Platinum deposition on functionalised graphene for corrosion resistant oxygen reduction electrodes

Graphene-related materials are promising supports for electrocatalysts due to their stability and high surface area. Their innate surface chemistries can be controlled and tuned via functionalisation to improve the stability of both the carbon support and the metal catalyst. Functionalised graphenes were prepared using either aryl diazonium functionalisation or non-destructive chemical reduction, to provide groups adapted for platinum deposition. XPS and TGA-MS measurements confirmed the presence of polyethyleneglycol and sulfur-containing functional groups, and provided consistent values for the extent of the reactions. The deposited platinum nanoparticles obtained were consistently around 2 nm via reductive chemistry and around 4 nm via the diazonium route. Although these graphene-supported electrocatalysts provided a lower electrochemical surface area (ECSA), functionalised samples showed enhanced specific activity compared to a commercial platinum/carbon black system. Accelerated stress testing (AST) showed improved durability for the functionalised graphenes compared to the non-functionalised materials, attributed to edge passivation and catalyst particle anchoring

Hierarchy measure for complex networks

Nature, technology and society are full of complexity arising from the intricate web of the interactions among the units of the related systems (e.g., proteins, computers, people). Consequently, one of the most successful recent approaches to capturing the fundamental features of the structure and dynamics of complex systems has been the investigation of the networks associated with the above units (nodes) together with their relations (edges). Most complex systems have an inherently hierarchical organization and, correspondingly, the networks behind them also exhibit hierarchical features. Indeed, several papers have been devoted to describing this essential aspect of networks, however, without resulting in a widely accepted, converging concept concerning the quantitative characterization of the level of their hierarchy. Here we develop an approach and propose a quantity (measure) which is simple enough to be widely applicable, reveals a number of universal features of the organization of real-world networks and, as we demonstrate, is capable of capturing the essential features of the structure and the degree of hierarchy in a complex network. The measure we introduce is based on a generalization of the m-reach centrality, which we first extend to directed/partially directed graphs. Then, we define the global reaching centrality (GRC), which is the difference between the maximum and the average value of the generalized reach centralities over the network. We investigate the behavior of the GRC considering both a synthetic model with an adjustable level of hierarchy and real networks. Results for real networks show that our hierarchy measure is related to the controllability of the given system. We also propose a visualization procedure for large complex networks that can be used to obtain an overall qualitative picture about the nature of their hierarchical structure.Comment: 29 pages, 9 figures, 4 table

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

Carbon foams from emulsion-templated reduced graphene oxide polymer composites: electrodes for supercapacitor devices

Amphiphilic reduced graphene oxide (rGO) is an efficient emulsifier for water-in-divinylbenzene (DVB) high internal phase emulsions. The polymerisation of the continuous DVB phase of the emulsion template and removal of water results in macroporous poly(divinylbenzene) (polyDVB). Subsequent pyrolysis of the poly(DVB) macroporous polymers yields ‘all-carbon’ foams containing micropores alongside emulsion templated-macropores, resulting in hierarchical porosity. The synthesis of carbon foams, or ‘carboHIPEs’, from poly(DVB) produced by polymerisation of rGO stabilised HIPEs provides both exceptionally high surface areas (up to 1820 m2 g−1) and excellent electrical conductivities (up to 285 S m−1), competing with the highest figures reported for carboHIPEs. The use of a 2D carbon emulsifier results in the elimination of post-carbonisation treatments to remove standard inorganic particulate emulsifiers, such as silica particles. It is demonstrated that rGO containing carboHIPEs are good candidates for supercapacitor electrodes where carboHIPEs derived from more conventional polymerised silica-stabilised HIPEs perform poorly. Supercapacitor devices featured a room-temperature ionic liquid electrolyte and electrodes derived from either rGO- or silica-containing poly(DVB)HIPEs demonstrated a maximum specific capacitance of 26 F g−1, an energy density of 5.2 W h kg−1 and a power density of 280 W kg−1

