The metastability of human UDP-galactose 4'-epimerase (GALE) is increased by variants associated with type III galactosemia but decreased by substrate and cofactor binding

Type III galactosemia is an inherited disease caused by mutations which affect the activity of UDP-galactose 4'-epimerase (GALE). We evaluated the impact of four disease-associated variants (p.N34S, p.G90E, p.V94M and p.K161N) on the conformational stability and dynamics of GALE. Thermal denaturation studies showed that wild-type GALE denatures at temperatures close to physiological, and disease-associated mutations often reduce GALE's thermal stability. This denaturation is under kinetic control and results partly from dimer dissociation. The natural ligands, NAD(+) and UDP-glucose, stabilize GALE. Proteolysis studies showed that the natural ligands and disease-associated variations affect local dynamics in the N-terminal region of GALE. Proteolysis kinetics followed a two-step irreversible model in which the intact protein is cleaved at Ala38 forming a long-lived intermediate in the first step. NAD(+) reduces the rate of the first step, increasing the amount of undigested protein whereas UDP-glucose reduces the rate of the second step, increasing accumulation of the intermediate. Disease-associated variants affect these rates and the amounts of protein in each state. Our results also suggest communication between domains in GALE. We hypothesize that, in vivo, concentrations of natural ligands modulate GALE stability and that it should be possible to discover compounds which mimic the stabilising effects of the natural ligands overcoming mutation-induced destabilization.

Complexity of Inferences in Polytree-shaped Semi-Qualitative Probabilistic Networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the Bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that inferences can be performed in linear time if there is a single observed node, which is a relevant practical case. Because our proof is constructive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynomial-time algorithm for SQPNs. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

Effect of solvent on the hydrogenation of 4-phenyl-2-butanone over Pt based catalysts

The hydrogenation of 4-phenyl-2-butanone over Pt/TiO2 and Pt/SiO2 catalysts has been performed in a range of solvents and it has been observed that the solvent impacted on the selectivity of ketone and aromatic ring hydrogenation as well as the overall TOF of the titania catalyst with no solvent effect on selectivity observed using the silica supported catalyst where ring hydrogenation was favored. For the titania catalyst, alkanes were found to favor ring hydrogenation whereas aromatics and alcohols led to carbonyl hydrogenation. A two-site catalyst model is proposed whereby the aromatic ring hydrogenation occurs over the metal sites while carbonyl hydrogenation is thought to occur predominantly at interfacial sites, with oxygen vacancies in the titania support activating the carbonyl. The effect of the solvent on the hydrogenation reaction over the titania catalyst was related to competition for the active sites between solvent and 4-phenyl-2-butanone.

The Development and Testing of a New Version of the Cognitive Reflection Test Applying Item Response Theory (IRT)

The cognitive reflection test (CRT) is a short measure of a person's ability to resist intuitive response tendencies and to produce a normatively correct response, which is based on effortful reasoning. Although the CRT is a very popular measure, its psychometric properties have not been extensively investigated. A major limitation of the CRT is the difficulty of the items, which can lead to floor effects in populations other than highly educated adults. The present study aimed at investigating the psychometric properties of the CRT applying item response theory analyses (a two-parameter logistic model) and at developing a new version of the scale (the CRT-long), which is appropriate for participants with both lower and higher levels of cognitive reflection. The results demonstrated the good psychometric properties of the original, as well as the new scale. The validity of the new scale was also assessed by measuring correlations with various indicators of intelligence, numeracy, reasoning and decision-making skills, and thinking dispositions. Moreover, we present evidence for the suitability of the new scale to be used with developmental samples. Finally, by comparing the performance of adolescents and young adults on the CRT and CRT-long, we report the first investigation into the development of cognitive reflection.

Experimental validation of a drive-by stiffness identification method for bridge monitoring

An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

Polybius’ ‘previous landslide’: Proof that Hannibal’s invasion route crossed the col de la traversette

Both Polybius and Livy described a landslide/landslip that blocked the Punic Army’s exfiltration from a high col on the water divide in the Western Alps. The landslide, more aptly termed rockfall, has been a source of contention amongst classicists for centuries despite the fact that only two cols—Clapier and Traversette—exhibit rockfall debris on the lee side of the Alps. While the Clapier rockfall is too small and too young to have provided blockage, the Traversette debris is nearly as Polybius described it when he retraced the invasion route some 60 years after the event. His ‘two-tier’ description of the deposit, a doublet of younger and older rock rubble, including measurements of width and volume are close to modern measurements and prove that he knew, in advance, the route Hannibal had followed. It would take a practiced eye to correctly identify the stratigraphic complexity inherent in the Traversette Rockfall. Here we present weathering ratios, soil stratigraphic, mineral, chemical and microbiological evidence in support of Polybius’ observations as a considerable background database for future geoarchaeological exploration.

Transcending epithelial and intracellular biological barriers; a prototype DNA delivery device

Microneedle technology provides the opportunity for the delivery of DNA therapeutics by a non-invasive, patient acceptable route. To deliver DNA successfully requires consideration of both extra and intracellular biological barriers. In this study we present a novel two tier platform; i) a peptide delivery system, termed RALA, that is able to wrap the DNA into nanoparticles, protect the DNA from degradation, enter cells, disrupt endosomes and deliver the DNA to the nucleus of cells ii) a microneedle (MN) patch that will house the nanoparticles within the polymer matrix, breach the skin's stratum corneum barrier and dissolve upon contact with skin interstitial fluid thus releasing the nanoparticles into the skin. Our data demonstrates that the RALA is essential for preventing DNA degradation within the poly(vinylpyrrolidone) (PVP) polymer matrix. In fact the RALA/DNA nanoparticles (NPs) retained functionality when in the MN arrays after 28days and over a range of temperatures. Furthermore the physical strength and structure of the MNs was not compromised when loaded with the NPs. Finally we demonstrated the effectiveness of our MN-NP platform in vitro and in vivo, with systemic gene expression in highly vascularised regions. Taken together this 'smart-system' technology could be applied to a wide range of genetic therapies.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Nonequilibrium critical scaling from quantum thermodynamics

