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.     

Polymer 4D printing: Advanced shape-change and beyond

4D printing is an exciting branch of additive manufacturing. It relies on established 3D printing techniques to fabricate objects in much the same way. However, structures which fall into the 4D printed category have the ability to change with time, hence the “extra dimension.” The common perception of 4D printed objects is that of macroscopic single-material structures limited to point-to-point shape change only, in response to either heat or water. However, in the area of polymer 4D printing, recent advancements challenge this understanding. A host of new polymeric materials have been designed which display a variety of wonderful effects brought about by unconventional stimuli, and advanced additive manufacturing techniques have been developed to accommodate them. As a result, the horizons of polymer 4D printing have been broadened beyond what was initially thought possible. In this review, we showcase the many studies which evolve the very definition of polymer 4D printing, and reveal emerging areas of research integral to its advancement.     

Development and validation of LC–MS/MS method for amlexanox in rat plasma and its application in preclinical pharmacokinetics

Amlexanox, an anti-inflammatory and anti-allergic agent, has been widely used clinically for the treatment of canker sores, asthma, and allergic rhinitis. Recently, amlexanox has received considerable attention in curing nonalcoholic fatty liver diseases and hepatitis virus infection. Herein, we first established a sensitive high-performance liquid chromatography-tandem mass spectrum (LC–MS/MS) method for the determination of amlexanox in rat plasma. Propranolol was used as the internal standard (IS). Using a simple protein precipitation method, the amlexanox and IS were separated with Capcell Pak C18 column (2.0 × 50 mm, 5 μm) and eluted with water and acetonitrile each containing 0.1% formic acid using gradient elution condition at a flow rate of 0.4 mL·min⁻¹. Amlexanox and IS were detected by a triple quadrupole mass in multiple reactive monitoring (MRM) under the transitions of m/z 299.2 → 281.2 and m/z 259.9 → 116.1 with positive electrospray ionization, respectively. The calibration curves of amlexanox were established with the range of 50 to 2000 ng·mL⁻¹ (r² > 0.99). The validation method consisted of selectivity, accuracy, precision, carryover effect, matrix effect, recovery, dilution effect, and stability. The fully validated method was successfully applied to the pharmacokinetic study of amlexanox in Wistar rats.     

Insights into MWCNTs/polyimide nanocomposites: from synthesis to application as free-standing flexible electrodes in low-cost micro-supercapacitors

In the pursuit to enlarge the library of polyimide materials for energy applications, new polyimide/MWCNTs composite films have been developed by MWCNTs-assisted polycondensation reaction of a hydroxyl and triphenylmethane-containing diamine with benzophenone tetracarboxylic dianhydride targeting to highlight their electrical storage capability as flexible electrodes in micro-supercapacitors (mSCs). The Fourier-transform infrared spectroscopy, proton nuclear magnetic resonance, UV–vis, fluorescence, and Raman spectroscopies were used to demonstrate the evolution of interfacial interactions between MWCNTs and the precursors (diamine monomer and intermediate polyamidic acid) and polyimide matrix that proved to be the origin of MWCNTs homogeneous dispersion. Thus, composite films incorporating 1, 3, 5, and 10 w.t.% MWCNTs were obtained and thoroughly investigated with regard to their morphology, mechanical behavior, thermal stability, and electrical conductivity. The electrochemical performance of these composites was first analyzed in a classical three-electrode cell by cyclic voltammetry and galvanostatic charge-discharge in both aqueous and organic electrolyte systems. By far, the best electrical storage capacity was obtained with the composite polyimide film containing 10% MWCNTs that was further used as both active material and current collector in a flexible symmetric mSC realized by a straightforward and low-cost procedure. In the attempt to better exploit the advantages of this composite film, it was layered with a graphite-containing paint and tested as an electrode in a flexible mSC, which provided satisfactory results. To our knowledge, this is the first report on the electrical charge storage capability of a polyimide/MWCNTs free-standing film as a flexible electrode in mSCs, which do not require time- and resource-consuming processing steps.     

An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

Application of microcrystalline cellulose as an efficient and cheap sorbent for the extraction of metoprolol from plasma and wastewater before HPLC–MS/MS determination

A dispersive solid-phase extraction method based on a new sorbent has been performed on plasma and wastewater samples to determine metoprolol by high-performance liquid chromatography–tandem mass spectrometry. In this study, the analyte was adsorbed from the samples onto microcrystalline cellulose as a green and efficient sorbent and then eluted for use in the determination step. In the mass spectrometer, the analyte was detected in the positive mode and selectivity of the analysis was increased by sequential mass analysis through multiple reaction monitoring. All of the effective parameters in the extraction of metoprolol from plasma and wastewater were optimized. Under optimal conditions the method was linear in the ranges of 1–1,000 and 0.1–1,000 ng/ml in plasma and wastewater samples, respectively. The detection limits of the method were 0.30 and 0.03 ng/ml in plasma and wastewater samples, respectively. The data showed that the method provides low detection limit, wide linear range, good precision and high extraction recovery. Finally several plasma and wastewater samples were successfully analyzed using the method. The use of a small amount of a green and inexpensive sorbent and a low volume of plasma without the need for further pretreatment steps are the main advantages of the method.     

Anti-fibrosis attributes: UHPLC-MS/MS-based pharmacokinetics profiling of a novel autotaxin inhibitor with excellent in vivo efficacy in rat

3,4-Difluorobenzyl(1-ethyl-5-(4-((4-hydroxypiperidin-1-yl)-methyl)thiazol-2-yl)-1H-indol-3-yl)carbamate (NAI59), a small molecule with outstanding therapeutic effectiveness to anti-pulmonary fibrosis, was developed as an autotaxin inhibitor candidate compound. To evaluate the pharmacokinetics and plasma protein binding of NAI59, a UPLC–MS/MS method was developed to quantify NAI59 in plasma and phosphate-buffered saline. The calibration curve linearity ranged from 9.95 to 1990.00 ng/mL in plasma. The accuracy was −6.8 to 5.9%, and the intra- and inter-day precision was within 15%. The matrix effect and recovery, as well as dilution integrity, were within the criteria. The chromatographic and mass spectrometric conditions were also feasible to determine phosphate-buffered saline samples, and it has been proved that this method exhibits good precision and accuracy in the range of 9.95–497.50 ng/mL in phosphate-buffered saline. This study is the first to determine the pharmacokinetics, absolute bioavailability, and plasma protein binding of NAI59 in rats using this established method. Therefore, the pharmacokinetic profiles of NAI59 showed a dose-dependent relationship after oral administration, and the absolute bioavailability in rats was 6.3%. In addition, the results of protein binding showed that the combining capacity of NAI59 with plasma protein attained 90% and increased with the increase in drug concentration.     

Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.