The complete mitochondrial genome of the foodborne parasitic pathogen Cyclospora cayetanensis

Cyclospora cayetanensis is a human-specific coccidian parasite responsible for several food and water-related outbreaks around the world, including the most recent ones involving over 900 persons in 2013 and 2014 outbreaks in the USA. Multicopy organellar DNA such as mitochondrion genomes have been particularly informative for detection and genetic traceback analysis in other parasites. We sequenced the C. cayetanensis genomic DNA obtained from stool samples from patients infected with Cyclospora in Nepal using the Illumina MiSeq platform. By bioinformatically filtering out the metagenomic reads of non-coccidian origin sequences and concentrating the reads by targeted alignment, we were able to obtain contigs containing Eimeria-like mitochondrial, apicoplastic and some chromosomal genomic fragments. A mitochondrial genomic sequence was assembled and confirmed by cloning and sequencing targeted PCR products amplified from Cyclospora DNA using primers based on our draft assembly sequence. The results show that the C. cayetanensis mitochondrion genome is 6274 bp in length, with 33% GC content, and likely exists in concatemeric arrays as in Eimeria mitochondrial genomes. Phylogenetic analysis of the C. cayetanensis mitochondrial genome places this organism in a tight cluster with Eimeria species. The mitochondrial genome of C. cayetanensis contains three protein coding genes, cytochrome (cytb), cytochrome C oxidase subunit 1 (cox1), and cytochrome C oxidase subunit 3 (cox3), in addition to 14 large subunit (LSU) and nine small subunit (SSU) fragmented rRNA genes

Robots that can adapt like animals

As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they will become damaged. However, while animals can quickly adapt to a wide variety of injuries, current robots cannot "think outside the box" to find a compensatory behavior when damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. Here we introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than two minutes, without requiring self-diagnosis or pre-specified contingency plans. Before deployment, a robot exploits a novel algorithm to create a detailed map of the space of high-performing behaviors: This map represents the robot's intuitions about what behaviors it can perform and their value. If the robot is damaged, it uses these intuitions to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a compensatory behavior that works in spite of the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new technique will enable more robust, effective, autonomous robots, and suggests principles that animals may use to adapt to injury

Ultrasound-evoked immediate early gene expression in the brainstem of the Chinese torrent frog, Odorrana tormota

The concave-eared torrent frog, Odorrana tormota, has evolved the extraordinary ability to communicate ultrasonically (i.e., using frequencies > 20 kHz), and electrophysiological experiments have demonstrated that neurons in the frog’s midbrain (torus semicircularis) respond to frequencies up to 34 kHz. However, at this time, it is unclear which region(s) of the torus and what other brainstem nuclei are involved in the detection of ultrasound. To gain insight into the anatomical substrate of ultrasound detection, we mapped expression of the activity-dependent gene, egr-1, in the brain in response to a full-spectrum mating call, a filtered, ultrasound-only call, and no sound. We found that the ultrasound-only call elicited egr-1 expression in the superior olivary and principal nucleus of the torus semicircularis. In sampled areas of the principal nucleus, the ultrasound-only call tended to evoke higher egr-1 expression than the full-spectrum call and, in the center of the nucleus, induced significantly higher egr-1 levels than the no-sound control. In the superior olivary nucleus, the full-spectrum and ultrasound-only calls evoked similar levels of expression that were significantly greater than the control, and egr-1 induction in the laminar nucleus showed no evidence of acoustic modulation. These data suggest that the sampled areas of the principal nucleus are among the regions sensitive to ultrasound in this species

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

Chronic Oedema and the older person: The effects of ageing upon treatment outcomes

Chronic oedema (CO) and lymphoedema (LO) are long-term conditions that can become more complicated or are more likely to develop with age. The ageing process can involve alterations in the structures that support the normal function of the lymphatic system or put it at greater risk of damage. The main three components (skin care, exercise and compression therapy) within the management of CO/LO can become more difficult to apply with age. This is because of reduced healing rates, decreased cardiovascular capacity and deterioration in vascular and arterial structures. The impact of ageing and how this can affect patients and treatment outcomes requires careful consideration

UBR5 is a Novel E3 Ubiquitin Ligase involved in Skeletal Muscle Hypertrophy and Recovery from Atrophy

