Variability of the Spectral Energy Distribution of the Blazar S5 0716+714

The emission from blazars is known to be variable at all wavelengths. The flux variability is often accompanied by spectral changes. Spectral energy distribution (SED) changes must be associated with changes in the spectra of emitting electrons and/or the physical parameters of the jet. Meaningful modeling of blazar broadband spectra is required to understand the extreme conditions within the emission region. Not only is the broadband SED crucial, but also information about its variability is needed to understand how the highest states of emission occur and how they differ from the low states. This may help in discriminating between models. Here we present the results of our SED modeling of the blazar S5 0716+714 during various phases of its activity. The SEDs are classified into different bins depending on the optical brightness state of the source.Comment: 4 pages, 3 figures, contributed talk presented at the conference Multifrequency Variability of Blazars, Guangzhou, China, September 22-24, 2010. To appear in Journal of Astrophysics and Astronomy (JAA

Noise-based approximation to thermal spin-injection in Fe/GaAs

© 2017 Author(s). We analyze the prospects for thermal spin-injection from iron into gallium arsenide via the application of electrical noise. By estimating the applied effective temperature-equivalent gradients, we characterize the magnitude of any electrical part of the thermal spin-injection efficiency or the spin-dependent Seebeck effect. The magnitude of the non-local spin signal associated with this effect suggests that temperature differences on the order of ∼100 K would be needed for true thermal spin-injection experiments. The large size of the effective temperature gradients induced by the noise-based method means that even very small thermo-electric effects can be quantified

A theory for the impact of a wave breaking onto a permeable barrier with jet generation

We model a water wave impact onto a porous breakwater. The breakwater surface is modelled as a thin barrier composed of solid matter pierced by channels through which water can flow freely. The water in the wave is modelled as a finite-length volume of inviscid, incompressible fluid in quasi-one-dimensional flow during its impact and flow through a typical hole in the barrier. The fluid volume moves at normal incidence to the barrier. After the initial impact the wave water starts to slow down as it passes through holes in the barrier. Each hole is the source of a free jet along whose length the fluid velocity and width vary in such a way as to conserve volume and momentum at zero pressure. We find there are two types of flow, depending on the porosity, ß , of the barrier. If ß : 0 = ß < 0.5774 then the barrier is a strong impediment to the flow, in that the fluid velocity tends to zero as time tends to infinity. But if ß : 0.5774 = ß = 1 then the barrier only temporarily holds up the flow, and the decelerating wave water passes through in a finite time. We report results for the velocity and impact pressure due to the incident wave water, and for the evolving shape of the jet, with examples from both types of impact. We account for the impulse on the barrier and the conserved kinetic energy of the flow. Consideration of small ß gives insight into the sudden changes in flow and the high pressures that occur when a wave impacts a nearly impermeable seawall

The emerging structure of the Extended Evolutionary Synthesis: where does Evo-Devo fit in?

The Extended Evolutionary Synthesis (EES) debate is gaining ground in contemporary evolutionary biology. In parallel, a number of philosophical standpoints have emerged in an attempt to clarify what exactly is represented by the EES. For Massimo Pigliucci, we are in the wake of the newest instantiation of a persisting Kuhnian paradigm; in contrast, Telmo Pievani has contended that the transition to an EES could be best represented as a progressive reformation of a prior Lakatosian scientific research program, with the extension of its Neo-Darwinian core and the addition of a brand-new protective belt of assumptions and auxiliary hypotheses. Here, we argue that those philosophical vantage points are not the only ways to interpret what current proposals to ‘extend’ the Modern Synthesis-derived ‘standard evolutionary theory’ (SET) entail in terms of theoretical change in evolutionary biology. We specifically propose the image of the emergent EES as a vast network of models and interweaved representations that, instantiated in diverse practices, are connected and related in multiple ways. Under that assumption, the EES could be articulated around a paraconsistent network of evolutionary theories (including some elements of the SET), as well as models, practices and representation systems of contemporary evolutionary biology, with edges and nodes that change their position and centrality as a consequence of the co-construction and stabilization of facts and historical discussions revolving around the epistemic goals of this area of the life sciences. We then critically examine the purported structure of the EES—published by Laland and collaborators in 2015—in light of our own network-based proposal. Finally, we consider which epistemic units of Evo-Devo are present or still missing from the EES, in preparation for further analyses of the topic of explanatory integration in this conceptual framework

β2-adrenergic signalling promotes cell migration by upregulating expression of the metastasis-associated molecule LYPD3

Metastasis is associated with poor prognosis in breast cancer. Although some studies suggest beta-blockers increase survival by delaying metastasis, others have been discordant. This study provides both insights into the anomalous findings and identifies potential biomarkers that may be treatment targets. Cell line models of basal-type and oestrogen receptor-positive breast cancer were profiled for basal levels of adrenoceptor gene/protein expression, and β2-adrenoceptor mediated cell behaviour including migration, invasion, adhesion, and survival in response to adrenoceptor agonist/antagonist treatment. Protein profiling and histology identified biomarkers and drug targets. Baseline levels of adrenoceptor gene expression are higher in basal-type rather than oestrogen receptor-positive cancer cells. Norepinephrine (NE) treatment increased invasive capacity in all cell lines but did not increase proliferation/survival. Protein profiling revealed the upregulation of the pro-metastatic gene Ly6/PLAUR Domain-Containing Protein 3 (LYPD3) in norepinephrine-treated MDA-MB-468 cells. Histology confirmed selective LYPD3 expression in primary and metastatic breast tumour samples. These findings demonstrate that basal-type cancer cells show a more aggressive adrenoceptor-β2-activated phenotype in the resting and stimulated state, which is attenuated by adrenoceptor-β2 inhibition. This study also highlights the first association between ADRβ2 signalling and LYPD3; its knockdown significantly reduced the basal and norepinephrine-induced activity of MCF-7 cells in vitro. The regulation of ADRβ2 signalling by LYPD3 and its metastasis promoting activities, reveal LYPD3 as a promising therapeutic target in the treatment of breast and other cancers

