scholarly journals Reduction Potential Predictions for Some 3-Aryl-Quinoxaline-2-Carbonitrile 1,4-Di-N-Oxide Derivatives with Known Anti-Tumor Properties

Computation ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 6
Author(s):  
Eric M. Miller ◽  
Cody J. Brazel ◽  
Krystina A. Brillos-Monia ◽  
Philip W. Crawford ◽  
Hannah C. Hufford ◽  
...  

The ability for DFT: B3LYP calculations using the 6-31g and lanl2dz basis sets to predict the electrochemical properties of twenty (20) 3-aryl-quinoxaline-2-carbonitrile 1,4-di-N-oxide derivatives with varying degrees of cytotoxic activity in dimethylformamide (DMF) was investigated. There was a strong correlation for the first reduction and moderate-to-low correlation of the second reduction of the diazine ring between the computational and the experimental data, with the exception of the derivative containing the nitro functionality. The four (4) nitro group derivatives are clear outliers in the overall data sets and the derivative E4 is ill-behaved. The remaining three (3) derivatives containing the nitro groups had a strong correlation between the computational and experimental data; however, the computational data falls substantially outside of the expected range.

Author(s):  
Cyprian Suchocki ◽  
Stanisław Jemioło

AbstractIn this work a number of selected, isotropic, invariant-based hyperelastic models are analyzed. The considered constitutive relations of hyperelasticity include the model by Gent (G) and its extension, the so-called generalized Gent model (GG), the exponential-power law model (Exp-PL) and the power law model (PL). The material parameters of the models under study have been identified for eight different experimental data sets. As it has been demonstrated, the much celebrated Gent’s model does not always allow to obtain an acceptable quality of the experimental data approximation. Furthermore, it is observed that the best curve fitting quality is usually achieved when the experimentally derived conditions that were proposed by Rivlin and Saunders are fulfilled. However, it is shown that the conditions by Rivlin and Saunders are in a contradiction with the mathematical requirements of stored energy polyconvexity. A polyconvex stored energy function is assumed in order to ensure the existence of solutions to a properly defined boundary value problem and to avoid non-physical material response. It is found that in the case of the analyzed hyperelastic models the application of polyconvexity conditions leads to only a slight decrease in the curve fitting quality. When the energy polyconvexity is assumed, the best experimental data approximation is usually obtained for the PL model. Among the non-polyconvex hyperelastic models, the best curve fitting results are most frequently achieved for the GG model. However, it is shown that both the G and the GG models are problematic due to the presence of the locking effect.


2021 ◽  
Vol 22 (2) ◽  
pp. 633
Author(s):  
Konrad Skotnicki ◽  
Slawomir Ostrowski ◽  
Jan Cz. Dobrowolski ◽  
Julio R. De la Fuente ◽  
Alvaro Cañete ◽  
...  

The azide radical (N3●) is one of the most important one-electron oxidants used extensively in radiation chemistry studies involving molecules of biological significance. Generally, it was assumed that N3● reacts in aqueous solutions only by electron transfer. However, there were several reports indicating the possibility of N3● addition in aqueous solutions to organic compounds containing double bonds. The main purpose of this study was to find an experimental approach that allows a clear assignment of the nature of obtained products either to its one-electron oxidation or its addition products. Radiolysis of water provides a convenient source of one-electron oxidizing radicals characterized by a very broad range of reduction potentials. Two inorganic radicals (SO4●−, CO3●−) and Tl2+ ions with the reduction potentials higher, and one radical (SCN)2●− with the reduction potential slightly lower than the reduction potential of N3● were selected as dominant electron-acceptors. Transient absorption spectra formed in their reactions with a series of quinoxalin-2-one derivatives were confronted with absorption spectra formed from reactions of N3● with the same series of compounds. Cases, in which the absorption spectra formed in reactions involving N3● differ from the absorption spectra formed in the reactions involving other one-electron oxidants, strongly indicate that N3● is involved in the other reaction channel such as addition to double bonds. Moreover, it was shown that high-rate constants of reactions of N3● with quinoxalin-2-ones do not ultimately prove that they are electron transfer reactions. The optimized structures of the radical cations (7-R-3-MeQ)●+, radicals (7-R-3-MeQ)● and N3● adducts at the C2 carbon atom in pyrazine moiety and their absorption spectra are reasonably well reproduced by density functional theory quantum mechanics calculations employing the ωB97XD functional combined with the Dunning’s aug-cc-pVTZ correlation-consistent polarized basis sets augmented with diffuse functions.


2014 ◽  
Vol 11 (2) ◽  
pp. 68-79
Author(s):  
Matthias Klapperstück ◽  
Falk Schreiber

Summary The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example.


