A New Terminal Nonsense Mutation of the Cathepsin C Gene in a Patient With Atypical Papillon-Lefèvre Syndrome

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Wood Quality and Pulping Process Efficiency of Elite <em>Eucalyptus</em> spp. Clones Field-Grown under Seasonal Drought Stress

The objective of the present study is to evaluate the wood quality of five elite Eucalyptus spp. clones at 4 years of age from a clonal test installed in a region of seasonal drought stress in central-western Brazil focusing on pulp production. A total of 25 trees were systematically felled and disks and logs were obtained along the trunk. Wooden disks were used for density and fiber analyses and the logs were converted into chips for application in the pulping process. For the denser genotype, clone D (E. grandis x E. urophylla x Eucalyptus tereticornis), a thicker cell wall associated to thinner fibers results in a negative effect on the fiber quality. In contrast, clone B (Eucalyptus pellita x E. grandis), which has relatively inferior pulping performance, displayed the lowest wood density associated to wider lumen and fibers. The best growth performances in response to acclimatization and adaptation to the site strongly influences the pulp productivity, which is identified as the parameter of greatest variance between genotypes, and highlighting clone E (E. grandis x E. urophylla)

Resposta da soja à adubação com zinco em solo com teores acima do nível crítico

O objetivo deste trabalho foi avaliar a resposta da soja a estratégias de adubação com zinco, em Latossolo com disponibilidade inicial do micronutriente acima do nível crítico. O experimento consistiu em 16 tratamentos com diferentes combinações de fontes, doses e formas de aplicação de Zn. Foram avaliados a produtividade da soja e os teores de Zn no solo, nas folhas e nos grãos. A fertilização com Zn aumentou a produtividade da soja, mesmo em solo com teor do micronutriente acima do nível crítico. A resposta à adubação varia de acordo com as estratégias de aplicação de zinco. Há indícios de que o nível crítico de Zn no solo deve ser revisto

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