Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor

The integration of ligand- and structure-based strategies might sensitively increase the success of drug discovery process. We have recently described the application of Molecular Electrostatic Potential autocorrelated vectors (autoMEPs) in generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to quantitatively predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, we have also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM), as a tool to simulate the conformational changes of the receptor induced by ligand binding. In the present study, the application of both linear and nonlinear 3D-QSAR methods and LBHM computational techniques has been used to depict the hypothetical antagonist binding site of the human adenosine A2A receptor. In particular, a collection of 127 known human A2A antagonists has been utilized to derive two 3D-QSAR models (autoMEPs/PLS&RSA). In parallel, using a rhodopsin-driven homology modeling approach, we have built a model of the human adenosine A2A receptor. Finally, 3D-QSAR and LBHM strategies have been utilized to predict the binding affinity of five new human A2A pyrazolo-triazolo-pyrimidine antagonists finding a good agreement between the theoretical and the experimental predictions.     

Sample selection models for count data in R

We provide a detailed hands-on tutorial for the R package SemiParSampleSel (version 1.5). The package implements selection models for count responses fitted by penalized maximum likelihood estimation. The approach can deal with non-random sample selection, flexible covariate effects, heterogeneous selection mechanisms and varying distributional parameters. We provide an overview of the theoretical background and then demonstrate how SemiParSampleSel can be used to fit interpretable models of different complexity. We use data from the German Socio-Economic Panel survey (SOEP v28, 2012. doi: 10.5684/soep.v28) throughout the tutorial.     

Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model

We introduce a binary regression accounting-based model for bankruptcy prediction of small and medium enterprises (SMEs). The main advantage of the model lies in its predictive performance in identifying defaulted SMEs. Another advantage, which is especially relevant for banks, is that the relationship between the accounting characteristics of SMEs and response is not assumed a priori (eg, linear, quadratic or cubic) and can be determined from the data. The proposed approach uses the quantile function of the generalized extreme value distribution as link function as well as smooth functions of accounting characteristics to flexibly model covariate effects. Therefore, the usual assumptions in scoring models of symmetric link function and linear or pre-specified covariate-response relationships are relaxed. Out-of-sample and out-of-time validation on Italian data shows that our proposal outperforms the commonly used (logistic) scoring model for different default horizons.     

Dynamic Plots in Virtual Negotiations

Advanced information and communications technology provides the basis for continuous monitoring of, and rapid data exchange about, crucial operations. Of special interest are those conflict situations where organizations continuously readjust mutually affecting decisions, considering the competitors' choices, but without communicating verbally. An example refers to trucking companies who base their decisions, which trucks to assign to different routes, on the competitors' assignments. To support the decision process for these types of virtual negotiation settings, a new dynamic plot approach is proposed. Dynamic plots can be used to visualize the decision topology of all parties and the impact of making a decision on all parties. Of special interest in this paper are dynamic plots with an individual stability equilibrium, where competitors do not revise their decisions unless a change in the market occurs. Dynamic plots for 2 × 2 conflict situations are discussed first, followed by a discussion of 3 × 3 conflict situations. The paper closes with a discussion of a computer implementation and empirical evidence of virtual negotiations with dynamic plots. The results of these virtual negotiations suggest that dynamic plots stimulate virtual negotiations and support efficiency, equity, and system optimum for these types of real-time negotiations.     

Applications of 1-alkoxycarbonyl- and 1-acyl-v-triazolo[4,5-b]pyridines as acylating reagents

Selective N-protection of hydroxyamino esters has been readily achieved using 1-alkoxycarbonyl- or 1-acyl-v-triazolo[4,5-b]pyridines. The amide-type triazolides reacted with alcohols in the presence of DBU at room temperature to afford in high yields the corresponding esters. The different reactivity of 1- and 3-alkoxycarbonyl derivatives of the title bicyclic system toward primary amines has been further investigated.     

Graphite electrode lithium tetraborate fusion for trace element determination in bulk geological samples by laser ablation ICP-MS

A rapid, accurate and precise method is presented for rock sample preparation in bulk analysis by LA-ICP-MS. Sample preparation is performed by lithium tetraborate fusion using an apparatus consisting of a 12 V (400 A) power source coupled with graphite electrodes utilized as crucibles. It allows analyzing few mg of powdered rock and, therefore, it could be useful in the case of low sample availability. An automated analytical protocol that allows determination of 25 elements (Ga, Rb, Sr, Y, Zr, Nb, Ba, rare earth elements, Hf, Ta, Pb, Th, and U) in 24 samples is also presented. Figure of merits related to the complete analytical protocol (sample preparation as fusion beads and LA-ICP-MS analyses) are estimated on five reference materials (USGS BCR2, USGS AGV2, USGS GSP2, CRPG ACE, and USGS RGM1) ranging from basaltic to rhyolitic in composition. The limits of detection range from c.a. 0.1 μg·g⁻¹ for Rb to 0.0007 μg·g⁻¹ for U. Precision is better than 10% for all elements with concentrations above 2 μg·g⁻¹, except for Pb (∼15%). Precision values raise to c.a. 15% for elements in concentration close to the limits of detection. Accuracies are better than 12% for all elements.