2015 ◽  
Vol 24 (07) ◽  
pp. 1550050 ◽  
Author(s):  
E. Matsinos ◽  
G. Rasche

In a previous paper, we reported the results of a partial-wave analysis (PWA) of the pion–nucleon (πN) differential cross-sections (DCSs) of the CHAOS Collaboration and came to the conclusion that the angular distribution of their π+p data sets is incompatible with the rest of the modern (meson factory) database. The present work, re-addressing this issue, has been instigated by a number of recent improvements in our analysis, namely regarding the inclusion of the theoretical uncertainties when investigating the reproduction of experimental data sets on the basis of a given "theoretical" solution, modifications in the parametrization of the form factors of the proton and of the pion entering the electromagnetic part of the πN amplitude, and the inclusion of the effects of the variation of the σ-meson mass when fitting the ETH model of the πN interaction to the experimental data. The new analysis of the CHAOS DCSs confirms our earlier conclusions and casts doubt on the value for the πN Σ term, which Stahov, Clement and Wagner have extracted from these data.


Polymers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3811
Author(s):  
Iosif Sorin Fazakas-Anca ◽  
Arina Modrea ◽  
Sorin Vlase

This paper proposes a new method for calculating the monomer reactivity ratios for binary copolymerization based on the terminal model. The original optimization method involves a numerical integration algorithm and an optimization algorithm based on k-nearest neighbour non-parametric regression. The calculation method has been tested on simulated and experimental data sets, at low (<10%), medium (10–35%) and high conversions (>40%), yielding reactivity ratios in a good agreement with the usual methods such as intersection, Fineman–Ross, reverse Fineman–Ross, Kelen–Tüdös, extended Kelen–Tüdös and the error in variable method. The experimental data sets used in this comparative analysis are copolymerization of 2-(N-phthalimido) ethyl acrylate with 1-vinyl-2-pyrolidone for low conversion, copolymerization of isoprene with glycidyl methacrylate for medium conversion and copolymerization of N-isopropylacrylamide with N,N-dimethylacrylamide for high conversion. Also, the possibility to estimate experimental errors from a single experimental data set formed by n experimental data is shown.


F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 146 ◽  
Author(s):  
Guanming Wu ◽  
Eric Dawson ◽  
Adrian Duong ◽  
Robin Haw ◽  
Lincoln Stein

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.


2020 ◽  
Author(s):  
Nozhan Bayat ◽  
Puyan Mojabi

The standard weighted L2 norm total variation multiplicative regularization (MR) term originally developed for microwave imaging algorithms is modified to take into account<br>structural prior information, also known as spatial priors (SP), about the object being imaged. This modification adds one extra term to the integrand of the standard MR, thus, being referred to as an augmented MR (AMR). The main advantage of the proposed approach is that it requires a minimal change to the existing microwave imaging algorithms that are already equipped with the MR. Using two experimental data sets, it is shown that the proposed AMR (i) can handle partial SP, and (ii) can, to some extent, enhance the quantitative accuracy achievable from<br>microwave imaging.


2017 ◽  
Author(s):  
Alexander P. Browning ◽  
Scott W. McCue ◽  
Rachelle N. Binny ◽  
Michael J. Plank ◽  
Esha T. Shah ◽  
...  

AbstractCollective cell spreading takes place in spatially continuous environments, yet it is often modelled using discrete lattice-based approaches. Here, we use data from a series of cell proliferation assays, with a prostate cancer cell line, to calibrate a spatially continuous individual based model (IBM) of collective cell migration and proliferation. The IBM explicitly accounts for crowding effects by modifying the rate of movement, direction of movement, and the rate of proliferation by accounting for pair-wise interactions. Taking a Bayesian approach we estimate the free parameters in the IBM using rejection sampling on three separate, independent experimental data sets. Since the posterior distributions for each experiment are similar, we perform simulations with parameters sampled from a new posterior distribution generated by combining the three data sets. To explore the predictive power of the calibrated IBM, we forecast the evolution of a fourth experimental data set. Overall, we show how to calibrate a lattice-free IBM to experimental data, and our work highlights the importance of interactions between individuals. Despite great care taken to distribute cells as uniformly as possible experimentally, we find evidence of significant spatial clustering over short distances, suggesting that standard mean-field models could be inappropriate.


2021 ◽  
Vol 2103 (1) ◽  
pp. 012222
Author(s):  
Olga Kokorina ◽  
Vadim Rybin ◽  
Semyon Rudyi

Abstract We propose a double-well linear Paul trap for particle’s spatial selection according to the charge-to-mass ratio. To perform spatial selection we implemented an experimental setup that permits to detect particles’ positions in the double-well trap from three different view-points: top, front left, and front right. The setup gives an opportunity to monitor the particles’ axial density distribution in real-time. We have shown a strong correlation between axial position of separated localization areas and the DC voltages applied to the rod and end-cap electrodes. We have experimentally determined the critical localization parameters where double-well mode acquires for all the trapped charged microparticles. According to the experimental data and a numerical simulation a upper value of charge-to-mass ratio of the trapped microparticles was estimated.


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