Counterflow dielectrophoresis for trypanosome enrichment and detection in blood

Human African trypanosomiasis or sleeping sickness is a deadly disease endemic in sub-Saharan Africa, caused by single-celled protozoan parasites. Although it has been targeted for elimination by 2020, this will only be realized if diagnosis can be improved to enable identification and treatment of afflicted patients. Existing techniques of detection are restricted by their limited field-applicability, sensitivity and capacity for automation. Microfluidic-based technologies offer the potential for highly sensitive automated devices that could achieve detection at the lowest levels of parasitemia and consequently help in the elimination programme. In this work we implement an electrokinetic technique for the separation of trypanosomes from both mouse and human blood. This technique utilises differences in polarisability between the blood cells and trypanosomes to achieve separation through opposed bi-directional movement (cell counterflow). We combine this enrichment technique with an automated image analysis detection algorithm, negating the need for a human operator

Cycle-centrality in complex networks

Networks are versatile representations of the interactions between entities in complex systems. Cycles on such networks represent feedback processes which play a central role in system dynamics. In this work, we introduce a measure of the importance of any individual cycle, as the fraction of the total information flow of the network passing through the cycle. This measure is computationally cheap, numerically well-conditioned, induces a centrality measure on arbitrary subgraphs and reduces to the eigenvector centrality on vertices. We demonstrate that this measure accurately reflects the impact of events on strategic ensembles of economic sectors, notably in the US economy. As a second example, we show that in the protein-interaction network of the plant Arabidopsis thaliana, a model based on cycle-centrality better accounts for pathogen activity than the state-of-art one. This translates into pathogen-targeted-proteins being concentrated in a small number of triads with high cycle-centrality. Algorithms for computing the centrality of cycles and subgraphs are available for download

Object Detection Through Exploration With A Foveated Visual Field

We present a foveated object detector (FOD) as a biologically-inspired alternative to the sliding window (SW) approach which is the dominant method of search in computer vision object detection. Similar to the human visual system, the FOD has higher resolution at the fovea and lower resolution at the visual periphery. Consequently, more computational resources are allocated at the fovea and relatively fewer at the periphery. The FOD processes the entire scene, uses retino-specific object detection classifiers to guide eye movements, aligns its fovea with regions of interest in the input image and integrates observations across multiple fixations. Our approach combines modern object detectors from computer vision with a recent model of peripheral pooling regions found at the V1 layer of the human visual system. We assessed various eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD performs on par with the SW detector while bringing significant computational cost savings.Comment: An extended version of this manuscript was published in PLOS Computational Biology (October 2017) at https://doi.org/10.1371/journal.pcbi.100574

Marginalization of end-use technologies in energy innovation for climate protection

Mitigating climate change requires directed innovation efforts to develop and deploy energy technologies. Innovation activities are directed towards the outcome of climate protection by public institutions, policies and resources that in turn shape market behaviour. We analyse diverse indicators of activity throughout the innovation system to assess these efforts. We find efficient end-use technologies contribute large potential emission reductions and provide higher social returns on investment than energy-supply technologies. Yet public institutions, policies and financial resources pervasively privilege energy-supply technologies. Directed innovation efforts are strikingly misaligned with the needs of an emissions-constrained world. Significantly greater effort is needed to develop the full potential of efficient end-use technologies

Climate change promotes parasitism in a coral symbiosis.

Coastal oceans are increasingly eutrophic, warm and acidic through the addition of anthropogenic nitrogen and carbon, respectively. Among the most sensitive taxa to these changes are scleractinian corals, which engineer the most biodiverse ecosystems on Earth. Corals' sensitivity is a consequence of their evolutionary investment in symbiosis with the dinoflagellate alga, Symbiodinium. Together, the coral holobiont has dominated oligotrophic tropical marine habitats. However, warming destabilizes this association and reduces coral fitness. It has been theorized that, when reefs become warm and eutrophic, mutualistic Symbiodinium sequester more resources for their own growth, thus parasitizing their hosts of nutrition. Here, we tested the hypothesis that sub-bleaching temperature and excess nitrogen promotes symbiont parasitism by measuring respiration (costs) and the assimilation and translocation of both carbon (energy) and nitrogen (growth; both benefits) within Orbicella faveolata hosting one of two Symbiodinium phylotypes using a dual stable isotope tracer incubation at ambient (26 °C) and sub-bleaching (31 °C) temperatures under elevated nitrate. Warming to 31 °C reduced holobiont net primary productivity (NPP) by 60% due to increased respiration which decreased host %carbon by 15% with no apparent cost to the symbiont. Concurrently, Symbiodinium carbon and nitrogen assimilation increased by 14 and 32%, respectively while increasing their mitotic index by 15%, whereas hosts did not gain a proportional increase in translocated photosynthates. We conclude that the disparity in benefits and costs to both partners is evidence of symbiont parasitism in the coral symbiosis and has major implications for the resilience of coral reefs under threat of global change

Distribution of Capillary Transit Times in Isolated Lungs of Oxygen-Tolerant Rats

Rats pre-exposed to 85% O2 for 5–7 days tolerate the otherwise lethal effects of 100% O2. The objective was to evaluate the effect of rat exposure to 85% O2 for 7 days on lung capillary mean transit time (t¯c) and distribution of capillary transit times (h c(t)). This information is important for subsequent evaluation of the effect of this hyperoxia model on the redox metabolic functions of the pulmonary capillary endothelium. The venous concentration vs. time outflow curves of fluorescein isothiocyanate labeled dextran (FITC-dex), an intravascular indicator, and coenzyme Q1 hydroquinone (CoQ1H2), a compound which rapidly equilibrates between blood and tissue on passage through the pulmonary circulation, were measured following their bolus injection into the pulmonary artery of isolated perfused lungs from rats exposed to room air (normoxic) or 85% O2 for 7 days (hyperoxic). The moments (mean transit time and variance) of the measured FITC-dex and CoQ1H2 outflow curves were determined for each lung, and were then used in a mathematical model [Audi et al. J. Appl. Physiol. 77: 332–351, 1994] to estimate t¯c and the relative dispersion (RDc) of h c(t). Data analysis reveals that exposure to hyperoxia decreases lung t¯c by 42% and increases RDc, a measure h c(t) heterogeneity, by 40%

Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page