Direct, positive feedbacks produce instability in models of interrelationships among soil structure, plants and arbuscular mycorrhizal fungi

Current conceptual models of reciprocal interactions linking soil structure, plants and arbuscular mycorrhizal fungi emphasise positive feedbacks among the components of the system. However, dynamical systems with high dimensionality and several positive feedbacks (i.e. mutualism) are prone to instability. Further, organisms such as arbuscular mycorrhizal fungi (AMF) are obligate biotrophs of plants and are considered major biological agents in soil aggregate stabilization. With these considerations in mind, we developed dynamical models of soil ecosystems that reflect the main features of current conceptual models and empirical data, especially positive feedbacks and linear interactions among plants, AMF and the component of soil structure dependent on aggregates. We found that systems become increasingly unstable the more positive effects with Type I functional response (i.e., the growth rate of a mutualist is modified by the density of its partner through linear proportionality) are added to the model, to the point that increasing the realism of models by adding linear effects produces the most unstable systems. The present theoretical analysis thus offers a framework for modelling and suggests new directions for experimental studies on the interrelationship between soil structure, plants and AMF. Non-linearity in functional responses, spatial and temporal heterogeneity, and indirect effects can be invoked on a theoretical basis and experimentally tested in laboratory and field experiments in order to account for and buffer the local instability of the simplest of current scenarios. This first model presented here may generate interest in more explicitly representing the role of biota in soil physical structure, a phenomenon that is typically viewed in a more process- and management-focused context. (C) 2011 Elsevier Ltd. All rights reserved.

Therapeutic effects of PPARα agonists on diabetic retinopathy in type 1 diabetes models

Retinal vascular leakage, inflammation, and neovascularization (NV) are features of diabetic retinopathy (DR). Fenofibrate, a peroxisome proliferator-activated receptor a (PPARa) agonist, has shown robust protective effects against DR in type 2 diabetic patients, but its effects on DR in type 1 diabetes have not been reported. This study evaluated the efficacy of fenofibrate on DR in type 1 diabetes models and determined if the effect is PPARa dependent. Oral administration of fenofibrate significantly ameliorated retinal vascular leakage and leukostasis in streptozotocin-induced diabetic rats and in Akita mice. Favorable effects on DR were also achieved by intravitreal injection of fenofibrate or another specific PPARa agonist. Fenofibrate also ameliorated retinal NV in the oxygen-induced retinopathy (OIR) model and inhibited tube formation and migration in cultured endothelial cells. Fenofibrate also attenuated overexpression of intercellular adhesion molecule-1, monocyte chemoattractant protein-1, and vascular endothelial growth factor (VEGF) and blocked activation of hypoxia-inducible factor-1 and nuclear factor-?B in the retinas of OIR and diabetic models. Fenofibrate's beneficial effects were blocked by a specific PPARa antagonist. Furthermore, Ppara knockout abolished the fenofibrate-induced downregulation of VEGF and reduction of retinal vascular leakage in DR models. These results demonstrate therapeutic effects of fenofibrate on DR in type 1 diabetes and support the existence of the drug target in ocular tissues and via a PPARa-dependent mechanism.

Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Synergistic effects of proteasome inhibitor carfilzomib in combination with tyrosine kinase inhibitors in imatinib-sensitive and -resistant chronic myeloid leukemia models

The tyrosine kinase inhibitor (TKI) imatinib has transformed the treatment and outlook of chronic myeloid leukemia (CML); however, the development of drug resistance and the persistence of TKI-resistant stem cells remain obstacles to eradicating the disease. Inhibition of proteasome activity with bortezomib has been shown to effectively induce apoptosis in TKI-resistant cells. In this study, we show that exposure to the next generation proteasome inhibitor carfilzomib is associated with a decrease in ERK signaling and increased expression of Abelson interactor proteins 1 and 2 (ABI-1/2). We also investigate the effect of carfilzomib in models of imatinib-sensitive and -resistant CML and demonstrate a potent reduction in proliferation and induction of apoptosis in a variety of models of imatinib-resistant CML, including primitive CML stem cells. Carfilzomib acts synergistically with the TKIs imatinib and nilotinib, even in imatinib-resistant cell lines. In addition, we found that the presence of immunoproteasome subunits is associated with an increased sensitivity to carfilzomib. The present findings provide a rational basis to examine the potential of carfilzomib in combination with TKIs as a potential therapy for CML, particularly in imatinib-resistant disease.

Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

Evaluation of infilled frames: an updated in-plane-stiffness macro-model considering the effects of vertical loads

The influence of masonry infills on the in-plane behaviour of RC framed structures is a central topic in the seismic evaluation and retrofitting of existing buildings. Many models in the literature use an equivalent strut member in order to represent the infill but, among the parameters influencing the equivalent strut behaviour, the effect of vertical loads acting on the frames is recognized but not quantified. Nevertheless a vertical load causes a non-negligible variation in the in-plane behaviour of infilled frames by influencing the effective volume of the infill. This results in a change in the stiffness and strength of the system. This paper presents an equivalent diagonal pin-jointed strut model taking into account the stiffening effect of vertical loads on the infill in the initial state. The in-plane stiffness of a range of infilled frames was evaluated using a finite element model of the frame-infill system and the cross-section of the strut equivalent to the infill was obtained for different levels of vertical loading by imposing the equivalence between the frame containing the infill and the frame containing the diagonal strut. In this way a law for identifying the equivalent strut width depending on the geometrical and mechanical characteristics of the infilled frame was generalized to consider the influence of vertical loads for use in the practical applications. The strategy presented, limited to the initial stiffness of infilled frames, is preparatory to the definition of complete non-linear cyclic laws for the equivalent strut.

Dynamic modelling of die melt temperature profile in polymer extrusion: Effects of process settings, screw geometry and material

Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.

Balancing the (carbon) budget: Using linear inverse models to estimate carbon flows and mass-balance 13C:15N labelling experiments in low oxygen sediments.

Over 1 million km² of seafloor experience permanent low-oxygen conditions within oxygen minimum zones (OMZs). OMZs are predicted to grow as a consequence of climate change, potentially affecting oceanic biogeochemical cycles. The Arabian Sea OMZ impinges upon the western Indian continental margin at bathyal depths (150 - 1500 m) producing a strong depth dependent oxygen gradient at the sea floor. The influence of the OMZ upon the short term processing of organic matter by sediment ecosystems was investigated using in situ stable isotope pulse chase experiments. These deployed doses of ¹³C:¹⁵N labeled organic matter onto the sediment surface at four stations from across the OMZ (water depth 540 - 1100 m; [O₂] = 0.35 - 15 μM). In order to prevent experimentally anoxia, the mesocosms were not sealed. ¹³C and ¹⁵N labels were traced into sediment, bacteria, fauna and ¹³C into sediment porewater DIC and DOC. However, the DIC and DOC flux to the water column could not be measured, limiting our capacity to obtain mass-balance for C in each experimental mesocosm. Linear Inverse Modeling (LIM) provides a method to obtain a mass-balanced model of carbon flow that integrates stable-isotope tracer data with community biomass and biogeochemical flux data from a range of sources. Here we present an adaptation of the LIM methodology used to investigate how ecosystem structure influenced carbon flow across the Indian margin OMZ. We demonstrate how oxygen conditions affect food-web complexity, affecting the linkages between the bacteria, foraminifera and metazoan fauna, and their contributions to benthic respiration. The food-web models demonstrate how changes in ecosystem complexity are associated with oxygen availability across the OMZ and allow us to obtain a complete carbon budget for the stationa where stable-isotope labelling experiments were conducted.

Can Leakage Models Be More Efficient? Non-Linear Models in Side Channel Attacks

In the last decade, many side channel attacks have been published in academic literature detailing how to efficiently extract secret keys by mounting various attacks, such as differential or correlation power analysis, on cryptosystems. Among the most efficient and widely utilized leakage models involved in these attacks are the Hamming weight and distance models which give a simple, yet effective, approximation of the power consumption for many real-world systems. These leakage models reflect the number of bits switching, which is assumed proportional to the power consumption. However, the actual power consumption changing in the circuits is unlikely to be directly of that form. We, therefore, propose a non-linear leakage model by mapping the existing leakage model via a transform function, by which the changing power consumption is depicted more precisely, hence the attack efficiency can be improved considerably. This has the advantage of utilising a non-linear power model while retaining the simplicity of the Hamming weight or distance models. A modified attack architecture is then suggested to yield the correct key efficiently in practice. Finally, an empirical comparison of the attack results is presented.