Maternal Serum Meteorin Levels and the Risk of Preeclampsia

BACKGROUND: Meteorin (METRN) is a recently described neutrophic factor with angiogenic properties. This is a nested case-control study in a longitudinal cohort study that describes the serum profile of METRN during different periods of gestation in healthy and preeclamptic pregnant women. Moreover, we explore the possible application of METRN as a biomarker. METHODS AND FINDINGS: Serum METRN was measured by ELISA in a longitudinal prospective cohort study in 37 healthy pregnant women, 16 mild preeclamptic women, and 20 healthy non-pregnant women during the menstrual cycle with the aim of assessing serum METRN levels and its correlations with other metabolic parameters. Immunostaining for METRN protein was performed in placenta. A multivariate logistic regression model was proposed and a classifier model was formulated for predicting preeclampsia in early and middle pregnancy. The performance in classification was evaluated using measures such as sensitivity, specificity, and the receiver operating characteristic (ROC) curve. In healthy pregnant women, serum METRN levels were significantly elevated in early pregnancy compared to middle and late pregnancy. METRN levels are significantly lower only in early pregnancy in preeclamptic women when compared to healthy pregnant women. Decision trees that did not include METRN levels in the first trimester had a reduced sensitivity of 56% in the detection of preeclamptic women, compared to a sensitivity of 69% when METRN was included. CONCLUSIONS: The joint measurements of circulating METRN levels in the first trimester and systolic blood pressure and weight in the second trimester significantly increase the probabilities of predicting preeclampsia

Socially and biologically inspired computing for self-organizing communications networks

The design and development of future communications networks call for a careful examination of biological and social systems. New technological developments like self-driving cars, wireless sensor networks, drones swarm, Internet of Things, Big Data, and Blockchain are promoting an integration process that will bring together all those technologies in a large-scale heterogeneous network. Most of the challenges related to these new developments cannot be faced using traditional approaches, and require to explore novel paradigms for building computational mechanisms that allow us to deal with the emergent complexity of these new applications. In this article, we show that it is possible to use biologically and socially inspired computing for designing and implementing self-organizing communication systems. We argue that an abstract analysis of biological and social phenomena can be made to develop computational models that provide a suitable conceptual framework for building new networking technologies: biologically inspired computing for achieving efficient and scalable networking under uncertain environments; socially inspired computing for increasing the capacity of a system for solving problems through collective actions. We aim to enhance the state-of-the-art of these approaches and encourage other researchers to use these models in their future work

The global abundance of tree palms

Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

Genetic analysis of forest species Eugenia uniflora L. through of newly developed SSR markers

Nine microsatellite loci for genetic analysis of three populations of the tropical tree Eugenia uniflora L. (pitanga or Brazilian cherry) from fragments of semideciduous forest were developed. We used the technique of building a (GA) n and (CA) n microsatellite-enriched library by capture with streptavidin-coated magnetic beads. We assessed the polymorphism of seven microsatellites in 84 mature trees found in three areas (Ribeirão Preto, Tambaú and São José do Rio Pardo), highly impacted by the agricultural practices, in a large region among Pardo river and Mogi-Guaçu river basins, in state of São Paulo, Brazil. All loci were polymorphic, and the number of alleles was high, ranging from 6 to 24, with a mean of 14.4. All stands showed the same high level of genetic diversity (mean H E = 0.83) and a low genetic differentiation (mean F ST = 0.031), indicating that genetic diversity was higher within rather than among populations. Seven of the nine loci were highly variable, and sufficiently informative for E. uniflora. It was concluded that these new SSR markers can be efficiently used for gene flow studies.Ronai Ferreira-Ramos, Prianda R. Laborda, Melissa de Oliveira Santos, Matheus S. Mayor, Moacyr A. Mestriner, Anete P. de Souza, Ana Lilia Alzate-Mari