A response surface model to predict and experimentally tune the chemical, magnetic and optoelectronic properties of oxygen-doped boron nitride

Porous boron nitride (BN), a combination of hexagonal, turbostratic and amorphous BN, has emerged as a new platform photocatalyst. Yet, this material lacks photoactivity under visible light. Theoretical studies predict that tuning the oxygen content in oxygen-doped BN (BNO) could lower the band gap. This is yet to be verified experimentally. We present herein a systematic experimental route to simultaneously tune BNO's chemical, magnetic and optoelectronic properties using a multivariate synthesis parameter space. We report deep visible range band gaps (1.50–2.90 eV) and tuning of the oxygen (2–14 at.%) and specific paramagnetic OB3 contents (7–294 a.u. g−1). Through designing a response surface via a design of experiments (DOE) process, we have identified synthesis parameters influencing BNO's chemical, magnetic and optoelectronic properties. We also present model prediction equations relating these properties to the synthesis parameter space that we have validated experimentally. This methodology can help tailor and optimise BN materials for heterogeneous photocatalysis

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy

Substrate cycling between de novo lipogenesis and lipid oxidation: a thermogenic mechanism against skeletal muscle lipotoxicity and glucolipotoxicity

Life is a combustion, but how the major fuel substrates that sustain human life compete and interact with each other for combustion has been at the epicenter of research into the pathogenesis of insulin resistance ever since Randle proposed a 'glucose-fatty acid cycle' in 1963. Since then, several features of a mutual interaction that is characterized by both reciprocality and dependency between glucose and lipid metabolism have been unravelled, namely: 1. the inhibitory effects of elevated concentrations of fatty acids on glucose oxidation (via inactivation of mitochondrial pyruvate dehydrogenase or via desensitization of insulin-mediated glucose transport), 2. the inhibitory effects of elevated concentrations of glucose on fatty acid oxidation (via malonyl-CoA regulation of fatty acid entry into the mitochondria), and more recently 3. the stimulatory effects of elevated concentrations of glucose on de novo lipogenesis, that is, synthesis of lipids from glucose (via SREBP1c regulation of glycolytic and lipogenic enzymes). This paper first revisits the physiological significance of these mutual interactions between glucose and lipids in skeletal muscle pertaining to both blood glucose and intramyocellular lipid homeostasis. It then concentrates upon emerging evidence, from calorimetric studies investigating the direct effect of leptin on thermogenesis in intact skeletal muscle, of yet another feature of the mutual interaction between glucose and lipid oxidation: that of substrate cycling between de novo lipogenesis and lipid oxidation. It is proposed that this energy-dissipating substrate cycling that links glucose and lipid metabolism to thermogenesis could function as a 'fine-tuning' mechanism that regulates intramyocellular lipid homeostasis, and hence contributes to the protection of skeletal muscle against lipotoxicity

Simulation of Receptivity and Induced Transition From Discrete Roughness Elements

The final publication is available at Springer via http://dx.doi.org/10.1007/s10494-015-9636-yDordrecht Simulations have been carried out to predict the receptivity and growth of crossflow vortices created by Discrete Roughness Elements (DREs) The final transition to turbulence has also been examined, including the effect of DRE spacing and freestream turbulence. Measurements by Hunt and Saric (2011) of perturbation mode shape at various locations were used to validate the code in particular for the receptivity region. The WALE sub-grid stress (SGS) model was adopted for application to transitional flows, since it allows the SGS viscosity to vanish in laminar regions and in the innermost region of the boundary layer when transition begins. Simulations were carried out for two spanwise wavelengths: λ= 12mm (critical) and λ= 6mm (control) and for roughness heights (k) from 12 μm to 42 μm. The base flow considered was an ASU (67)-0315 aerofoil with 45 ⁰ sweep at -2.9 ⁰ incidence and with onset flow at a chord-based Reynolds number Re <inf>c</inf>= 2.4x10 ⁶. For λ= 12mm results showed, in accord with the experimental data, that the disturbance amplitude growth rate was linear for k = 12 μm and 24 μm, but the growth rate was decreased for k = 36 μm Receptivity to λ= 6mm roughness showed equally good agreement with experiments, indicating that this mode disappeared after a short distance to be replaced by a critical wavelength mode. Analysis of the development of modal disturbance amplitudes with downstream distance showed regions of linear, non-linear, saturation, and secondary instability behaviour. Examination of breakdown to turbulence revealed two possible routes: the first was 2D-like transition (probably Tollmien-Schlichting waves even in the presence of crossflow vortices) when transition occurred beyond the pressure minimum; the second was a classical crossflow vortex secondary instability, leading to the formation of a turbulent wedge

