization of the FC cut-off to exclude the absence of histological remission, as for the continuous GS, falls within values that resemble those of the healthy population. Conclusion: The continuous GS and RHI histological scores are strongly correlated in their definitions of histological response. An absence of histological remission could only be excluded at physiological levels of FC.Portuguese IBD group [GEDII- Grupo de Estudo da Doenca Inflamatoria Intestinal]info:eu-repo/semantics/publishedVersio

Deep-sequencing reveals broad subtype-specific HCV resistance mutations associated with treatment failure.

A percentage of hepatitis C virus (HCV)-infected patients fail direct acting antiviral (DAA)-based treatment regimens, often because of drug resistance-associated substitutions (RAS). The aim of this study was to characterize the resistance profile of a large cohort of patients failing DAA-based treatments, and investigate the relationship between HCV subtype and failure, as an aid to optimizing management of these patients. A new, standardized HCV-RAS testing protocol based on deep sequencing was designed and applied to 220 previously subtyped samples from patients failing DAA treatment, collected in 39 Spanish hospitals. The majority had received DAA-based interferon (IFN) α-free regimens; 79% had failed sofosbuvir-containing therapy. Genomic regions encoding the nonstructural protein (NS) 3, NS5A, and NS5B (DAA target regions) were analyzed using subtype-specific primers. Viral subtype distribution was as follows: genotype (G) 1, 62.7%; G3a, 21.4%; G4d, 12.3%; G2, 1.8%; and mixed infections 1.8%. Overall, 88.6% of patients carried at least 1 RAS, and 19% carried RAS at frequencies below 20% in the mutant spectrum. There were no differences in RAS selection between treatments with and without ribavirin. Regardless of the treatment received, each HCV subtype showed specific types of RAS. Of note, no RAS were detected in the target proteins of 18.6% of patients failing treatment, and 30.4% of patients had RAS in proteins that were not targets of the inhibitors they received. HCV patients failing DAA therapy showed a high diversity of RAS. Ribavirin use did not influence the type or number of RAS at failure. The subtype-specific pattern of RAS emergence underscores the importance of accurate HCV subtyping. The frequency of "extra-target" RAS suggests the need for RAS screening in all three DAA target regions

COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy.</jats:p