Genomic analysis of the function of the transcription factor gata3 during development of the Mammalian inner ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKB beta, a dramatic increase in Akt1/PKB alpha protein and relocation of Akt1/PKB alpha from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27(kip1), a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain

Decreases in Community Viral Load Are Accompanied by Reductions in New HIV Infections in San Francisco

BACKGROUND: At the individual level, higher HIV viral load predicts sexual transmission risk. We evaluated San Francisco's community viral load (CVL) as a population level marker of HIV transmission risk. We hypothesized that the decrease in CVL in San Francisco from 2004-2008, corresponding with increased rates of HIV testing, antiretroviral therapy (ART) coverage and effectiveness, and population-level virologic suppression, would be associated with a reduction in new HIV infections. METHODOLOGY/PRINCIPAL FINDINGS: We used San Francisco's HIV/AIDS surveillance system to examine the trends in CVL. Mean CVL was calculated as the mean of the most recent viral load of all reported HIV-positive individuals in a particular community. Total CVL was defined as the sum of the most recent viral loads of all HIV-positive individuals in a particular community. We used Poisson models with robust standard errors to assess the relationships between the mean and total CVL and the primary outcome: annual numbers of newly diagnosed HIV cases. Both mean and total CVL decreased from 2004-2008 and were accompanied by decreases in new HIV diagnoses from 798 (2004) to 434 (2008). The mean (p = 0.003) and total CVL (p = 0.002) were significantly associated with new HIV cases from 2004-2008. CONCLUSIONS/SIGNIFICANCE: Reductions in CVL are associated with decreased HIV infections. Results suggest that wide-scale ART could reduce HIV transmission at the population level. Because CVL is temporally upstream of new HIV infections, jurisdictions should consider adding CVL to routine HIV surveillance to track the epidemic, allocate resources, and to evaluate the effectiveness of HIV prevention and treatment efforts

Immunological mechanism of action and clinical profile of disease-modifying treatments in multiple sclerosis.

Multiple sclerosis (MS) is a life-long, potentially debilitating disease of the central nervous system (CNS). MS is considered to be an immune-mediated disease, and the presence of autoreactive peripheral lymphocytes in CNS compartments is believed to be critical in the process of demyelination and tissue damage in MS. Although MS is not currently a curable disease, several disease-modifying therapies (DMTs) are now available, or are in development. These DMTs are all thought to primarily suppress autoimmune activity within the CNS. Each therapy has its own mechanism of action (MoA) and, as a consequence, each has a different efficacy and safety profile. Neurologists can now select therapies on a more individual, patient-tailored basis, with the aim of maximizing potential for long-term efficacy without interruptions in treatment. The MoA and clinical profile of MS therapies are important considerations when making that choice or when switching therapies due to suboptimal disease response. This article therefore reviews the known and putative immunological MoAs alongside a summary of the clinical profile of therapies approved for relapsing forms of MS, and those in late-stage development, based on published data from pivotal randomized, controlled trials

The predictability of ecological stability in a noisy world

Random environmental variation, or stochasticity, is a key determinant of ecological dynamics. While we have some appreciation of how environmental stochasticity can moderate the variability and persistence of communities, we know little about its implications for the nature and predictability of ecological responses to large perturbations. Here, we show that shifts in the temporal autocorrelation (colour) of environmental noise provoke trade-offs in ecological stability across a wide range of different food-web structures by stabilizing dynamics in some dimensions, while simultaneously destabilizing them in others. Specifically, increasingly positive autocorrelation (reddening) of environmental noise increases resilience by hastening the recovery of food webs following a large perturbation, but reduces their resistance to perturbation and increases their temporal variability (reduces biomass stability). In contrast, all stability dimensions become less predictable, showing increased variability around the mean response, as environmental noise reddens. Moreover, we found environmental reddening to be a considerably more important determinant of stability than intrinsic food-web characteristics. These findings reveal the fundamental and dominant role played by environmental stochasticity in determining the dynamics and stability of ecosystems, and extend our understanding of how the multiple dimensions of stability relate to each other beyond simple white noise environments