Stable isotope-based statistical tools as ecological indicator of pollution sources in Mediterranean transitional water ecosystems

N-stable isotope analysis of macroalgae has become a popular method for the monitoring of nitrogen pollution in aquatic ecosystems. Basing on changes in their δ¹⁵N, macroalgae have been successfully used as biological traps to intercept nitrogen inputs. As different nitrogen sources differ in their isotopic signature, this technique provides useful information on the origin of pollutants and their extension in the water body. However, isotopic fractionation potentially resulting from microbial nitrogen processing, and indirect isotopic variations due to effects of physicochemical conditions on algal nutrient uptake and metabolism, may affect anthropogenic N isotopic values during transportation and assimilation. This in turn can affect the observed isotopic signature in the algal tissue, inducing isotopic variations not related to the origin of assimilated nitrogen, representing a “background noise” in isotope-based water pollution studies.In this study, we focused on three neighbouring coastal lakes (Caprolace, Fogliano and Sabaudia lakes) located south of Rome (Italy). Lakes were characterized by differences in terms of anthropogenic pressure (i.e. urbanization, cultivated crops, livestock grazing) and potential “background noise” levels (i.e. nutrient concentration, pH, microbial concentration). Our aim was to assess nitrogen isotopic variations in fragments of Ulva lactuca specimens after 48 h of submersion to identify and locate the origins of nitrogen pollutants affecting each lake. δ¹⁵N were obtained for replicated specimens of U. lactuca spatially distributed to cover the entire surface of each lake, previously collected from a benchmark, unpolluted site. In order to reduce the environmental background noise on isotopic observations, a Bayesian hierarchical model relating isotopic variation to environmental covariates and random spatial effects was used to describe and understand the distribution of isotopic signals in each lake.Our procedure (i) allowed to remove background noise and confounding effects from the observed isotopic signals; (ii) allowed to detect “hidden” pollution sources that would not be detected when not accounting for the confounding effect of environmental background noise; (iii) produced maps of the three lakes providing a clear representation of the isotopic signal variation even where background noise was high. Maps were useful to locate nitrogen pollution sources, identify the origin of the dissolved nitrogen and quantify the extent of pollutants, showing localized organic pollution impacting Sabaudia and Fogliano, but not Caprolace. This method provided a clear characterization of both intra- and inter-lake anthropogenic pressure gradients, representing a powerful approach to the ecological indication and nitrogen pollution management in complex systems, as transitional waterbodies are.     

Control of the NADPH supply and GSH recycling for oxidative stress management in hepatoma and liver mitochondria

To unveil what controls mitochondrial ROS detoxification, the NADPH supply and GSH/GSSG recycling for oxidative stress management were analyzed in cancer and non-cancer mitochondria. Therefore, proteomic and kinetomic analyses were carried out of the mitochondrial (i) NADPH producing and (ii) GSH/GSSG recycling enzymes associated to oxidative stress management. The protein contents of the eight enzymes analyzed were similar or even higher in AS-30D rat hepatoma mitochondria (HepM) than in rat liver (RLM) and rat heart (RHM) mitochondria, suggesting that the NADPH/GSH/ROS pathway was fully functional in cancer mitochondria.The Vmax values of IDH-2 were much greater than those of GDH, TH and ME, suggesting that IDH-2 is the predominant NADPH producer in the three mitochondrial types; in fact, the GDH reverse reaction was favored. The Vmax values of GR and GPx were lower in HepM than in RLM, suggesting that the oxidative stress management is compromised in cancer mitochondria. The Km values of IDH-2, GR and GPx were all similar among the different mitochondrial types.Kinetic modeling revealed that the oxidative stress management was mainly controlled by GR, GPx and IDH. Modeling and experimentation also revealed that, due to their higher IDH-2 activity and lower GPx activity presumably by acetylation, HepM (i) showed higher steady-state NADPH levels; (ii) required greater peroxide concentrations to achieve reliable steady-state fluxes and metabolite concentration; and (iii) endured higher peroxide concentrations without collapsing their GSH/GSSG ratios. Then, to specifically prompt lower GSH/GSSG ratios under oxidative stress thus compromising cancer mitochondria functioning, GPx should be re-activated.     

A queueing model for predicting message latency in uni-directional <Emphasis Type="Italic">k</Emphasis>-ary <Emphasis Type="Italic">n</Emphasis>-cubes with deterministic routing and non-uniform traffic

The interconnection network is one of the key architectural components in any parallel computer. The distribution of the traffic injected into the network is among the factors that greatly influences network performance. The uniform traffic pattern has been adopted in many existing network performance evaluation studies due to the tractability of the resulting analytical modelling approach. However, many real applications exhibit non-uniform traffic patterns such as hot-spot traffic. K-ary n-cubes have been the mostly widely used in the implementation of practical parallel systems. Extensive research studies have been conducted on the performance modelling and evaluation of these networks. Nonetheless, most of these studies have been confined to uniform traffic distributions and have been based on software simulation. The present paper proposes a new stochastic model to predict message latency in k-ary n-cubes with deterministic routing in the presence of hot-spot traffic. The model has been validated through simulation experiments and has shown a close agreement with simulation results.

Population demography influences climatic niche evolution: evidence from diploid American Hordeum species (Poaceae)

In this study, we explore the interplay of population demography with the evolution of ecological niches during or after speciation in Hordeum. While large populations maintain a high level of standing genetic diversity, gene flow and recombination buffers against fast alterations in ecological adaptation. Small populations harbour lower allele diversity but can more easily shift to new niches if they initially survive under changed conditions. Thus, large populations should be more conservative regarding niche changes in comparison to small populations. We used environmental niche modelling together with phylogenetic, phylogeographic and population genetic analyses to infer the correlation of population demography with changes in ecological niche dimensions in 12 diploid Hordeum species from the New World, forming four monophyletic groups. Our analyses found both shifts and conservatism in distinct niche dimensions within and among clades. Speciation due to vicariance resulted in three species with no pronounced climate niche differences, while species originating due to long‐distance dispersals or otherwise encountering genetic bottlenecks mostly revealed climate niche shifts. Niche convergence among clades indicates a niche‐filling pattern during the last 2 million years in South American Hordeum. We provide evidence that species, which did not encounter population reductions mainly showed ecoclimatic niche conservatism, while major niche shifts occurred in species which have undergone population bottlenecks. Our data allow the conclusion that population demography influences adaptation and niche shifts or conservatism in South American Hordeum species.     

The response of stream periphyton to Pacific salmon: using a model to understand the role of environmental context

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