Quinazoline Derivatives Designed as Efflux Pump Inhibitors: Molecular Modeling and Spectroscopic Studies

Multidrug resistance of bacteria is a worrying concern in the therapeutic field and an alternative method to combat it is designing new efflux pump inhibitors (EPIs). This article presents a molecular study of two quinazoline derivatives, labelled BG1189 and BG1190, proposed as EPIs. In silico approach investigates the pharmacodynamic and pharmacokinetic profile of BG1189 and BG1190 quinazolines. Molecular docking and predicted ADMET features suggest that BG1189 and BG1190 may represent attractive candidates as antimicrobial drugs. UV-Vis absorption spectroscopy was employed to study the time stability of quinazoline solutions in water or in dimethyl sulfoxide (DMSO), in constant environmental conditions, and to determine the influence of usual storage temperature, normal room lighting and laser radiation (photostability) on samples stability. The effects of irradiation on BG1189 and BG1190 molecules were also assessed through Fourier-transform infrared (FTIR) spectroscopy. FTIR spectra showed that laser radiation breaks some chemical bonds affecting the substituents and the quinazoline radical of the compounds.     

Current Efficiency,Corrosion and Structural Changes in SnO2-Sb2O3-CuO Inert Anodes for Aluminium Electrolysis

A systematic study was conducted on current efficiency （CE）, corrosion and structural changes in SnO2-based inert anodes （made of 96wt%SnO2＋2wt%Sb2O3＋2wt%CuO） on a laboratory Hall-Heroult aluminium cell. The influence of operating parameters and electrolyte composition on the CE and corrosion process were evaluated. The CE was found to be more than 90% and catastrophic corrosion took place at low percent of Al2O3, high percent of LiF, low cryolite ratio and high current densities. From all the structural changes that took place in the SnO2-based inert anodes, we assumed that the most important contribution was due to the migration of CuO towards the outer limits of the constituent grains of SnO2 based ceramic. The complex process occurred during the formation of various phases and their sintering ability both directly depended on Cu/Sb molar ratio.     

Higher-Order Convex Approximations of Young Measures in Optimal Control

The general theory of approximation of (possibly generalized) Young measures is presented, and concrete cases are investigated. An adjoint-operator approach, combined with quasi-interpolation of test integrands, is systematically used. Applicability is demonstrated on an optimal control problem for an elliptic system, together with one-dimensional illustrative calculations of various options.     

Properties and applications of $$P_n$$-simple functionals

In this paper some representations of a linear positive functional are established. These results are extended for linear positive operators \(L_n:C[a,b] \rightarrow C[a,b]\). Also, approximation properties of linear positive operators, expressed in terms of moduli of smoothness, are considered. In the last section, the remainder term in various approximation processes is studied.     

Sensitive detection of endocrine disrupters using ionic liquid--single walled carbon nanotubes modified screen-printed based biosensors

Simple and low cost biosensor based on screen-printed electrode for sensitive detection of some alkylphenols was developed, by entrapment of HRP in a nanocomposite gel based on single-walled carbon nanotubes (SWCNTs) and 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF₆]) ionic liquid. Raman and FTIR spectroscopy, CV and EIS studies demonstrate the interaction between SWCNTs and ionic liquid. The nanocomposite gel, SWCNT-[BMIM][PF₆] provides to the modified sensor a considerable enhanced electrocatalytic activity toward hydrogen peroxide reduction. The HRP based biosensor exhibits high sensitivity and good stability, allowing a detection of the alkylphenols at an applied potential of −0.2 V vs. Ag/AgCl, in linear range from 5.5 to 97.7 μM for 4-t-octylphenol and respectively, between 5.5 and 140 μM for 4-n-nonylphenol, with a response time of about 5 s. The detection limit was 1.1 μM for 4-t-octylphenol, and respectively 0.4 μM for 4-n-nonylphenol (S/N = 3).     

Assessment of the In Vivo Release and Biocompatibility of Novel Vesicles Containing Zinc in Rats

This paper is focused on the in vivo release and biocompatibility evaluation in rats of some novel systems entrapping zinc chloride in lipid vesicles. The particles were prepared by zinc chloride immobilization inside lipid vesicles made using phosphatidylcholine, stabilized with 0.5% chitosan solution, and dialyzed for 10 h to achieve a neutral pH. The submicrometric systems were physico-chemically characterized. White Wistar rats, assigned into four groups of six animals each, were treated orally with a single dose, as follows: Group I (control): deionized water 0.3 mL/100 g body weight; Group II (Zn): 2 mg/kg body weight (kbw) zinc chloride; Group III (LV-Zn): 2 mg/kbw zinc chloride in vesicles; Group IV (LVC-Zn): 2 mg/kbw zinc chloride in vesicles stabilized with chitosan. Haematological, biochemical, and immune parameters were assessed after 24 h and 7 days, and then liver fragments were collected for histopathological examination. The use of zinc submicrometric particles—especially those stabilized with chitosan—showed a delayed zinc release in rats. No substantial changes to blood parameters, plasma biochemical tests, serum complement activity, or peripheral neutrophils phagocytic capacity were noted; moreover, the tested substances did not induce liver architectural disturbances. The obtained systems provided a delayed release of zinc, and showed good biocompatibility in rats.     

Functional Additive Mixed Models

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, for example, spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well, and also scales to larger datasets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.     

Functional Generalized Additive Models

We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F( ·, ·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as by Müller and Yao (2008 Müller, H.G., and Yao, F. (2008), “Functional Additive Models,” Journal of the American Statistical Association, 103, 1534–1544.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F( ·, ·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. The FGAM is implemented in R in the refund package. There are additional supplementary materials available online.