Plasmodium falciparum glyoxalase II: Theorell-Chance product inhibition patterns, rate-limiting substrate binding via Arg(257)/Lys(260), and unmasking of acid-base catalysis

Glyoxalase II (GloII) is a ubiquitous thioester hydrolase catalyzing the last step of the glutathione-dependent conversion of 2-oxoaldehydes to 2-hydroxycarboxylic acids. Here, we present a detailed structure-function analysis of cGloII from the malaria parasite Plasmodium falciparum. The activity of the enzyme was salt-sensitive and pH-log k(cat) and pH-log k(cat)/K-m profiles revealed acid-base catalysis. An acidic pK(a)(app) value of approximately 6 probably reflects hydroxide formation at the metal center. The glutathione-binding site was analyzed by site-directed mutagenesis. Substitution of residue Arg(154) caused a 2.5-fold increase of K-m(app), whereas replacements of Arg(257) or Lys(260) were far more detrimental. Although the glutathione-binding site and the catalytic center are separated, six of six single mutations at the substrate-binding site decreased the k(cat)(app) value. Furthermore, product inhibition studies support a Theorell-Chance Bi Bi mechanism with glutathione as the second product. We conclude that the substrate is predominantly bound via ionic interactions with the conserved residues Arg(257) and Lys(260), and that correct substrate binding is a pH-and salt-dependent rate-limiting step for catalysis. The presented mechanistic model is presumably also valid for GloII from many other organisms. Our study could be valuable for drug development strategies and enhances the understanding of the chemistry of binuclear metallohydrolases

The international risk-sharing puzzle is at business-cycle and lower frequency

We decompose the correlation between relative consumption and the real exchange rate into its dynamic components at different frequencies. Using multivariate spectral analysis techniques we show that, at odds with a high degree of risk-sharing, in most OECD countries the dynamic correlation tends to be quite negative, and signifi cantly so, at frequencies lower than two years —the appropriate frequencies for assessing the performance of international business cycle models. Theoretically, we show that the dynamic correlation over different frequencies predicted by standard open-economy models is the sum of two terms: a term constant across frequencies, which can be negative when uninsurable risk is largeand a term variable across frequencies, which in bond economies is necessarily positive, refl ecting the insurance that intertemporal trade provides against forecastable contingencies. Numerical analysis suggests that leading mechanisms proposed by the literature to account for the puzzle are consistent with the evidence across the spectrumDescomponemos la correlación entre el consumo relativo y el tipo de cambio real en sus componentes dinámicos a diferentes frecuencias. Utilizando técnicas de análisis espectral multivariado mostramos que, en contradicción con un alto grado de diversifi cación del riesgo, en la mayoría de los países de la OCDE la correlación dinámica tiende a ser bastante negativa, y signifi cativamente negativa a frecuencias inferiores a dos años —las frecuencias apropiadas para evaluar el desempeño de los modelos internacionales del ciclo económico—. En teoría mostramos que la correlación dinámica a diferentes frecuencias predicha por modelos estándar de economía abierta, es la suma de dos términos: un término constante en cada frecuencia, que puede ser negativo cuando el riesgo no asegurable es grandey un término que varia con la frecuencia, que en economías con bonos es necesariamente positivo y que refl eja la cobertura de riesgo contra contingencias predecibles proporcionada por el comercio intertemporal. El análisis numérico sugiere que los mecanismos principales propuestos por la literatura para dar cuenta de la anomalía, son consistentes con la evidencia empírica a diferentes frecuencias del espectr

Ridge Formation and De-Spinning of Iapetus via an Impact-Generated Satellite

We present a scenario for building the equatorial ridge and de-spinning Iapetus through an impact-generated disk and satellite. This impact puts debris into orbit, forming a ring inside the Roche limit and a satellite outside. This satellite rapidly pushes the ring material down to the surface of Iapetus, and then itself tidally evolves outward, thereby helping to de-spin Iapetus. This scenario can de-spin Iapetus an order of magnitude faster than when tides due to Saturn act alone, almost independently of its interior geophysical evolution. Eventually, the satellite is stripped from its orbit by Saturn. The range of satellite and impactor masses required is compatible with the estimated impact history of Iapetus.Comment: 19 pages, 3 figures; Icarus, in pres

Missing data imputation of high-resolution temporal climate time series data

© 2020 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Analysis of high-resolution data offers greater opportunity to understand the nature of data variability, behaviours, trends and to detect small changes. Climate studies often require complete time series data which, in the presence of missing data, means imputation must be undertaken. Research on the imputation of high-resolution temporal climate time series data is still at an early phase. In this study, multiple approaches to the imputation of missing values were evaluated, including a structural time series model with Kalman smoothing, an autoregressive integrated moving average (ARIMA) model with Kalman smoothing and multiple linear regression. The methods were applied to complete subsets of data from 12 month time series of hourly temperature, humidity and wind speed data from four locations along the coast of Western Australia. Assuming that observations were missing at random, artificial gaps of missing observations were studied using a five-fold cross-validation methodology with the proportion of missing data set to 10%. The techniques were compared using the pooled mean absolute error, root mean square error and symmetric mean absolute percentage error. The multiple linear regression model was generally the best model based on the pooled performance indicators, followed by the ARIMA with Kalman smoothing. However, the low error values obtained from each of the approaches suggested that the models competed closely and imputed highly plausible values. To some extent, the performance of the models varied among locations. It can be concluded that the modelling approaches studied have demonstrated suitability in imputing missing data in hourly temperature, humidity and wind speed data and are therefore recommended for application in other fields where high-resolution data with missing values are common

