Cartilage stem/progenitor cells are activated in osteoarthritis via interleukin-1β/nerve growth factor signaling

Introduction: Interleukin-1β (IL-1β) and nerve growth factor (NGF) are key regulators in the pathogenesis of inflammatory arthritis; specifically, IL-1β is involved in tissue degeneration and NGF is involved in joint pain. However, the cellular and molecular interactions between IL-1β and NGF in articular cartilage are not known. Cartilage stem/progenitor cells (CSPCs) have recently been identified in osteoarthritic (OA) cartilage on the basis of their migratory properties. Here we hypothesize that IL-1β/NGF signaling is involved in OA cartilage degeneration by targeting CSPCs. Method: NGF and NGF receptor (NGFR: TrkA and p75NTR) expression in healthy and OA human articular cartilage and isolated chondrocytes was determined by immunostaining, qRT-PCR, flow cytometry and western blot. Articular cartilage derived stem/progenitor cells were collected and identified by stem/progenitor cell characteristics. 3D-cultured CSPC pellets and cartilage explants were treated with NGF and NGF neutralizing antibody, and extracellular matrix changes were examined by sulfated glycosaminoglycan (GAG) release and MMP expression and activity. Results: Expression of NGF, TrkA and p75NTR was found to be elevated in human OA cartilage. Cellular changes upon IL-1β and/or NGF treatment were then examined. NGF mRNA and NGFR proteins levels were upregulated in cultured chondrocytes exposed to IL-1β. NGF was chemotactic for cells isolated from OA cartilage. Cells isolated on the basis of their chemotactic migration towards NGF demonstrated stem/progenitor cell characteristics, including colony-forming ability, multi-lineage differentiation potential, and stem cell surface markers. The effects of NGF perturbation in cartilage explants and 3D-cultured CSPCs were next analyzed. NGF treatment resulted in extracellular matrix catabolism indicated by increased sGAG release and MMP expression and activity; conversely, treatment with NGF neutralizing antibody inhibited increased MMP levels, and enhanced tissue inhibitor of matrix metalloprotease-1 (TIMP1) expression in OA cartilage explants. NGF blockade with neutralizing antibody also affected cartilage matrix remodeling in 3D-CSPC pellet cultures. Conclusion: Our results strongly suggest that NGF signaling is a contributing factor in articular cartilage degeneration in OA, which likely targets a specific subpopulation of progenitor cells, the CSPCs, affecting their migratory and matrix remodeling activities. These findings provide novel cellular/signaling therapeutic targets in osteoarthritic cartilage

Baryon chiral perturbation theory with virtual photons and leptons

We construct the general pion-nucleon SU(2) Lagrangian including both virtual photons and leptons for relativistic baryon chiral perturbation theory up to fourth order. We include the light leptons as explicit dynamical degrees of freedom by introducing new building blocks which represent these leptons.Comment: 11 page

On the Inability of Markov Models to Capture Criticality in Human Mobility

We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian nature of mobility was used to establish a theoretical upper bound on the predictability of human mobility (expressed as a minimum error probability limit), based on temporally correlated entropy. Since its inception, this bound has been widely used and empirically validated using Markov chains. We show that recurrent-neural architectures can achieve significantly higher predictability, surpassing this widely used upper bound. In order to explain this anomaly, we shed light on several underlying assumptions in previous research works that has resulted in this bias. By evaluating the mobility predictability on real-world datasets, we show that human mobility exhibits scale-invariant long-range correlations, bearing similarity to a power-law decay. This is in contrast to the initial assumption that human mobility follows an exponential decay. This assumption of exponential decay coupled with Lempel-Ziv compression in computing Fano's inequality has led to an inaccurate estimation of the predictability upper bound. We show that this approach inflates the entropy, consequently lowering the upper bound on human mobility predictability. We finally highlight that this approach tends to overlook long-range correlations in human mobility. This explains why recurrent-neural architectures that are designed to handle long-range structural correlations surpass the previously computed upper bound on mobility predictability

Recovery and evolutionary analysis of complete integron gene cassette arrays from Vibrio

BACKGROUND: Integrons are genetic elements capable of the acquisition, rearrangement and expression of genes contained in gene cassettes. Gene cassettes generally consist of a promoterless gene associated with a recombination site known as a 59-base element (59-be). Multiple insertion events can lead to the assembly of large integron-associated cassette arrays. The most striking examples are found in Vibrio, where such cassette arrays are widespread and can range from 30 kb to 150 kb. Besides those found in completely sequenced genomes, no such array has yet been recovered in its entirety. We describe an approach to systematically isolate, sequence and annotate large integron gene cassette arrays from bacterial strains. RESULTS: The complete Vibrio sp. DAT722 integron cassette array was determined through the streamlined approach described here. To place it in an evolutionary context, we compare the DAT722 array to known vibrio arrays and performed phylogenetic analyses for all of its components (integrase, 59-be sites, gene cassette encoded genes). It differs extensively in terms of genomic context as well as gene cassette content and organization. The phylogenetic tree of the 59-be sites collectively found in the Vibrio gene cassette pool suggests frequent transfer of cassettes within and between Vibrio species, with slower transfer rates between more phylogenetically distant relatives. We also identify multiple cases where non-integron chromosomal genes seem to have been assembled into gene cassettes and others where cassettes have been inserted into chromosomal locations outside integrons. CONCLUSION: Our systematic approach greatly facilitates the isolation and annotation of large integrons gene cassette arrays. Comparative analysis of the Vibrio sp. DAT722 integron obtained through this approach to those found in other vibrios confirms the role of this genetic element in promoting lateral gene transfer and suggests a high rate of gene gain/loss relative to most other loci on vibrio chromosomes. We identify a relationship between the phylogenetic distance separating two species and the rate at which they exchange gene cassettes, interactions between the non-mobile portion of bacterial genomes and the vibrio gene cassette pool as well as intragenomic translocation events of integrons in vibrios

