Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Cytosine arabinoside-metabolizing enzyme genes are underexpressed in children with MLL gene-rearranged acute lymphoblastic leukemia

Infant acute lymphoblastic leukemia (IALL) is characterized by mixed lineage leukemia (MLL) gene rearrangements, unique gene expression profiles, poor prognosis, and drug resistance. One exception is cytosine arabinoside (Ara-C) to which IALL cells seem to be more sensitive. We quantified mRNA expression of Ara-C key enzymes in leukemic lymphoblasts from 64 Brazilian ALL children, 15 of them presenting MLL gene rearrangement, and correlated it with clinical and biological features. The diagnosis was based on morphological criteria and immunophenotyping using monoclonal antibodies. MLL gene rearrangements were detected by conventional cytogenetic analysis, RT-PCR and/or fluorescence in situ hybridization. The DCK and HENT1 expression levels were determined by real-time quantitative PCR using SYBR Green I. Relative quantification was made by the standard curve method. The results were analyzed by Mann-Whitney and Fisher exact tests. A P value of £0.05 was considered to be statistically significant. DCK and HENT1 expression levels were significantly lower in children with MLL gene-rearranged ALL compared to children with MLL germ line ALL (P = 0.0003 and 0.03, respectively). Our results differ from previous ones concerning HENT1 mRNA expression that observed a higher expression level in MLL gene-rearranged leukemias. In conclusion, the expression of the genes related to Ara-C metabolism was lower in MLL-positive children in the sample studied, suggesting the presence of population differences in the expression profile of these genes especially for HENT1