Carbon and nitrogen stock and fluxes in coastal Atlantic Forest of southeast Brazil: potential impacts of climate change on biogeochemical functioning

The Atlantic Forest is one of the most important biomes of Brazil. Originally covering approximately 1.5 million of km(2), today this area has been reduced to 12% of its original size. Climate changes may alter the structure and the functioning of this tropical forest. Here we explore how increases in temperature and changes in precipitation distribution could affect dynamics of carbon and nitrogen in coastal Atlantic Forest of the southeast region of Brazil The main conclusion of this article is that the coastal Atlantic Forest has high stocks of carbon and nitrogen above ground, and especially, below ground. An increase in temperature may transform these forests from important carbon sinks to carbon sources by increasing loss of carbon and nitrogen to the atmosphere. However, this conclusion should be viewed with caution because it is based on limited information. Therefore, more studies are urgently needed to enable us to make more accurate predictions.

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

Phospholipase D2:A Pivotal Player Modulating RBL-2H3 Mast Cell Structure

The current study examined the role of PLD2 in the maintenance of mast cell structure. Phospholipase D (PLD) catalyzes hydrolysis of phosphatidylcholine to produce choline and phosphatidic acid (PA). PLD has two isoforms, PLD1 and PLD2, which vary in expression and localization depending on the cell type. The mast cell line RBL-2H3 was transfected to overexpress catalytically active (PLD2CA) and inactive (PLD2CI) forms of PLD2. The results of this study show that PLD2CI cells have a distinct star-shaped morphology, whereas PLD2CA and RBL-2H3 cells are spindle shaped. In PLD2CI cells, the Golgi complex was also disorganized with dilated cisternae, and more Golgi-associated vesicles were present as compared with the PLD2CA and RBL-2H3 cells. Treatment with exogenous PA led to the restoration of the wild-type Golgi complex phenotype in PLD2CI cells. Conversely, treatment of RBL-2H3 and PLD2CA cells with 1% 1-Butanol led to a disruption of the Golgi complex. The distribution of acidic compartments, including secretory granules and lysosomes, was also modified in PLD2CI cells, where they concentrated in the perinuclear region. These results suggest that the PA produced by PLD2 plays an important role in regulating cell morphology in mast cells. (J Histochem Cytochem 60:386-396, 2012)

Genetic diversity and population structure of Musa accessions in ex situ conservation

Abstract Background Banana cultivars are mostly derived from hybridization between wild diploid subspecies of Musa acuminata (A genome) and M. balbisiana (B genome), and they exhibit various levels of ploidy and genomic constitution. The Embrapa ex situ Musa collection contains over 220 accessions, of which only a few have been genetically characterized. Knowledge regarding the genetic relationships and diversity between modern cultivars and wild relatives would assist in conservation and breeding strategies. Our objectives were to determine the genomic constitution based on Internal Transcribed Spacer (ITS) regions polymorphism and the ploidy of all accessions by flow cytometry and to investigate the population structure of the collection using Simple Sequence Repeat (SSR) loci as co-dominant markers based on Structure software, not previously performed in Musa. Results From the 221 accessions analyzed by flow cytometry, the correct ploidy was confirmed or established for 212 (95.9%), whereas digestion of the ITS region confirmed the genomic constitution of 209 (94.6%). Neighbor-joining clustering analysis derived from SSR binary data allowed the detection of two major groups, essentially distinguished by the presence or absence of the B genome, while subgroups were formed according to the genomic composition and commercial classification. The co-dominant nature of SSR was explored to analyze the structure of the population based on a Bayesian approach, detecting 21 subpopulations. Most of the subpopulations were in agreement with the clustering analysis. Conclusions The data generated by flow cytometry, ITS and SSR supported the hypothesis about the occurrence of homeologue recombination between A and B genomes, leading to discrepancies in the number of sets or portions from each parental genome. These phenomenons have been largely disregarded in the evolution of banana, as the “single-step domestication” hypothesis had long predominated. These findings will have an impact in future breeding approaches. Structure analysis enabled the efficient detection of ancestry of recently developed tetraploid hybrids by breeding programs, and for some triploids. However, for the main commercial subgroups, Structure appeared to be less efficient to detect the ancestry in diploid groups, possibly due to sampling restrictions. The possibility of inferring the membership among accessions to correct the effects of genetic structure opens possibilities for its use in marker-assisted selection by association mapping.