Prediction of Promiscuous P-Glycoprotein Inhibition Using a Novel Machine Learning Scheme

BACKGROUND: P-glycoprotein (P-gp) is an ATP-dependent membrane transporter that plays a pivotal role in eliminating xenobiotics by active extrusion of xenobiotics from the cell. Multidrug resistance (MDR) is highly associated with the over-expression of P-gp by cells, resulting in increased efflux of chemotherapeutical agents and reduction of intracellular drug accumulation. It is of clinical importance to develop a P-gp inhibition predictive model in the process of drug discovery and development. METHODOLOGY/PRINCIPAL FINDINGS: An in silico model was derived to predict the inhibition of P-gp using the newly invented pharmacophore ensemble/support vector machine (PhE/SVM) scheme based on the data compiled from the literature. The predictions by the PhE/SVM model were found to be in good agreement with the observed values for those structurally diverse molecules in the training set (n = 31, r(2) = 0.89, q(2) = 0.86, RMSE = 0.40, s = 0.28), the test set (n = 88, r(2) = 0.87, RMSE = 0.39, s = 0.25) and the outlier set (n = 11, r(2) = 0.96, RMSE = 0.10, s = 0.05). The generated PhE/SVM model also showed high accuracy when subjected to those validation criteria generally adopted to gauge the predictivity of a theoretical model. CONCLUSIONS/SIGNIFICANCE: This accurate, fast and robust PhE/SVM model that can take into account the promiscuous nature of P-gp can be applied to predict the P-gp inhibition of structurally diverse compounds that otherwise cannot be done by any other methods in a high-throughput fashion to facilitate drug discovery and development by designing drug candidates with better metabolism profile

A quantitative systems view of the spindle assembly checkpoint

The idle assembly checkpoint acts to delay chromosome segregation until all duplicated sister chromatids are captured by the mitotic spindle. This pathway ensures that each daughter cell receives a complete copy of the genome. The high fidelity and robustness of this process have made it a subject of intense study in both the experimental and computational realms. A significant number of checkpoint proteins have been identified but how they orchestrate the communication between local spindle attachment and global cytoplasmic signalling to delay segregation is not yet understood. Here, we propose a systems view of the spindle assembly checkpoint to focus attention on the key regulators of the dynamics of this pathway. These regulators in turn have been the subject of detailed cellular measurements and computational modelling to connect molecular function to the dynamics of spindle assembly checkpoint signalling. A review of these efforts reveals the insights provided by such approaches and underscores the need for further interdisciplinary studies to reveal in full the quantitative underpinnings of this cellular control pathway

C-type lectin-like domains in Fugu rubripes

BACKGROUND: Members of the C-type lectin domain (CTLD) superfamily are metazoan proteins functionally important in glycoprotein metabolism, mechanisms of multicellular integration and immunity. Three genome-level studies on human, C. elegans and D. melanogaster reported previously demonstrated almost complete divergence among invertebrate and mammalian families of CTLD-containing proteins (CTLDcps). RESULTS: We have performed an analysis of CTLD family composition in Fugu rubripes using the draft genome sequence. The results show that all but two groups of CTLDcps identified in mammals are also found in fish, and that most of the groups have the same members as in mammals. We failed to detect representatives for CTLD groups V (NK cell receptors) and VII (lithostathine), while the DC-SIGN subgroup of group II is overrepresented in Fugu. Several new CTLD-containing genes, highly conserved between Fugu and human, were discovered using the Fugu genome sequence as a reference, including a CSPG family member and an SCP-domain-containing soluble protein. A distinct group of soluble dual-CTLD proteins has been identified, which may be the first reported CTLDcp group shared by invertebrates and vertebrates. We show that CTLDcp-encoding genes are selectively duplicated in Fugu, in a manner that suggests an ancient large-scale duplication event. We have verified 32 gene structures and predicted 63 new ones, and make our annotations available through a distributed annotation system (DAS) server and their sequences as additional files with this paper. CONCLUSIONS: The vertebrate CTLDcp family was essentially formed early in vertebrate evolution and is completely different from the invertebrate families. Comparison of fish and mammalian genomes revealed three groups of CTLDcps and several new members of the known groups, which are highly conserved between fish and mammals, but were not identified in the study using only mammalian genomes. Despite limitations of the draft sequence, the Fugu rubripes genome is a powerful instrument for gene discovery and vertebrate evolutionary analysis. The composition of the CTLDcp superfamily in fish and mammals suggests that large-scale duplication events played an important role in the evolution of vertebrates