Wild immunology: converging on the real world

Recently, the Centre for Immunity, Infection and Evolution sponsored a one-day symposium entitled "Wild Immunology." The CIIE is a new Wellcome Trust-funded initiative with the remit to connect evolutionary biology and ecology with research in immunology and infectious diseases in order to gain an interdisciplinary perspective on challenges to global health. The central question of the symposium was, "Why should we try to understand infection and immunity in wild systems?" Specifically, how does the immune response operate in the wild and how do multiple coinfections and commensalism affect immune responses and host health in these wild systems? The symposium brought together a broad program of speakers, ranging from laboratory immunologists to infectious disease ecologists, working on wild birds, unmanaged animals, wild and laboratory rodents, and on questions ranging from the dynamics of coinfection to how commensal bacteria affect the development of the immune system. The meeting on wild immunology, organized by Amy Pedersen, Simon Babayan, and Rick Maizels, was held at the University of Edinburgh on 30 June 2011.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

Unprotected left main stenting in the real world: two-year outcomes of the French left main taxus registry

BACKGROUND: Cardiac surgery is the reference treatment for patients with left main (LM) disease, although percutaneous coronary intervention with drug-eluting stents is emerging as a possible alternative. The objective of this registry was to evaluate the 2-year outcome of elective percutaneous coronary intervention for unprotected LM disease with paclitaxel-eluting stents. METHODS AND RESULTS: A total of 291 patients were prospectively included from 4 centers. Acute myocardial infarction and cardiogenic shock were the only exclusion criteria. Patients were 69+/-11 years old, 29% were diabetic, and 25% had 3-vessel disease. For distal LM lesions (78%), the provisional side-branch T-stenting approach was used in 92% of cases and final kissing balloon inflation in 97%. Angiographic success was obtained in 99.7% of cases. At 2-year follow-up, the total cardiac death rate was 5.4% (1 EuroSCORE point was associated with a 15% [95% confidence interval 2.9% to 28.2%, P=0.013] higher risk of cardiac death), target-lesion revascularization was 8.7%, and incidence of Q-wave or non-Q-wave myocardial infarction was 0.9% and 3.1%, respectively. The combined end point occurred in 15.8% of cases and stroke in 0.7%. The incidence of definite and probable LM stent thrombosis was 0.7%, whereas the incidence of any stent thrombosis was 3.8%, with a higher risk in patients with side-branch stenting in the presence of LM bifurcation lesions (hazard ratio 9.6, 95% confidence interval 1.2 to 77.7, P=0.035). CONCLUSIONS: Unprotected LM stenting with paclitaxel-eluting stents, with a strategy of provisional side-branch T-stenting for distal lesions, provides excellent acute angiographic results and good mid-term clinical outcomes, with a 15.8% rate of major adverse cardiac events at 2-year follow-up.

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.

Real-World Energy Measurements of a Wireless Mesh Network

Over the past several years the topics of energy consumption and energy harvesting have gained significant importance as a means for improved operation of wireless sensor and mesh networks. Energy-awareness of operation is especially relevant for application scenarios from the domain of environmental monitoring in hard to access areas. In this work we reflect upon our experiences with a real-world deployment of a wireless mesh network. In particular, a comprehensive study on energy measurements collected over several weeks during the summer and the winter period in a network deployment in the Swiss Alps is presented. Energy performance is monitored and analysed for three system components, namely, mesh node, battery and solar panel module. Our findings cover a number of aspects of energy consumption, including the amount of load consumed by a mesh node, the amount of load harvested by a solar panel module, and the dependencies between these two. With our work we aim to shed some light on energy-aware network operation and to help both users and developers in the planning and deployment of a new wireless (mesh) network for environmental research.

Real-World Evaluation of Sensor Context-aware Adaptive Duty-cycled Opportunistic Routing

Energy is of primary concern in wireless sensor networks (WSNs). Low power transmission makes the wireless links unreliable, which leads to frequent topology changes. Resulting packet retransmissions aggravate the energy consumption. Beaconless routing approaches, such as opportunistic routing (OR) choose packet forwarders after data transmissions, and are promising to support dynamic features of WSNs. This paper proposes SCAD - Sensor Context-aware Adaptive Duty-cycled beaconless OR for WSNs. SCAD is a cross-layer routing solution and it brings the concept of beaconless OR into WSNs. SCAD selects packet forwarders based on multiple types of network contexts. To achieve a balance between performance and energy efficiency, SCAD adapts duty-cycles of sensors based on real-time traffic loads and energy drain rates. We implemented SCAD in TinyOS running on top of Tmote Sky sensor motes. Real-world evaluations show that SCAD outperforms other protocols in terms of both throughput and network lifetime.

