Multiscale Bone Remodelling with Spatial P Systems

Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integration schemas. Spatial P systems, a variant of P systems in which a more geometric concept of space has been added, have several characteristics in common with Cellular Automata. We propose such a formalism as a basis to rephrase the Complex Automata multiscaling approach and, in this perspective, provide a 2-scale Spatial P system describing bone remodelling. The proposed model not only results to be highly faithful and expressive in a multiscale scenario, but also highlights the need of a deep and formal expressiveness study involving Complex Automata, Spatial P systems and other promising multiscale approaches, such as our shape-based one already resulted to be highly faithful.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

The closest elastic tensor of arbitrary symmetry to an elasticity tensor of lower symmetry

The closest tensors of higher symmetry classes are derived in explicit form for a given elasticity tensor of arbitrary symmetry. The mathematical problem is to minimize the elastic length or distance between the given tensor and the closest elasticity tensor of the specified symmetry. Solutions are presented for three distance functions, with particular attention to the Riemannian and log-Euclidean distances. These yield solutions that are invariant under inversion, i.e., the same whether elastic stiffness or compliance are considered. The Frobenius distance function, which corresponds to common notions of Euclidean length, is not invariant although it is simple to apply using projection operators. A complete description of the Euclidean projection method is presented. The three metrics are considered at a level of detail far greater than heretofore, as we develop the general framework to best fit a given set of moduli onto higher elastic symmetries. The procedures for finding the closest elasticity tensor are illustrated by application to a set of 21 moduli with no underlying symmetry.Comment: 48 pages, 1 figur

Inferring copy number and genotype in tumour exome data

Background: Using whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequencing, however is predominantly used for variant detection and infrequently utilised for detection of somatic copy number variation. Results: We propose a new method to infer copy number and genotypes using whole exome data from paired tumour/normal samples. Our algorithm uses two Hidden Markov Models to predict copy number and genotypes and computationally resolves polyploidy/aneuploidy, normal cell contamination and signal baseline shift. Our method makes explicit detection on chromosome arm level events, which are commonly found in tumour samples. The methods are combined into a package named ADTEx (Aberration Detection in Tumour Exome). We applied our algorithm to a cohort of 17 in-house generated and 18 TCGA paired ovarian cancer/normal exomes and evaluated the performance by comparing against the copy number variations and genotypes predicted using Affymetrix SNP 6.0 data of the same samples. Further, we carried out a comparison study to show that ADTEx outperformed its competitors in terms of precision and F-measure. Conclusions: Our proposed method, ADTEx, uses both depth of coverage ratios and B allele frequencies calculated from whole exome sequencing data, to predict copy number variations along with their genotypes. ADTEx is implemented as a user friendly software package using Python and R statistical language. Source code and sample data are freely available under GNU license (GPLv3) at http://adtex.sourceforge.net/

Conductivity and redox stability of new double perovskite oxide Sr 1.6 K 0.4 Fe 1+ x Mo 1− x O 6− δ (x= 0.2, 0.4, 0.6)

A series of new perovskite oxides Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) were synthesised by solid state reaction method. Synthesis of Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) was achieved above 700 °C in 5 % H2/Ar, albeit with the formation of impurity phases. Phase stability upon redox cycling was only observed for sample Sr1.6K0.4Fe1.4Mo0.6O6−δ. Redox cycling of Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) demonstrates a strong dependence on high temperature reduction to achieve high conductivities. After the initial reduction at 1200 °C in 5 %H2/Ar, then re-oxidation in air at 700 °C and further reduction at 700 °C in 5 %H2/Ar, the attained conductivities were between 0.1 and 58.4 % of the initial conductivity after reduction 1200 °C in 5 %H2/Ar depending on the composition. In the investigated new oxides, sample Sr1.6K0.4Fe1.4Mo0.6O6−δ is most redox stable also retains reasonably high electrical conductivity, ~70 S/cm after reduction at 1200 °C and 2–3 S/cm after redox cycling at 700 °C, indicating it is a potential anode for SOFCs

Recombinant leucine-rich repeat flightless-interacting protein-1 improves healing of acute wounds through its effects on proliferation inflammation and collagen deposition

Wound healing is an increasing clinical problem involving substantial morbidity, mortality, and rising health care costs. Leucine-rich repeat flightless-interacting protein-1 (LRRFIP-1) regulates toll-like receptor (TLR)-mediated inflammation, suggesting a potential role in the healing of wounds. We sought to determine the role of LRRFIP-1 in wound repair and whether the exogenous addition of recombinant LRRFIP-1 (rLRRFIP-1) affected healing responses. Using a model of full-thickness incisional acute wounds in BALB/c mice, we investigated the effect of wounding on LRRFIP-1 expression. The effect of rLRRFIP-1 on cellular proliferation, inflammation, and collagen deposition was also investigated. LRRFIP-1 was upregulated in response to wounding, was found to directly associate with flightless I (Flii), and significantly increased cellular proliferation both in vitro and in vivo. rLRRFIP-1 reduced Flii expression in wounds in vivo and resulted in significantly improved healing with a concurrent dampening of TLR4-mediated inflammation and improved collagen deposition. Additionally, decreased levels of TGF-β1 and increased levels of TGF-β3 were observed in rLRRFIP-1-treated wounds suggesting a possible antiscarring effect of rLRRFIP-1. Further studies are required to elucidate if the mechanisms behind LRRFIP-1 action in wound repair are independent of Flii. However, these results identify rLRRFIP-1 as a possible treatment modality for improved healing of acute wounds.Zlatko Kopecki, Natalie E. Stevens, Gink N. Yang, Elizabeth Melville and Allison J. Cowi

A metatranscriptomic approach to explore longitudinal tissue specimens from non-healing diabetes related foot ulcers

Cellular mechanisms and/or microbiological interactions which contribute to chronic diabetes related foot ulcers (DRFUs) were explored using serially collected tissue specimens from chronic DRFUs and control healthy foot skin. Total RNA was isolated for next-generation sequencing. We found differentially expressed genes (DEGs) and enriched hallmark gene ontology biological processes upregulated in chronic DRFUs which primarily functioned in the host immune response including: (i) Inflammatory response; (ii) TNF signalling via NFKB; (iii) IL6 JAK-STAT3 signalling; (iv) IL2 STAT5 signalling and (v) Reactive oxygen species. A temporal analysis identified RN7SL1 signal recognition protein and IGHG4 immunoglobulin protein coding genes as being the most upregulated genes after the onset of treatment. Testing relative temporal changes between healing and non-healing DRFUs identified progressive upregulation in healed wounds of CXCR5 and MS4A1 (CD20), both canonical markers of lymphocytes (follicular B cells/follicular T helper cells and B cells, respectively). Collectively, our RNA-seq data provides insights into chronic DRFU pathogenesis