Spin-size disorder model for granular superconductors with charging effects

A quantum pseudo-spin model with random spin sizes is introduced to study the effects of charging-energy disorder on the superconducting transition in granular superconducting materials. Charging-energy effects result from the small electrical capacitance of the grains when the Coulomb charging energy is comparable to the Josephson coupling energy. In the pseudo-spin model, randomness in the spin size is argued to arise from the inhomogeneous grain-size distribution. For a particular bimodal spin-size distribution, the model describes percolating granular superconductors. A mean-field theory is developed to obtain the phase diagram as a function of temperature, average charging energy and disorder.Comment: 4 pages, 2 figure

DNA Adenine Methylation Is Required to Replicate Both Vibrio cholerae Chromosomes Once per Cell Cycle

DNA adenine methylation is widely used to control many DNA transactions, including replication. In Escherichia coli, methylation serves to silence newly synthesized (hemimethylated) sister origins. SeqA, a protein that binds to hemimethylated DNA, mediates the silencing, and this is necessary to restrict replication to once per cell cycle. The methylation, however, is not essential for replication initiation per se but appeared so when the origins (oriI and oriII) of the two Vibrio cholerae chromosomes were used to drive plasmid replication in E. coli. Here we show that, as in the case of E. coli, methylation is not essential for oriI when it drives chromosomal replication and is needed for once-per-cell-cycle replication in a SeqA-dependent fashion. We found that oriII also needs SeqA for once-per-cell-cycle replication and, additionally, full methylation for efficient initiator binding. The requirement for initiator binding might suffice to make methylation an essential function in V. cholerae. The structure of oriII suggests that it originated from a plasmid, but unlike plasmids, oriII makes use of methylation for once-per-cell-cycle replication, the norm for chromosomal but not plasmid replication

Functional identification of biological neural networks using reservoir adaptation for point processes

The complexity of biological neural networks does not allow to directly relate their biophysical properties to the dynamics of their electrical activity. We present a reservoir computing approach for functionally identifying a biological neural network, i.e. for building an artificial system that is functionally equivalent to the reference biological network. Employing feed-forward and recurrent networks with fading memory, i.e. reservoirs, we propose a point process based learning algorithm to train the internal parameters of the reservoir and the connectivity between the reservoir and the memoryless readout neurons. Specifically, the model is an Echo State Network (ESN) with leaky integrator neurons, whose individual leakage time constants are also adapted. The proposed ESN algorithm learns a predictive model of stimulus-response relations in in vitro and simulated networks, i.e. it models their response dynamics. Receiver Operating Characteristic (ROC) curve analysis indicates that these ESNs can imitate the response signal of a reference biological network. Reservoir adaptation improved the performance of an ESN over readout-only training methods in many cases. This also held for adaptive feed-forward reservoirs, which had no recurrent dynamics. We demonstrate the predictive power of these ESNs on various tasks with cultured and simulated biological neural networks

Molecular Characterization of a 21.4 Kilobase Antibiotic Resistance Plasmid from an α-Hemolytic Escherichia coli O108:H- Human Clinical Isolate

This study characterizes the 21.4 kilobase plasmid pECTm80 isolated from Escherichia coli strain 80, an α hemolytic human clinical diarrhoeal isolate (serotype O108:H-). DNA sequence analysis of pECTm80 revealed it belonged to incompatibility group X1, and contained plasmid partition and toxin-antitoxin systems, an R6K-like triple origin (ori) replication system, genes required for replication regulation, insertion sequences IS1R, ISEc37 and a truncated transposase gene (Tn3-like ΔtnpA) of the Tn3 family, and carried a class 2 integron. The class 2 integron of pECTm80 contains an intact cassette array dfrA1-sat2, encoding resistance to trimethoprim and streptothricin, and an aadA1 gene cassette truncated by the insertion of IS1R. The complex plasmid replication system includes α, β and γ origins of replication. Pairwise BLASTn comparison of pECTm80 with plasmid pE001 reveals a conserved plasmid backbone suggestive of a common ancestral lineage. Plasmid pECTm80 is of potential clinical importance, as it carries multiple genes to ensure its stable maintenance through successive bacterial cell divisions and multiple antibiotic resistance genes

Causal Measures of Structure and Plasticity in Simulated and Living Neural Networks

A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify “causal” relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal relationships among multiple measures is desired. These techniques can be especially useful when the interactions among those measures are highly complex, difficult to untangle, and maybe changing over time

Bone Marrow-Derived Progenitor Cells Augment Venous Remodeling in a Mouse Dorsal Skinfold Chamber Model