Time series forecasting with the WARIMAX-GARCH method

It is well-known that causal forecasting methods that include appropriately chosen Exogenous Variables (EVs) very often present improved forecasting performances over univariate methods. However, in practice, EVs are usually difficult to obtain and in many cases are not available at all. In this paper, a new causal forecasting approach, called Wavelet Auto-Regressive Integrated Moving Average with eXogenous variables and Generalized Auto-Regressive Conditional Heteroscedasticity (WARIMAX-GARCH) method, is proposed to improve predictive performance and accuracy but also to address, at least in part, the problem of unavailable EVs. Basically, the WARIMAX-GARCH method obtains Wavelet “EVs” (WEVs) from Auto-Regressive Integrated Moving Average with eXogenous variables and Generalized Auto-Regressive Conditional Heteroscedasticity (ARIMAX-GARCH) models applied to Wavelet Components (WCs) that are initially determined from the underlying time series. The WEVs are, in fact, treated by the WARIMAX-GARCH method as if they were conventional EVs. Similarly to GARCH and ARIMA-GARCH models, the WARIMAX-GARCH method is suitable for time series exhibiting non-linear characteristics such as conditional variance that depends on past values of observed data. However, unlike those, it can explicitly model frequency domain patterns in the series to help improve predictive performance. An application to a daily time series of dam displacement in Brazil shows the WARIMAX-GARCH method to remarkably outperform the ARIMA-GARCH method, as well as the (multi-layer perceptron) Artificial Neural Network (ANN) and its wavelet version referred to as Wavelet Artificial Neural Network (WANN) as in [1], on statistical measures for both in-sample and out-of-sample forecasting

Beta decay and shape isomerism in 74Kr

We study the properties of $^{74}$Kr, and particularly the Gamow Teller strength distribution, using a deformed selfconsistent HF+RPA method with Skyrme type interactions. Results are presented for two density-dependent effective two-body interactions, including the dependence on deformation of the HF energy that exhibits two minima at close energies and distant deformations, one prolate and one oblate. We study the role of deformation, residual interaction, pairing and RPA correlations on the Gamow Teller strength distribution. Results on moments of inertia and gyromagnetic factors, as well as on $E0$ and $M1$ transitions are also presented.Comment: 20 pages, RevTeX. 12 PS figures. To appear in Nucl. Phys.

Sleepwalking into lock-in? Avoiding wrongs to future people in the governance of solar radiation management research

This paper argues for two ways in which we can avoid the reckless endangerment of future people in the governance of solar radiation management (SRM) research, which could happen through lock-in to SRM deployment from research. SRM research is at an early stage, one at which the mechanisms of lock-in could start to operate. However, lock-in fit to endanger future people could be slowed or stopped through targeted governance. This paper argues that governance of SRM research that does not include provisions to detect, slow, or stop lock-in fails the test of an intergenerationally adequate precautionary principle, and that research governed without these provisions cannot itself be justified as a precaution against the impacts of climate change

HOx observations over West Africa during AMMA: impact of isoprene and NOx

Aircraft OH and HO2 measurements made over West Africa during the AMMA field campaign in summer 2006 have been investigated using a box model constrained to observations of long-lived species and physical parameters. "Good" agreement was found for HO2 (modelled to observed gradient of 1.23 ± 0.11). However, the model significantly overpredicts OH concentrations. The reasons for this are not clear, but may reflect instrumental instabilities affecting the OH measurements. Within the model, HOx concentrations in West Africa are controlled by relatively simple photochemistry, with production dominated by ozone photolysis and reaction of O(1D) with water vapour, and loss processes dominated by HO2 + HO2 and HO2 + RO2. Isoprene chemistry was found to influence forested regions. In contrast to several recent field studies in very low NOx and high isoprene environments, we do not observe any dependence of model success for HO2 on isoprene and attribute this to efficient recycling of HOx through RO2 + NO reactions under the moderate NOx concentrations (5–300 ppt NO in the boundary layer, median 76 ppt) encountered during AMMA. This suggests that some of the problems with understanding the impact of isoprene on atmospheric composition may be limited to the extreme low range of NOx concentrations

Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy

Fiber-based Raman spectroscopy in the context of &lt;italic&gt;in vivo&lt;/italic&gt; biomedical application suffers from the presence of background fluorescence from the surrounding tissue that might mask the crucial but inherently weak Raman signatures. One method that has shown potential for suppressing the background to reveal the Raman spectra is shifted excitation Raman spectroscopy (SER). SER collects multiple emission spectra by shifting the excitation by small amounts and uses these spectra to computationally suppress the fluorescence background based on the principle that Raman spectrum shifts with excitation while fluorescence spectrum does not. We introduce a method that utilizes the spectral characteristics of the Raman and fluorescence spectra to estimate them more effectively, and compare this approach against existing methods on real world datasets.</p