Cholesterol and membrane phospholipid compositions modulate the leakage capacity of the swaposin domain from a potato aspartic protease (StAsp-PSI)

Potato aspartic proteases (StAPs) and their swaposin domain (StAsp-PSI) are proteins with cytotoxic activity which involves plasma membrane destabilization. The ability of these proteins to produce cell death varies with the cellular type. Therefore, StAPs and StAsp-PSI selective cytotoxicity could be attributed to the different membrane lipid compositions of target cells. In this work we investigate the possible mechanism by which StAPs and StAsp-PSI produce selective membrane destabilization. Results obtained from leakage assays show that StAsp-PSI is a potent inducer of the leakage of LUVs containing anionic phospholipids, especially those containing phosphatidylglycerol. Based in these results, we suggest that the cytotoxic activity of StAsp-PSI on pathogenic microorganisms could be mediated by the attraction between the exposed positive domains of StAsp-PSI and the negatively charged microorganism membrane. On the other hand, our circular dichroism spectroscopic measurements and analysis by size exclusion chromatography and followed by electrophoresis, indicate that hydrophobic environment is necessary to StAsp-PSI oligomerization and both StAsp-PSI disulfide bounds and membrane with negative charged phospholipids are required by StAsp-PSI to produce membrane destabilization and then induce cell death in tumors and microorganism cell targets. Additionally, we demonstrate that the presence of cholesterol into the LUV membranes strongly diminishes the capacity of StAsp-PSI to produce leakage. This result suggests that the lack of hemolytic and cytotoxic activities on human lymphocytes of StAsp-PSI/StAPs may be partly due by the presence of cholesterol in these cell membrane types.     

Landscape factors modulating patterns of salmonid distribution during summer in north Patagonian rivers

Understanding how ecosystem processes influencing fish distribution operate across spatial scales is important to understand biological invasions. Salmonids, originally from the Northern Hemisphere, have been repeatedly introduced throughout the world, making them an ideal group to test hypotheses about factors driving invasions. We assessed the influence of environmental variables at the watershed scale on the abundance and structure of salmonid assemblages in the breeding streams of the Upper Limay river basin, Rio Negro, Argentina. We combined field captures with digital map data and geographic information systems to examine landscape-level patterns of salmonid abundance in 35 representative sub-basins of the environmental gradient. We employed a hierarchical cluster analysis and classification and regression tree models to relate the abundance of salmonids and types of species assemblages with environmental characteristics at watershed level. We found stream localization, precipitation regime, altitude and air temperature to be important predictors of the abundance and assemblage structure of salmonids. Total catches showed an increasing gradient of catch-per-unit-effort from west to east and from north to south, with Oncorhynchus mykiss being the most abundant species. O. mykiss relative abundance was westward skewed, where smaller catchments with steeper and shaded valleys are drained by less productive streams with more irregular hydrological regimes, like those found in this species' North American native range. In contrast, the abundance of Salmo trutta abundance was eastward skewed, where larger, sunnier and more gently sloped catchments result in more productive streams with stable hydrological regimes, like those found in that species' European native range. Thus, differential salmonid abundance could result from the interplay between the evolutionary fingerprint left by each species' native environment (especially flow and temperature regimes) and the availability of those conditions in new environments to which they have been translocated. By furthering our understanding of how landscape conditioned invasion success, these findings can help guide the management of economically important introduced fish.     

17‐β‐Estradiol increases macrophage activity through activation of the G‐protein‐coupled estrogen receptor and improves the response of female mice to Cryptococcus gattii

Cryptococcus gattii (Cg) is one of the agents of cryptococcosis, a severe systemic mycosis with a higher prevalence in men than women, but the influence of the female sex hormone, 17‐β‐estradiol (E2), on cryptococcosis remains unclear. Our study shows that female mice presented delayed mortality, increased neutrophil recruitment in bronchoalveolar lavage fluid, and reduced fungal load after 24 hr of infection compared to male and ovariectomised female mice (OVX). E2 replacement restored OVX female survival. Female macrophages have more efficient fungicidal activity, which was increased by E2 and reversed by the antagonist of G‐protein‐coupled oestrogen receptor (GPER), which negatively modulates PI3K activation. Furthermore, E2 induces a reduction in Cg cell diameter, cell charge, and antioxidant peroxidase activity. In conclusion, female mice present improved control of Cg infection, and GPER is important for E2 modulation of the female response.     

Turning the analysis of obesity–mortality associations upside down: Modeling years of life lost through conditional distributions

Objective:

We demonstrate the utility of parametric survival analysis. The analysis of longevity as a function of risk factors such as body mass index (BMI; kg/m²), activity levels, and dietary factors is a mainstay of obesity research. Modeling survival through hazard functions, relative risks, or odds of dying with methods such as Cox proportional hazards or logistic regression are the most common approaches and have many advantages. However, they also have disadvantages in terms of the ease of interpretability, especially for non‐statisticians; the need for additional data to convert parameter estimates to estimates of years of life lost (YLL); debates about the appropriate time scale in the model; and an inability to estimate median survival time when the censoring rate is too high.

Design and Methods:

We will conduct parametric survival analyses with multiple distributions, including distributions that are known to be poor fits (Gaussian), as well as a newly discovered “Compressed Gaussian”'' distribution.

Results:

Parametric survival analysis models were able to accurately estimate median survival times in a population‐based data set of 15,703 individuals, even for distributions that were not good fits and the censoring rate was high, due to the central limit theorem.

Conclusions:

Parametric survival models are able to provide more direct answers, and in our analysis of an obesity‐related data set, gave consistent YLL estimates regardless of the distribution used. We recommend increased consideration of parametric survival models in chronic disease and risk factor epidemiology.