Synthesis and Evaluation of a Schiff-Based Fluorescent Chemosensors for the Selective and Sensitive Detection of Cu<Superscript>2+</Superscript> in Aqueous Media with Fluorescence Off-On Responses

Copper being an essential nutrient; also pose a risk for human health in excessive amount. A simple and convenient method for the detection of trace amount of copper was employed using an optical probe R1 based on Schiff base. The probe was synthesized by Schiff base condensation of benzyl amine and 2-hydroxy-1-napthaldehyde and characterized by single X-ray diffraction, ¹H NMR and FTIR. By screening its fluorescence response in a mixture of DMSO and H₂O (20:80, v/v) R1 displayed a pronounced enhancement in fluorescence only upon treatment with copper. Other examined metal ions such as alkali, alkaline and transition had no influence. Within a wide pH range 5–12 R1 could selectively detect copper by interrupting ICT mechanism that results in CHEF. From Job’s plot analysis a 2:1 binding stoichiometry was revealed. The fluorescence response was linear in the range 1–10?×?10^?9 M with detection limit 30?×?10^?9 M. Association constant was determined as 1?×?10¹¹ M^?2 by Benesi-Hilderbrand plot. As a fast responsive probe it possesses good reproducibility and was employed for detection of copper in different water samples.     

Infection Dynamics of ATG8 in Leishmania: Balancing Autophagy for Therapeutics

In many regions of the world, Leishmaniasis is a cause of substantial mortality and ailment. Due to impediment in available treatment, development of novel and effective treatments is indispensable. Significance of autophagy has been accentuated in infectious disease as well as in Leishmaniasis, and it is having capability to be manifested as a therapeutic target. By evincing autophagy as a novel therapeutic regime, this study emphasized on the critical role of ATG4.1-ATG8 and ATG5-ATG12 complexes in Leishmania species. The objective here was to identify ATG8 as a potential therapeutic target in Leishmania. R71T, P56E, R18P are the significant mutations which shows detrimental effect on ATG8 while Arg276, Arg73, Cys75 of ATG4.1 and Val88, Pro89, Glu116, Asn117, and Gly120 are interacting residues of ATG8. Along with this, we also bring into spotlight an enticing role of Thiabendazole derivatives that interferes with the survival mechanisms by targeting ATG8. Further, the study claims that thiabendazole can be a potential drug candidate to target autophagy process in the infectious disease Leishmaniasis.     

Microorganisms swimming through radiative Sutterby nanofluid over stretchable cylinder: Hydrodynamic effect

In the present article, radiative Sutterby nanofluid flow over a stretchable cylinder is considered. The suspended swimming microorganisms have been deliberated in the fluid analysis. Different processes such as Brownian motion, thermophoresis, Joules heating, and viscous dissipation have been inspected in the presences of stratification parameters. The solutions for flow profiles have been obtained via optimal homotopy analysis method. Impacts of different physical involved variables on non-dimensional velocity, temperature, nanofluid concentration, and concentration of density of swimming microorganisms have been debated. Coefficient of skin friction, local Nusselt number, Sherwood number, and density of motile organisms have been calculated. The results reveal that Sutterby fluid parameter enhances the skin friction and has a reverse impact on the velocity, while an increase in stratification causes a declination in the flow boundary layers. The temperature of the flow is also seen to be boosted by the increment in Brownian motion parameter. Analysis of entropy generation shows that the concentration difference parameter maximizes the entropy and minimizes the dimensionless Bejan number.     

Optimization of the numerical treatment of the Darcy–Forchheimer flow of Ree–Eyring fluid with chemical reaction by using artificial neural networks

In this study, Darcy Forchheimer flow paradigm, which is a useful paradigm in fields such as petroleum engineering where high flow velocity effects are common, has been analyzed with artificial intelligence approach. In this context, first of all, Darcy–Forchheimer flow of Ree–Eyring fluid along a permeable stretching surface with convective boundary conditions has been examined and heat and mass transfer mechanisms have been investigated by including the effect of chemical process, heat generation/absorption, and activation energy. Cattaneo–Christov heat flux model has been used to analyze heat transfer properties. Within the scope of optimizing Darcy–Forchheimer flow of Ree–Eyring fluid; three different artificial neural network models have been developed to predict Nusselt number, Sherwood number, and skin friction coefficient values. The developed artificial neural network model has been able to predict Nusselt number, Sherwood number, and skin friction coefficient values with high accuracy. The findings obtained as a result of the study showed that artificial neural networks are an ideal tool that can be used to model Darcy–Forchheimer Ree–Eyring fluid flow towards a permeable stretch layer with activation energy and a convective boundary condition.