MINE: Module Identification in Networks

<p>Abstract</p> <p>Background</p> <p>Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.</p> <p>Results</p> <p>MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the <it>C. elegans </it>protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties.</p> <p>Conclusions</p> <p>MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both <it>S. cerevisiae </it>and <it>C. elegans</it>.</p

Three-dimensionally Ordered Macroporous Structure Enabled Nanothermite Membrane of Mn2O3/Al

Mn2O3 has been selected to realize nanothermite membrane for the first time in the literature. Mn2O3/Al nanothermite has been synthesized by magnetron sputtering a layer of Al film onto three-dimensionally ordered macroporous (3DOM) Mn2O3 skeleton. The energy release is significantly enhanced owing to the unusual 3DOM structure, which ensures Al and Mn2O3 to integrate compactly in nanoscale and greatly increase effective contact area. The morphology and DSC curve of the nanothermite membrane have been investigated at various aluminizing times. At the optimized aluminizing time of 30 min, energy release reaches a maximum of 2.09 kJ∙g−1, where the Al layer thickness plays a decisive role in the total energy release. This method possesses advantages of high compatibility with MEMS and can be applied to other nanothermite systems easily, which will make great contribution to little-known nanothermite research

Perpendicular local magnetization under voltage control in Ni films on ferroelectric BaTiO₃ substrates.

High-resolution magnetoelectric imaging is used to demonstrate electrical control of the perpendicular local magnetization associated with 125 nm-wide magnetic stripe domains in 100-nm-thick Ni films. This magnetoelectric coupling is achieved in zero magnetic field using strain from ferroelectric BaTiO3 substrates to control perpendicular anisotropy imposed by the growth stress. These findings may be exploited for perpendicular recording in nanopatterned hybrid media.This work was funded by Isaac Newton Trust grants 10.26(u) and 11.35 (u), UK EPSRC grant EP/G031509/1, a Herchel Smith Fellowship (X.M.), the Spanish MEC Ramón y Cajal programme (X.M.), and the Royal Society (X.M.). The authors thank Luis Hueso and Raffaele Pellicelli for discussions.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1002/adma.201404799/abstract

Chacterization of CU tube filled with Al alloy foam by means of X-ray computer tomography

Copper tubes filled with aluminium foams were prepared by directly foaming metal powder compacts inside them. Compressive behaviour and foam-shell interface, that characterizes mechanical properties of reinforced tubes, were investigated by means of variable focus X-ray computer tomography. Compression tests were performed on empty and filled samples at increasing deformation steps: at each stage the samples were observed by tomography. A geometric evaluation of porosity on 2D sections was performed by calculating, for each pore, its area, equivalent diameter and circularity

Theories for influencer identification in complex networks

In social and biological systems, the structural heterogeneity of interaction networks gives rise to the emergence of a small set of influential nodes, or influencers, in a series of dynamical processes. Although much smaller than the entire network, these influencers were observed to be able to shape the collective dynamics of large populations in different contexts. As such, the successful identification of influencers should have profound implications in various real-world spreading dynamics such as viral marketing, epidemic outbreaks and cascading failure. In this chapter, we first summarize the centrality-based approach in finding single influencers in complex networks, and then discuss the more complicated problem of locating multiple influencers from a collective point of view. Progress rooted in collective influence theory, belief-propagation and computer science will be presented. Finally, we present some applications of influencer identification in diverse real-world systems, including online social platforms, scientific publication, brain networks and socioeconomic systems.Comment: 24 pages, 6 figure

Molecular mechanisms of drug resistance in natural Leishmania populations vary with genetic background

The evolution of drug-resistance in pathogens is a major global health threat. Elucidating the molecular basis of pathogen drug-resistance has been the focus of many studies but rarely is it known whether a drug-resistance mechanism identified is universal for the studied pathogen; it has seldom been clarified whether drug-resistance mechanisms vary with the pathogen's genotype. Nevertheless this is of critical importance in gaining an understanding of the complexity of this global threat and in underpinning epidemiological surveillance of pathogen drug resistance in the field. This study aimed to assess the molecular and phenotypic heterogeneity that emerges in natural parasite populations under drug treatment pressure. We studied lines of the protozoan parasite Leishmania (L.) donovani with differential susceptibility to antimonial drugs; the lines being derived from clinical isolates belonging to two distinct genetic populations that circulate in the leishmaniasis endemic region of Nepal. Parasite pathways known to be affected by antimonial drugs were characterised on five experimental levels in the lines of the two populations. Characterisation of DNA sequence, gene expression, protein expression and thiol levels revealed a number of molecular features that mark antimonial-resistant parasites in only one of the two populations studied. A final series of in vitro stress phenotyping experiments confirmed this heterogeneity amongst drug-resistant parasites from the two populations. These data provide evidence that the molecular changes associated with antimonial-resistance in natural Leishmania populations depend on the genetic background of the Leishmania population, which has resulted in a divergent set of resistance markers in the Leishmania populations. This heterogeneity of parasite adaptations provides severe challenges for the control of drug resistance in the field and the design of molecular surveillance tools for widespread applicability