The delivery of bone marrow-derived cells (BMDCs) has been widely used to stimulate angiogenesis and arteriogenesis. We identified a progenitor-enriched subpopulation of BMDCs that is able to augment venular remodeling, a generally unexplored area in microvascular research. Two populations of BMDCs, whole bone marrow (WBM) and Lin−/Sca-1+ progenitor cells, were encapsulated in sodium alginate and delivered to a mouse dorsal skinfold chamber model. Upon observation that encapsulated Sca-1+ progenitor cells enhance venular remodeling, the cells and tissue were analyzed on structural and molecular levels. Venule walls were thickened and contained more nuclei after Sca-1+ progenitor cell delivery. In addition, progenitors expressed mRNA transcript levels of chemokine (C-X-C motif) ligand 2 (CXCL2) and interferon gamma (IFNγ) that are over 5-fold higher compared to WBM. Tissues that received progenitors expressed significantly higher protein levels of vascular endothelial growth factor (VEGF), monocyte chemotactic protein-1 (MCP-1), and platelet derived growth factor-BB (PDGF-BB) compared to tissues that received an alginate control construct. Nine days following cell delivery, tissue from progenitor recipients contained 39% more CD45+ leukocytes, suggesting that these cells may enhance venular remodeling through the modulation of the local immune environment. Results show that different BMDC populations elicit different microvascular responses. In this model, Sca-1+ progenitor cell-derived CXCL2 and IFNγ may mediate venule enlargement via modulation of the local inflammatory environment

Novel phages of healthy skin metaviromes from South Africa

Recent skin metagenomic studies have investigated the harbored viral diversity and its possible influence on healthy skin microbial populations, and tried to establish global patterns of skin-phage evolution. However, the detail associated with the phages that potentially play a role in skin health has not been investigated. While skin metagenome and -metavirome studies have indicated that the skin virome is highly site specific and shows marked interpersonal variation, they have not assessed the presence/absence of individual phages. Here, we took a semi-culture independent approach (metaviromic) to better understand the composition of phage communities on skin from South African study participants. Our data set adds over 130 new phage species of the skin to existing databases. We demonstrated that identical phages were present on different individuals and in different body sites, and we conducted a detailed analysis of the structural organization of these phages. We further found that a bacteriophage related to the Staphylococcus capitis phage Stb20 may be a common skin commensal virus potentially regulating its host and its activities on the ski

Beyond Statistical Significance: Implications of Network Structure on Neuronal Activity

It is a common and good practice in experimental sciences to assess the statistical significance of measured outcomes. For this, the probability of obtaining the actual results is estimated under the assumption of an appropriately chosen null-hypothesis. If this probability is smaller than some threshold, the results are deemed statistically significant and the researchers are content in having revealed, within their own experimental domain, a “surprising” anomaly, possibly indicative of a hitherto hidden fragment of the underlying “ground-truth”. What is often neglected, though, is the actual importance of these experimental outcomes for understanding the system under investigation. We illustrate this point by giving practical and intuitive examples from the field of systems neuroscience. Specifically, we use the notion of embeddedness to quantify the impact of a neuron's activity on its downstream neurons in the network. We show that the network response strongly depends on the embeddedness of stimulated neurons and that embeddedness is a key determinant of the importance of neuronal activity on local and downstream processing. We extrapolate these results to other fields in which networks are used as a theoretical framework

Central motor control failure in fibromyalgia: a surface electromyography study

<p>Abstract</p> <p>Background</p> <p>Fibromyalgia (FM) is characterised by diffuse musculoskeletal pain and stiffness at multiple sites, tender points in characteristic locations, and the frequent presence of symptoms such as fatigue. The aim of this study was to assess whether the myoelectrical manifestations of fatigue in patients affected by FM are central or peripheral in origin.</p> <p>Methods</p> <p>Eight female patients aged 55.6 ± 13.6 years (FM group) and eight healthy female volunteers aged 50.3 ± 9.3 years (MCG) were studied by means of non-invasive surface electromyography (s-EMG) involving a linear array of 16 electrodes placed on the skin overlying the biceps brachii muscle, with muscle fatigue being evoked by means of voluntary and involuntary (electrically elicited) contractions. Maximal voluntary contractions (MVCs), motor unit action potential conduction velocity distributions (mean ± SD and skewness), and the mean power frequency of the spectrum (MNF) were estimated in order to assess whether there were any significant differences between the two groups and contraction types.</p> <p>Results</p> <p>The motor pattern of recruitment during voluntary contractions was altered in the FM patients, who also showed fewer myoelectrical manifestations of fatigue (normalised conduction velocity rate of changes: -0.074 ± 0.052%/s in FM vs -0.196 ± 0.133%/s in MCG; normalised MNF rate of changes: -0.29 ± 0.16%/s in FM vs -0.66 ± 0.34%/s in MCG). Mean conduction velocity distribution and skewnesses values were higher (p < 0.01) in the FM group. There were no between-group differences in the results obtained from the electrically elicited contractions.</p> <p>Conclusion</p> <p>The apparent paradox of fewer myoelectrical manifestations of fatigue in FM is the electrophysiological expression of muscle remodelling in terms of the prevalence of slow conducting fatigue-resistant type I fibres. As the only between-group differences concerned voluntary contractions, they are probably more related to central motor control failure than muscle membrane alterations, which suggests pathological muscle fibre remodelling related to altered suprasegmental control.</p