Quadrupling Muscle Mass in Mice by Targeting TGF-ß Signaling Pathways

Myostatin is a transforming growth factor-ß family member that normally acts to limit skeletal muscle growth. Mice genetically engineered to lack myostatin activity have about twice the amount of muscle mass throughout the body, and similar effects are seen in cattle, sheep, dogs, and a human with naturally occurring loss-of-function mutations in the myostatin gene. Hence, there is considerable interest in developing agents capable of inhibiting myostatin activity for both agricultural and human therapeutic applications. We previously showed that the myostatin binding protein, follistatin, can induce dramatic increases in muscle mass when overexpressed as a transgene in mice. In order to determine whether this effect of follistatin results solely from inhibition of myostatin activity, I analyzed the effect of this transgene in myostatin-null mice. Mstn−/− mice carrying a follistatin transgene had about four times the muscle mass of wild type mice, demonstrating the existence of other regulators of muscle mass with similar activity to myostatin. The greatest effect on muscle mass was observed in offspring of mothers homozygous for the Mstn mutation, raising the possibility that either myostatin itself or a downstream regulator may normally be transferred from the maternal to fetal circulations. These findings demonstrate that the capacity for increasing muscle growth by manipulating TGF-ß signaling pathways is much more extensive than previously appreciated and suggest that muscle mass may be controlled at least in part by a systemic mode of action of myostatin

Improving population-level refractive error monitoring via mixture distributions

Introduction: Sampling and describing the distribution of refractive error in populations is critical to understanding eye care needs, refractive differences between groups and factors affecting refractive development. We investigated the ability of mixture models to describe refractive error distributions. Methods: We used key informants to identify raw refractive error datasets and a systematic search strategy to identify published binned datasets of community-representative refractive error. Mixture models combine various component distributions via weighting to describe an observed distribution. We modelled raw refractive error data with a single-Gaussian (normal) distribution, mixtures of two to six Gaussian distributions and an additive model of an exponential and Gaussian (ex-Gaussian) distribution. We tested the relative fitting accuracy of each method via Bayesian Information Criterion (BIC) and then compared the ability of selected models to predict the observed prevalence of refractive error across a range of cut-points for both the raw and binned refractive data. Results: We obtained large raw refractive error datasets from the United States and Korea. The ability of our models to fit the data improved significantly from a single-Gaussian to a two-Gaussian-component additive model and then remained stable with ≥3-Gaussian-component mixture models. Means and standard deviations for BIC relative to 1 for the single-Gaussian model, where lower is better, were 0.89 ± 0.05, 0.88 ± 0.06, 0.89 ± 0.06, 0.89 ± 0.06 and 0.90 ± 0.06 for two-, three-, four-, five- and six-Gaussian-component models, respectively, tested across US and Korean raw data grouped by age decade. Means and standard deviations for the difference between observed and model-based estimates of refractive error prevalence across a range of cut-points for the raw data were −3.0% ± 6.3, 0.5% ± 1.9, 0.6% ± 1.5 and −1.8% ± 4.0 for one-, two- and three-Gaussian-component and ex-Gaussian models, respectively. Conclusions: Mixture models appear able to describe the population distribution of refractive error accurately, offering significant advantages over commonly quoted simple summary statistics such as mean, standard deviation and prevalence

Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science

Abstract Background Many interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts. Methods We used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts. Results The CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct. Conclusion The CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.http://deepblue.lib.umich.edu/bitstream/2027.42/78272/1/1748-5908-4-50.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/2/1748-5908-4-50-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/3/1748-5908-4-50-S3.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/4/1748-5908-4-50-S4.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/5/1748-5908-4-50.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78272/6/1748-5908-4-50-S2.PDFPeer Reviewe

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u

A metabolite-derived protein modification integrates glycolysis with KEAP1-NRF2 signalling.

Mechanisms that integrate the metabolic state of a cell with regulatory pathways are necessary to maintain cellular homeostasis. Endogenous, intrinsically reactive metabolites can form functional, covalent modifications on proteins without the aid of enzymes1,2, and regulate cellular functions such as metabolism3-5 and transcription6. An important 'sensor' protein that captures specific metabolic information and transforms it into an appropriate response is KEAP1, which contains reactive cysteine residues that collectively act as an electrophile sensor tuned to respond to reactive species resulting from endogenous and xenobiotic molecules. Covalent modification of KEAP1 results in reduced ubiquitination and the accumulation of NRF27,8, which then initiates the transcription of cytoprotective genes at antioxidant-response element loci. Here we identify a small-molecule inhibitor of the glycolytic enzyme PGK1, and reveal a direct link between glycolysis and NRF2 signalling. Inhibition of PGK1 results in accumulation of the reactive metabolite methylglyoxal, which selectively modifies KEAP1 to form a methylimidazole crosslink between proximal cysteine and arginine residues (MICA). This posttranslational modification results in the dimerization of KEAP1, the accumulation of NRF2 and activation of the NRF2 transcriptional program. These results demonstrate the existence of direct inter-pathway communication between glycolysis and the KEAP1-NRF2 transcriptional axis, provide insight into the metabolic regulation of the cellular stress response, and suggest a therapeutic strategy for controlling the cytoprotective antioxidant response in several human diseases