The emerging field of quantum thermodynamics is contributing important results and insights into archetypal many-body problems, including quantum phase transitions. Still, the question whether out-of-equilibrium quantities, such as fluctuations of work, exhibit critical scaling after a sudden quench in a closed system has remained elusive. Here, we take a novel approach to the problem by studying a quench across an impurity quantum critical point. By performing density matrix renormalization group computations on the two-impurity Kondo model, we are able to establish that the irreversible work produced in a quench exhibits finite-size scaling at quantum criticality. This scaling faithfully predicts the equilibrium critical exponents for the crossover length and the order parameter of the model, and, moreover, implies a new exponent for the rescaled irreversible work. By connecting the irreversible work to the two-impurity spin correlation function, our findings can be tested experimentally.

Catalyst screening: Refinement of the origin of the volcano curve and its implication in heterogeneous catalysis

Understanding the overall catalytic activity trend for rational catalyst design is one of the core goals in heterogeneous catalysis. In the past two decades, the development of density functional theory (DFT) and surface kinetics make it feasible to theoretically evaluate and predict the catalytic activity variation of catalysts within a descriptor-based framework. Thereinto, the concept of the volcano curve, which reveals the general activity trend, usually constitutes the basic foundation of catalyst screening. However, although it is a widely accepted concept in heterogeneous catalysis, its origin lacks a clear physical picture and definite interpretation. Herein, starting with a brief review of the development of the catalyst screening framework, we use a two-step kinetic model to refine and clarify the origin of the volcano curve with a full analytical analysis by integrating the surface kinetics and the results of first-principles calculations. It is mathematically demonstrated that the volcano curve is an essential property in catalysis, which results from the self-poisoning effect accompanying the catalytic adsorption process. Specifically, when adsorption is strong, it is the rapid decrease of surface free sites rather than the augmentation of energy barriers that inhibits the overall reaction rate and results in the volcano curve. Some interesting points and implications in assisting catalyst screening are also discussed based on the kinetic derivation. Moreover, recent applications of the volcano curve for catalyst design in two important photoelectrocatalytic processes (the hydrogen evolution reaction and dye-sensitized solar cells) are also briefly discussed.

The Development of a Two-Dimensional Transient Catalyst Model for Direct Injection Two-Stroke Applications.

This paper describes the development of a two-dimensional transient catalyst model. Although designed primarily for two-stroke direct injection engines, the model is also applicable to four-stroke lean burn and diesel applications. The first section describes the geometries, properties and chemical processes simulated by the model and discusses the limitations and assumptions applied. A review of the modeling techniques adopted by other researchers is also included. The mathematical relationships which are used to represent the system are then described, together with the finite volume method used in the computer program. The need for a two-dimensional approach is explained and the methods used to model effects such as flow and temperature distribution are presented. The problems associated with developing surface reaction rates are discussed in detail and compared with published research. Validation and calibration of the model is achieved by comparing predictions with measurements from a flow reactor. While an extensive validation process, involving detailed measurements of gas composition and thermal gradients, has been completed, the analysis is too detailed for publication here and is the subject of a separate technical paper.

The Validation of a Two-Dimensional Transient Catalyst Model for Direct Injection Two-Stroke Applications

This paper describes the detailed validation of a computer model designed to simulate the transient light-off in a two-stroke oxidation catalyst. A plug flow reactor is employed to provide measurements of temperature and gas concentration at various radial and axial locations inside the catalyst. These measurements are recorded at discrete intervals during a transient light-off in which the inlet temperature is increased from ambient to 300oC at rates of up to 6oC/sec. The catalyst formulation used in the flow reactor, and its associated test procedures, are then simulated by the computer and a comparison made between experimental readings and model predictions. The design of the computer model to which this validation exercise relates is described in detail in a separate technical paper. The first section of the paper investigates the warm-up characteristics of the substrate and examines the validity of the heat transfer predictions between the wall and the gas in the absence of chemical reactions. The predictions from a typical single-component CO transient light-off test are discussed in the second section and are compared with experimental data. In particular the effect of the temperature ramp on the light-off curve and reaction zone development is examined. An analysis of the C3H6 conversion is given in the third section while the final section examines the accuracy of the light-off curves which are produced when both CO and C3H6 are present in the feed gas. The analysis shows that the heat and mass transfer calculations provided reliable predictions of the warm-up behaviour and post light-off gas concentration profiles. The self-inhibition and cross-inhibition terms in the global rate expressions were also found to be reasonably reliable although the surface reaction rates required calibration with experimental data.

Comparison of two construction algorithms for local model networks

The divide-and-conquer approach of local model (LM) networks is a common engineering approach to the identification of a complex nonlinear dynamical system. The global representation is obtained from the weighted sum of locally valid, simpler sub-models defined over small regions of the operating space. Constructing such networks requires the determination of appropriate partitioning and the parameters of the LMs. This paper focuses on the structural aspect of LM networks. It compares the computational requirements and performances of the Johansen and Foss (J&F) and LOLIMOT tree-construction algorithms. Several useful and important modifications to each algorithm are proposed. The modelling performances are evaluated using real data from a pilot plant of a pH neutralization process. Results show that while J&F achieves a more accurate nonlinear representation of the pH process, LOLIMOT requires significantly less computational effort.