Developing affordable and accessible pro‐angiogenic wound dressings; incorporation of 2 deoxy D‐ribose (2dDR) into cotton fibres and wax‐coated cotton fibres

The absorption capacity of cotton dressings is a critical factor in their widespread use where they help absorb wound exudate. Cotton wax dressings, in contrast, are used for wounds where care is taken to avoid adhesion of dressings to sensitive wounds such as burn injuries. Accordingly, we explored the loading of 2‐deoxy‐D‐ribose (2dDR), a small sugar, which stimulates angiogenesis and wound healing in normal and diabetic rats, into both types of dressings and measured the release of it over several days. The results showed that approximately 90% of 2dDR was released between 3 and 5 days when loaded into cotton dressings. For wax‐coated cotton dressings, several methods of loading of 2dDR were explored. A strategy similar to the commercial wax coating methodology was found the best protocol which provided a sustained release over 5 days. Cytotoxicity analysis of 2dDR loaded cotton dressing showed that the dressing stimulated metabolic activity of fibroblasts over 7 days confirming the non‐toxic nature of this sugar‐loaded dressings. The results of the chick chorioallantoic membrane (CAM) assay demonstrated a strong angiogenic response to both 2dDR loaded cotton dressing and to 2dDR loaded cotton wax dressings. Both dressings were found to increase the number of newly formed blood vessels significantly when observed macroscopically and histologically. We conclude this study offers a simple approach to developing affordable wound dressings as both have the potential to be evaluated as pro‐active dressings to stimulate wound healing in wounds where management of exudate or prevention of adherence to the wounds are clinical requirements

Graph Metrics for Temporal Networks

Temporal networks, i.e., networks in which the interactions among a set of elementary units change over time, can be modelled in terms of time-varying graphs, which are time-ordered sequences of graphs over a set of nodes. In such graphs, the concepts of node adjacency and reachability crucially depend on the exact temporal ordering of the links. Consequently, all the concepts and metrics proposed and used for the characterisation of static complex networks have to be redefined or appropriately extended to time-varying graphs, in order to take into account the effects of time ordering on causality. In this chapter we discuss how to represent temporal networks and we review the definitions of walks, paths, connectedness and connected components valid for graphs in which the links fluctuate over time. We then focus on temporal node-node distance, and we discuss how to characterise link persistence and the temporal small-world behaviour in this class of networks. Finally, we discuss the extension of classic centrality measures, including closeness, betweenness and spectral centrality, to the case of time-varying graphs, and we review the work on temporal motifs analysis and the definition of modularity for temporal graphs.Comment: 26 pages, 5 figures, Chapter in Temporal Networks (Petter Holme and Jari Saram\"aki editors). Springer. Berlin, Heidelberg 201

The physics of spreading processes in multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent "multilayer" approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.Comment: 25 pages, 4 figure

Longitudinal transcriptomic and genetic landscape of radiotherapy response in canine melanoma

Canine malignant melanoma (MM) is a highly aggressive tumour with a low survival rate and represents an ideal spontaneous model for the human counterpart. Considerable progress has been recently obtained, but the therapeutic success for canine melanoma is still challenging. Little is known about the mechanisms beyond pathogenesis and melanoma development, and the molecular response to radiotherapy has never been explored before. A faster and deeper understanding of cancer mutational processes and developing mechanisms are now possible through next generation sequencing technologies. In this study, we matched whole exome and transcriptome sequencing in four dogs affected by MM at diagnosis and at disease progression to identify possible genetic mechanisms associated with therapy failure. According to previous studies, a genetic similarity between canine MM and its human counterpart was observed. Several somatic mutations were functionally related to MAPK, PI3K/AKT and p53 signalling pathways, but located in genes other than BRAF, RAS and KIT. At disease progression, several mutations were related to therapy effects. Natural killer cell-mediated cytotoxicity and several immune-system-related pathways resulted activated opening a new scenario on the microenvironment in this tumour. In conclusion, this study suggests a potential role of the immune system associated to radiotherapy in canine melanoma, but a larger sample size associated with functional studies are needed

Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity - i.e. the tendency to form two separate subgraphs - than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network