Evidence from the real world: N-15 natural abundances reveal enhanced nitrogen use at high plant diversity in Central European grasslands

Complementarity that leads to more efficient resource use is presumed to be a key mechanism explaining positive biodiversity–productivity relationships but has been described solely for experimental set-ups with controlled environmental settings or for very short gradients of abiotic conditions, land-use intensity and biodiversity. Therefore, we analysed plant diversity effects on nitrogen dynamics across a broad range of Central European grasslands. The 15N natural abundance in soil and plant biomass reflects the net effect of processes affecting ecosystem N dynamics. This includes the mechanism of complementary resource utilization that causes a decrease in the 15N isotopic signal. We measured plant species richness, natural abundance of 15N in soil and plants, above-ground biomass of the community and three single species (an herb, grass and legume) and a variety of additional environmental variables in 150 grassland plots in three regions of Germany. To explore the drivers of the nitrogen dynamics, we performed several analyses of covariance treating the 15N isotopic signals as a function of plant diversity and a large set of covariates. Increasing plant diversity was consistently linked to decreased δ15N isotopic signals in soil, above-ground community biomass and the three single species. Even after accounting for multiple covariates, plant diversity remained the strongest predictor of δ15N isotopic signals suggesting that higher plant diversity leads to a more closed nitrogen cycle due to more efficient nitrogen use. Factors linked to increased δ15N values included the amount of nitrogen taken up, soil moisture and land-use intensity (particularly fertilization), all indicators of the openness of the nitrogen cycle due to enhanced N-turnover and subsequent losses. Study region was significantly related to the δ15N isotopic signals indicating that regional peculiarities such as former intensive land use could strongly affect nitrogen dynamics. Synthesis. Our results provide strong evidence that the mechanism of complementary resource utilization operates in real-world grasslands where multiple external factors affect nitrogen dynamics. Although single species may differ in effect size, actively increasing total plant diversity in grasslands could be an option to more effectively use nitrogen resources and to reduce the negative environmental impacts of nitrogen losses.

The effects of qualitatively different acute physical activity interventions in real-world settings on executive functions in preadolescent children

There is growing evidence indicating a positive effect of acute physical activity on cognitive performance in children. Most of the evidence originates, however, from studies in highly controlled laboratory settings. The aim of the present study was to investigate whether the same effects can be found in more real-world settings. We examined the effects of qualitatively different acute physical activity interventions on the three core dimensions of executive functions (updating, inhibition, shifting). In an experimental between-subject design, 219 ten to twelve year-olds were assigned to one of four conditions which varied systematically in physical activation and cognitive engagement. Executive functions were measured before and immediately after the intervention. Contrary to the hypothesis, no effects of acute physical activity with and without cognitive engagement were found on executive functions in the overall sample. Only children with higher fitness and/or higher academic achievement benefitted from the interventions in terms of their updating performance. Thus, the results indicate that it may be more difficult to attain positive effects through acute physical activity in real-world settings than in laboratory settings and that physiological and cognitive requirements may have to be adjusted to individual capacity to make an intervention effective.

Plant diversity moderates drought stress in grasslands: Implications from a large real-world study on 13C natural abundances

Land-use change and intensification play a key role in the current biodiversity crisis. The resulting species loss can have severe effects on ecosystem functions and services, thereby increasing ecosystem vulnerability to climate change. We explored whether land-use intensification (i.e. fertilization intensity), plant diversity and other potentially confounding environmental factors may be significantly related to water use (i.e. drought stress) of grassland plants. Drought stress was assessed using δ13C abundances in aboveground plant biomass of 150 grassland plots across a gradient of land-use intensity. Under water shortage, plants are forced to increasingly take up the heavier 13C due to closing stomata leading to an enrichment of 13C in biomass. Plants were sampled at the community level and for single species, which belong to three different functional groups (one grass, one herb, two legumes). Results show that plant diversity was significantly related to the δ13C signal in community, grass and legume biomass indicating that drought stress was lower under higher diversity, although this relation was not significant for the herb species under study. Fertilization, in turn, mostly increased drought stress as indicated by more positive δ13C values. This effect was mostly indirect by decreasing plant diversity. In line with these results, we found similar patterns in the δ13C signal of the organic matter in the topsoil, indicating a long history of these processes. Our study provided strong indication for a positive biodiversity-ecosystem functioning relationship with reduced drought stress at higher plant diversity. However, it also underlined a negative reinforcing situation: as land-use intensification decreases plant diversity in grasslands, this might subsequently increases drought sensitivity. Vice-versa, enhancing plant diversity in species-poor agricultural grasslands may moderate negative effects of future climate change.

The distinction between real and fictional worlds: Investigating individual differences in fantasy understanding

In this paper, two studies are reported in which children’s ability to distinguish reality from fantasy was investigated. In Experiment 1, children of different ages made pairwise comparisons of 12 pictures of fictional figures and 3 photographs of real people by evaluating on a 6-point scale how easily these figures could meet each other. The results revealed that fantasy/reality distinction develops with age: 7–8-year-old showed a fundamental categorical distinction (comparable to that of adults) whereas 3–4-year-old treated the real world like one of many worlds. In Experiment 2, we took an individual differences approach and tested 116 4–5-year-old who performed the same fantasy task. In addition, they were presented with theory-of-mind tasks and tests measuring non-verbal intelligence and language skills. The results showed that, after statistically controlling for age, non-verbal intelligence, and language skills, theory-of-mind abilities still significantly contributed to the prediction of fantasy understanding.