We have recently identified that a HECT domain E3 ubiquitin ligase, named UBR5, was epigenetically altered (via DNA methylation) after human skeletal muscle hypertrophy, where its gene expression was positively correlated with increased lean leg mass in humans [1]. This was counterintuitive given the well-defined role of other E3 ligase family members, MuRF1 and MAFbx in muscle atrophy. Therefore, in the present study we aimed to investigate this relatively uncharacterised E3 ubiquitin ligase using multiple in-vivo and in-vitro models of skeletal muscle atrophy, injury, recovery from atrophy as well as anabolism and hypertrophy. We report for the first time, that during atrophy evoked by tetrodotoxin (TTX) nerve silencing in rats, the UBR5 promoter was significantly hypomethylated with a concomitant increase in gene expression early (3 & 7 days) after the induction of atrophy. However, at these timepoints larger increases in MuRF1/MAFbx were observed, and UBR5 expression had returned to baseline levels during later atrophy (14 days) where muscle mass loss was greatest. We confirmed an alternate gene expression profile for UBR5 versus MuRF1/MAFbx in a secondary model of atrophy induced by 7 days continuous low frequency electrical stimulation, where UBR5 demonstrated no significant increase, whereas MuRF1/MAFbx were elevated. Further, after partial (52%) recovery of muscle mass following 7 days TTX-cessation, UBR5 was hypomethylated and increased at the gene expression level, while alternately, reductions in gene expression of MuRF1 and MAFbx were observed. To substantiate these gene expression findings, we observed a significant increase in UBR5 protein abundance after full recovery (14 days) of muscle mass from hindlimb unloading (HU) in rats. Aged rats also demonstrated a similar temporal increase in UBR5 protein abundance after recovery from HU. Further, we confirmed significant increases in UBR5 protein during recovery from nerve crush injury in mice at 28 and 45 days, that related to a full recovery of muscle mass between 45-60 days. During anabolism and hypertrophy, UBR5 gene expression increased following an acute bout of mechanical loading in three-dimensional bioengineered mouse muscle in-vitro, and after chronic electrical stimulation-induced hypertrophy in rats in-vivo, without increases in MuRF1/MAFbx. Additionally, increased UBR5 protein abundance was identified following synergist ablation/functional overload (FO)-induced hypertrophy of the plantaris muscle in mice in-vivo, and finally over a 7-day time-course of regeneration in primary human muscle cells in-vitro. Finally, genetic association studies (> 700,000 SNPs) in human cohorts identified that the A alleles of rs10505025 and rs4734621 SNPs were strongly associated with larger cross-sectional area of fast-twitch muscle fibres and favoured strength/power versus endurance/untrained phenotypes. Overall, we suggest that UBR5 is a novel E3 ubiquitin ligase that is alternatively regulated compared to MuRF1/MAFbx, and is elevated during early atrophy (but not later atrophy), recovery, anabolism and hypertrophy in animals in-vivo as well as during human muscle cell regeneration in-vitro. In humans, genetic variations of the UBR5 gene are strongly associated with larger fast-twitch muscle fibres and strength/power performance

Optima TB: A tool to help optimally allocate tuberculosis spending.

Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is required to maximise the impact of limited budgets. The Optima TB tool has been developed to support analytical capacity and inform evidence-based priority setting processes for TB health benefits package design. This paper outlines the Optima TB framework and how it was applied in Belarus, an upper-middle income country in Eastern Europe with a relatively high burden of TB. Optima TB is a population-based disease transmission model, with programmatic cost functions and an optimisation algorithm. Modelled populations include age-differentiated general populations and higher-risk populations such as people living with HIV. Populations and prospective interventions are defined in consultation with local stakeholders. In partnership with the latter, demographic, epidemiological, programmatic, as well as cost and spending data for these populations and interventions are then collated. An optimisation analysis of TB spending was conducted in Belarus, using program objectives and constraints defined in collaboration with local stakeholders, which included experts, decision makers, funders and organisations involved in service delivery, support and technical assistance. These analyses show that it is possible to improve health impact by redistributing current TB spending in Belarus. Specifically, shifting funding from inpatient- to outpatient-focused care models, and from mass screening to active case finding strategies, could reduce TB prevalence and mortality by up to 45% and 50%, respectively, by 2035. In addition, an optimised allocation of TB spending could lead to a reduction in drug-resistant TB infections by 40% over this period. This would support progress towards national TB targets without additional financial resources. The case study in Belarus demonstrates how reallocations of spending across existing and new interventions could have a substantial impact on TB outcomes. This highlights the potential for Optima TB and similar modelling tools to support evidence-based priority setting

Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment

<p>Abstract</p> <p>Background</p> <p>While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile.</p> <p>Methods</p> <p>RNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes.</p> <p>Results</p> <p><it>In silico </it>models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils) and cells of the adaptive immune system (peripheral blood mononuclear cells).</p> <p>Conclusion</p> <p>Genome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant to perturbation.</p