Historical separation and present-day structure of common dolphinfish (Coryphaena hippurus) populations in the Atlantic Ocean and Mediterranean Sea

The common dolphinfish (Coryphaena hippurus) is an epipelagic, mid-trophic level, highly migratory species distributed throughout the world’s tropical and subtropical oceans in waters greater than 20C. Life-history variables, migratory behaviour, and genetic markers have been used to define major stocks in the central Atlantic Ocean and Mediterranean Sea. Here, we used the mitochondrial DNA gene NADH subunit 1 (688 bp) to test for differences between population groups. A total of 103 haplotypes were detected among 203 fish. Gene diversities in samples were large and similar among populations (mean h ¼ 0.932; range 0.894–0.987), but nucleotide diversities varied widely among samples (range p ¼ 0.004–0.034) and appear to reflect population histories. Principal component analysis revealed two large populations groups, and the analysis of molecular variation and pairwise values of UST resolved population structure within these groups. Populations in the eastern Atlantic and Mediterranean showed the largest amounts of divergence from one another (UCT ¼ 0.331). Adult movement and biophysical barriers to larval dispersal may explain contemporary differences between stocks, but the divergent populations in the Mediterranean Sea are likely due to isolations by cold temperature barriers during Pleistocene glaciations. The geographically large stock groupings require international cooperation in the harvest management and conservation of local dolphinfish populations

BioNoMo. The biodiversity network of Mozambique

Mozambique biodiversity richness plays a pivotal role to achieve the sustainable development of the country. However, Mozambique's flora and fauna diversity still remains broadly unknown and poorly documented. To properly address this issue, one of the strategic needs expressed by the Mozambican institutions was the development of a national biodiversity data repository to aggregate, manage and make data available online. Thus, a sustainable infrastructure for the standardisation, aggregation, organisation and sharing of primary biodiversity data was developed. Named the "Biodiversity Network of Mozambique" (BioNoMo), such a tool serves as a national repository of biodiversity data and aggregates occurrence records of plants and animals in the country obtained from floristic and faunistic observations and from specimens of biological collections. In this paper, the authors present the structure and data of BioNoMO, including software details, the process of data gathering and aggregation, the taxonomic coverage and the WebGIS development. Currently, aggregating a total of 273,172 records, including 85,092 occurrence records of plants and 188,080 occurrence records of animals (41.2% terrestrial, 58,8% aquatic), BioNoMo represents the largest aggregator of primary biodiversity data in Mozambique and it is planned to grow further by aggregating new datasets

Opinion formation in multiplex networks with general initial distributions

We study opinion dynamics over multiplex networks where agents interact with bounded confidence. Namely, two neighbouring individuals exchange opinions and compromise if their opinions do not differ by more than a given threshold. In literature, agents are generally assumed to have a homogeneous confidence bound. Here, we study analytically and numerically opinion evolution over structured networks characterised by multiple layers with respective confidence thresholds and general initial opinion distributions. Through rigorous probability analysis, we show analytically the critical thresholds at which a phase transition takes place in the long-term consensus behaviour, over multiplex networks with some regularity conditions. Our results reveal the quantitative relation between the critical threshold and initial distribution. Further, our numerical simulations illustrate the consensus behaviour of the agents in network topologies including lattices and, small-world and scale-free networks, as well as for structure-dependent convergence parameters accommodating node heterogeneity. We find that the critical thresholds for consensus tend to agree with the predicted upper bounds in Theorems 4 and 5 in this paper. Finally, our results indicate that multiplexity hinders consensus formation when the initial opinion configuration is within a bounded range and, provide insight into information diffusion and social dynamics in multiplex systems modeled by networks

Weighted temporal event graphs

The times of temporal-network events and their correlations contain information on the function of the network and they influence dynamical processes taking place on it. To extract information out of correlated event times, techniques such as the analysis of temporal motifs have been developed. We discuss a recently-introduced, more general framework that maps temporal-network structure into static graphs while retaining information on time-respecting paths and the time differences between their consequent events. This framework builds on weighted temporal event graphs: directed, acyclic graphs (DAGs) that contain a superposition of all temporal paths. We introduce the reader to the temporal event-graph mapping and associated computational methods and illustrate its use by applying the framework to temporal-network percolation