Imaging of selective nuclear receptor modulator-induced conformational changes in the nuclear receptor to allow interaction with coactivator and corepressor proteins in living cells

Selective nuclear receptor modulators (SNRMs), which are used clinically for the treatment of NR-related diseases, display mixed agonistic/antagonistic activity in a tissue-selective manner depending on the cellular concentrations of coregulator proteins, that is, coactivators and corepressors. The molecular details of the SNRM function provided us with an idea for a rational method for the high-throughput screening of SNRMs in real time in intact living cells. We have developed genetically encoded fluorescent indicators based on the principle of ligand-induced coactivator and/or corepressor recruitment to NR ligand binding domain in single living cells. We demonstrated that an SNRM induces a distinct conformational change in the NR LBD, which is different from that induced by a full agonist or antagonist, but favorable for the recruitment of a coactivator or corepressor protein to the NR. The molecular details of an SNRM binding to a NR, and the subsequently induced conformational changes and recruitment of coregulator protein(s) are important features for the understanding of SNRM action in the living body. Our fluorescent indicators are capable of distinguishing among agonists, antagonists, and SNRMs, and can therefore serve as versatile molecular sensors that predict the pharmacological character of ligands, which is important for an accurate cure of a disease.     

Iterative Learning Control Utilizing the Error Prediction Method

In this paper, iterative learning control utilizing the error prediction method is proposed for a class of linear time varying systems subjected to disturbances. Prediction of the error is done by identifying the system time varying parameters. Convergence of the proposed method is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the presence of disturbances. The effectiveness of the proposed method is presented by simulations.     

A revised viscoelastic micropolar nanofluid model with motile micro‐organisms and variable thermal conductivity

In the present study, a magnetized micropolar nanofluid and motile micro‐organism with variable thermal conductivity over a moving surface have been discussed. The mathematical modeling has been formulated using a second‐grade fluid model and a revised form of the micropolar fluid model. The governing fluid contains micro‐organisms and nanoparticles. The resulting nonlinear mathematical differential equations have been solved with the help of the homotopy analysis method. The graphical and physical features of buoyancy force, micro‐organisms, magnetic field, microrotation, and variable thermal conductivity have been discussed in detail. The numerical results for Nusselt number, motile density number, and Sherwood number are presented with the help of tables. According to the graphical effects, it is noted that the buoyancy ratio and the bioconvection parameter resist the fluid motion. An enhancement in the temperature profile is observed due to the increment in thermal conductivity. Peclet number tends to diminish the motile density profile; however, the viscoelastic parameter magnifies the motile density profile.     

Actions of viscous dissipation and Ohmic heating on bidirectional flow of a magneto-Prandtl nanofluid with prescribed heat and mass fluxes

The present contribution determines the impacts of viscous dissipation and Ohmic heating with magnetic coating on Prandtl nanofluid flow driven by an unsteady bidirectionally moveable surface. Random motion of nanoparticles and thermophoretic diffusion are elaborated through a two-phase nanofluid model. The novelty of the investigation is fortified by prescribed heat flux and prescribed mass flux mechanisms. The appropriate combination of variables leads to a system of strong nonlinear ordinary differential equations. The formulated nonlinear system is then tackled by an efficient numerical scheme, namely, the Keller–Box method. Nanoliquid-temperature and mass-concentration distributions are conferred through various plots with the impacts of miscellaneous-arising parameters. The rates of heat and mass transferences are also discussed through tables. The thermal states of the nanomaterial and mass concentration are reduced for incremental amounts of the unsteady factor, ratio parameter, elastic parameter, and Prandtl fluid parameter. Moreover, escalating amounts of the Brownian parameter, Eckert number, magnetic factor, and thermophoresis parameter enhances the temperature of the nanoliquid. An error analysis is also presented to predict the efficiency of the method used for the computational work.     

Synthesis,characterization and visible-light-driven photoelectrochemical hydrogen evolution reaction of carbazole-containing conjugated polymers

Hydrogen (H₂) is one of the most important fuel candidates and its low-cost production would necessitate the development of efficient electrocatalysts. In this study, we report the synthesis and evaluation of two new carbazole-containing polymers as organic photoelectrochemical (PEC) catalysts for hydrogen evolution reaction (HER). The synthesis of these new conjugated polymers, poly(N-(2-ethylhexyl)-3,6-carbazole-p-bisdodecyloxy-phenylene vinylene) (P1) and poly(N-(2-ethylhexyl)-3,6-carbazole-p-bis(2-ethylhexyloxy)-phenylene vinylene) (P2), was accomplished by the Horner–Emmons polymerization reaction and subsequently characterized by ¹H NMR, FTIR, diffuse reflectance UV–vis spectroscopy (DR UV–vis), scanning electron microscope (SEM) and thermogravimetric analysis (TGA). The optical band gaps of P1 and P2, derived from the onset absorption edge, were found to be 2.10 and 2.14 eV, respectively. The chronoamperometric (CA) measurements revealed that the photo-current density generated at ～0 V by P1 and P2, without the use of additional noble metal based cocatalysts or sacrificial electron donors, was ?1.8 and ?2.1 μA/cm², respectively. The enhanced PEC performance of P2 was attributed due to its narrow band gap that enhanced light harvesting ability and the larger surface area which helped in minimizing charge recombination. The experimental observations were well supported by the drastic quenching of PL emission intensity of P2. The linear sweep voltammetry (LSV) measurements showed the onset potential at around ?0.3 V for both polymers. The photocurrent density difference for P2 at ?1.2 V reached to maximum value of 0.37 mA/cm², amounting to ～25% current enhancement under illumination. Long-term stability testing via CA measurements revealed that P2 was relatively more stable than P1, which warranted its potential as photocatalyst for solar water splitting. In addition, P1 and P2 are readily soluble in common organic solvents which make them potential candidates for photovoltaic devices application.