A gadolinium-based magnetic ionic liquid for supramolecular dispersive liquid–liquid microextraction followed by HPLC/UV for the determination of favipiravir in human plasma

Favipiravir is a potential antiviral medication that has been recently licensed for Covid-19 treatment. In this work, a gadolinium-based magnetic ionic liquid was prepared and used as an extractant in dispersive liquid–liquid microextraction (DLLME) of favipiravir in human plasma. The high enriching ability of DLLME allowed the determination of favipiravir in real samples using HPLC/UV with sufficient sensitivity. The effects of several variables on extraction efficiency were investigated, including type of extractant, amount of extractant, type of disperser and disperser volume. The maximum enrichment was attained using 50 mg of the Gd-magnetic ionic liquid (MIL) and 150 μl of tetrahydrofuran. The Gd-based MIL could form a supramolecular assembly in the presence of tetrahydrofuran, which enhanced the extraction efficiency of favipiravir. The developed method was validated according to US Food and Drug Administration bioanalytical method validation guidelines. The coefficient of determination was 0.9999, for a linear concentration range of 25 to 1.0 × 10⁵ ng/ml. The percentage recovery (accuracy) varied from 99.83 to 104.2%, with RSD values (precision) ranging from 4.07 to 11.84%. The total extraction time was about 12 min and the HPLC analysis time was 5 min. The method was simple, selective and sensitive for the determination of favipiravir in real human plasma.     

Furan Analog of the Alkaloid Dubiamine Based on 5-Hydroxymethylfurfurol

Chemistry of Natural Compounds -     

(O-Si)-Chelate acetic and benzoic acid N-(fluorosilylmethyl)amides: synthesis and structure

Russian Chemical Bulletin - New representatives of (O-Si)-chelate compounds, N-(fluorosilyl)methyl derivatives of N-methylacetamide, N-methylbenzamide, N-phenylacetamide, and N-phenylbenzamide,...     

Nonlinear Optical Properties of Novel Metallophthalocyanines

Journal of Applied Spectroscopy - Detailed measurements of nonlinear optical properties and optical limiting for four phthalocyanine (Pc) derivatives (PcCo, PcCu, PcMn, and PcSi) are reported. The...     

Block GPBi-CG method for solving nonsymmetric linear systems with multiple right-hand sides and its convergence analysis

Numerical Algorithms - In this paper, the block generalized product-type bi-conjugate gradient (GPBi-CG) method for solving large, sparse nonsymmetric linear systems of equations with multiple...     

Estimation of the Sorption Activity of Silver Nanoparticles on Biodegradable Fibers of Natural and Artificial Origin

Russian Physics Journal - The specific features of the sorption activity of silver nanoparticles (AgNPs) on biodegradable polymers of natural (collagen) and artificial (polyamide 6.6) origin have...     

Baer sums for a natural class of monoid extensions

Semigroup Forum - It is well known that the set of isomorphism classes of extensions of groups with abelian kernel is characterized by the second cohomology group. In this paper we generalise this...     

Correction to: Impact of leg bending in the patient-specific computational fluid dynamics of popliteal stenting

Acta Mechanica Sinica - A Correction to this paper has been published: https://doi.org/10.1007/s10409-021-01066-2     

A Neural Network-Based Policy Iteration Algorithm with Global $$H^2$$ -Superlinear Convergence for Stochastic Games on Domains

In this work, we propose a class of numerical schemes for solving semilinear Hamilton–Jacobi–Bellman–Isaacs (HJBI) boundary value problems which arise naturally from exit time problems of diffusion processes with controlled drift. We exploit policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally in the \(H^2\)-norm and further demonstrate that this convergence is superlinear, by interpreting the algorithm as an inexact Newton iteration for the HJBI equation. Moreover, we construct the optimal feedback controls from the numerical value functions and deduce convergence. The numerical schemes and convergence results are then extended to oblique derivative boundary conditions. Numerical experiments on the stochastic Zermelo navigation problem are presented to illustrate the theoretical results and to demonstrate the effectiveness of the method.