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

70º Aniversario de la declaración universal de derechos humanos. La protección internacional de los Derechos Humanos en cuestión

Segundo volúmen de la Colección Perspectivas Iberoamericanas sobre la justicia. La Declaración Universal de los Derechos Humanos de las Naciones Unidas cumple, el 10 de diciembre de 2018, setenta años. La simbólica fecha obliga a los investigadores en derechos humanos a reflexionar críticamente sobre los avances y límites de un complejo sistema de normas y, sobre todo, de valores culturales sustentados en la matriz liberal occidental. Desde entonces, ha habido indiscutibles avances institucionales y normativos, como la creación del Consejo de Derechos Humanos, varios pactos y declaraciones complementarias, órganos específicos, tribunales internacionales, jurisprudencia, constituciones estatales, una infinidad de instituciones basadas en esta “ética mínima universal” que, contradictoriamente, no logró evitar un conjunto de catástrofes humanitarias y de vulneración de derechos. La primera década del siglo XX trae un reflejo limitante al consenso de la posguerra, pues la agresividad de los Estados hegemónicos, en alianza con intereses privados transnacionales, pone en jaque la capacidad del sistema protector frente a guerras humanitarias e internacionales. tratados económicos de nueva generación aquellos que excluyen por completo a la democracia del proceso de negociación.A Declaração Universal dos Direitos Humanos das Nações Unidas completa, em 10 de diciembre de 2018, setenta años. A data simbólica exige dos pesquisadores em direitos humanos uma reflexão crítica a respeito dos avanços y dos limites de um sistema complexo de normas e, principalmente, de valores culturales apoiados na matriz liberal ocidental. De lá para cá, houve indiscutível avanço institucional e normativo, do qual é exemplo a criação do Conselho de Direitos Humanos, diversos pactos e declarações complementarios, órgão específicos, tribunais internacionais, jurisprudência, constituições dos States, uma infinidade de instituições pautadas nesse “mínimo ético universal” que, contraditoriamente, não conseguiu evitar um conjunto de catástrofes humanitárias e de violação de direitos. A primeira década do século XX traz uma reflexão limite para o consenso do pós-guerra, pois a agressividade dos States hegemônicos, em aliança com interesses private transnacionais, põe em check a capacidade do sistema protectivo diante das guerras humanitárias e dos tratados internacionais econômicos de nueva generación aqueles que excluem completamente a democracia do processo negociador

Diabetes Affects Antibody Response to SARS-CoV-2 Vaccination in Older Residents of Long-term Care Facilities: Data From the GeroCovid Vax Study

Objective: Type 2 diabetes may affect the humoral immune response after vaccination, but data concerning coronavirus disease 19 (COVID-19) vaccines are scarce. We evaluated the impact of diabetes on antibody response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in older residents of long-term care facilities (LTCFs) and tested for differences according to antidiabetic treatment. Research design and methods: For this analysis, 555 older residents of LTCFs participating in the GeroCovid Vax study were included. SARS-CoV-2 trimeric S immunoglobulin G (anti-S IgG) concentrations using chemiluminescent assays were tested before the first dose and after 2 and 6 months. The impact of diabetes on anti-S IgG levels was evaluated using linear mixed models, which included the interaction between time and presence of diabetes. A second model also considered diabetes treatment: no insulin therapy (including dietary only or use of oral antidiabetic agents) and insulin therapy (alone or in combination with oral antidiabetic agents). Results: The mean age of the sample was 82.1 years, 68.1% were women, and 25.2% had diabetes. In linear mixed models, presence of diabetes was associated with lower anti-S IgG levels at 2 (β = -0.20; 95% CI -0.34, -0.06) and 6 months (β = -0.22; 95% CI -0.37, -0.07) after the first vaccine dose. Compared with those without diabetes, residents with diabetes not using insulin had lower IgG levels at 2- and 6-month assessments (β = -0.24; 95% CI -0.43, -0.05 and β = -0.30; 95% CI -0.50, -0.10, respectively), whereas no differences were observed for those using insulin. Conclusions: Older residents of LTCFs with diabetes tended to have weaker antibody response to COVID-19 vaccination. Insulin treatment might buffer this effect and establish humoral immunity similar to that in individuals without diabetes