Control of Regioselectivity over Gold Nanocrystals of Different Surfaces for the Synthesis of 1,4‐Disubstituted Triazole through the Click Reaction

Gold nanocubes, octahedra, and rhombic dodecahedra were examined for facet‐dependent catalytic activity in the formation of triazoles. Rhombic dodecahedra gave 100 % regioselective 1,4‐triazoles. The product yield was increased by decreasing the particle size. However, a mixture of 1,4‐ and 1,5‐triazoles was obtained in lower yields when cubes and octahedra of similar sizes were used. The lowest Au‐atom density on the {110} surface and largest unsaturated coordination number of surface Au atoms may explain their best catalytic efficiency and product regioselectivity. Various spectroscopic techniques were employed to verify the formation of the Au–acetylide intermediate and establish the reaction mechanism, in which phenylacetylene binds to the Au {110} surface through the terminal‐binding mode to result in the exclusive formation of 1,4‐triazoles. The smallest rhombic dodecahedra can give diverse 1,4‐disubstituted triazoles in good yields by coupling a wide variety of alkynes and organic halides.     

Silica nanowires: Growth,integration, and sensing applications

This review (with 129 refs.) gives an overview on how the integration of silica nanowires (NWs) into micro-scale devices has resulted, in recent years, in simple yet robust nano-instrumentation with improved performance in targeted application areas such as sensing. This has been achieved by the use of appropriate techniques such as di-electrophoresis and direct vapor-liquid-growth phenomena, to restrict the growth of NWs to site-specific locations. This also has eliminated the need for post-growth processing and enables nanostructures to be placed on pre-patterned substrates. Various kinds of NWs have been investigated to determine how their physical and chemical properties can be tuned for integration into sensing structures. NWs integrated onto interdigitated micro-electrodes have been applied to the determination of gases and biomarkers. The technique of directly growing NWs eliminates the need for their physical transfer and thus preserves their structure and performance, and further reduces the costs of fabrication. The biocompatibility of NWs also has been studied with respect to possible biological applications. This review addresses the challenges in growth and integration of NWs to understand related mechanism on biological contact or gas exposure and sensing performance for personalized health and environmental monitoring. Figure

Silica nanowires decorated micro-electrodes for sensing application     

Prospective virtual screening for novel p53–MDM2 inhibitors using ultrafast shape recognition

The p53 protein, known as the guardian of genome, is mutated or deleted in approximately 50 % of human tumors. In the rest of the cancers, p53 is expressed in its wild-type form, but its function is inhibited by direct binding with the murine double minute 2 (MDM2) protein. Therefore, inhibition of the p53–MDM2 interaction, leading to the activation of tumor suppressor p53 protein presents a fundamentally novel therapeutic strategy against several types of cancers. The present study utilized ultrafast shape recognition (USR), a virtual screening technique based on ligand–receptor 3D shape complementarity, to screen DrugBank database for novel p53–MDM2 inhibitors. Specifically, using 3D shape of one of the most potent crystal ligands of MDM2, MI-63, as the query molecule, six compounds were identified as potential p53–MDM2 inhibitors. These six USR hits were then subjected to molecular modeling investigations through flexible receptor docking followed by comparative binding energy analysis. These studies suggested a potential role of the USR-selected molecules as p53–MDM2 inhibitors. This was further supported by experimental tests showing that the treatment of human colon tumor cells with the top USR hit, telmisartan, led to a dose-dependent cell growth inhibition in a p53-dependent manner. It is noteworthy that telmisartan has a long history of safe human use as an approved anti-hypertension drug and thus may present an immediate clinical potential as a cancer therapeutic. Furthermore, it could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53–MDM2 inhibitors against variety of cancers. Importantly, the present study demonstrates that the adopted USR-based virtual screening protocol is a useful tool for hit identification in the domain of small molecule p53–MDM2 inhibitors.     

Solid‐State NMR and DFT Combined for the Surface Study of Functionalized Silicon Nanoparticles

Silicon nanoparticles (NPs) serve a wide range of optical, electronic, and biological applications. Chemical grafting of various molecules to Si NPs can help to passivate their reactive surfaces, “fine‐tune” their properties, or even give them further interesting features. In this work, ¹H, ¹³C, and ²⁹Si solid‐state NMR spectroscopy has been combined with density functional theory calculations to study the surface chemistry of hydride‐terminated and alkyl‐functionalized Si NPs. This combination of techniques yields assignments for the observed chemical shifts, including the contributions resulting from different surface planes, and highlights the presence of physisorbed water. Resonances from near‐surface ¹³C nuclei were shown to be substantially broadened due to surface disorder and it is demonstrated that in an ambient environment hydride‐terminated Si NPs undergo fast back‐bond oxidation, whereas long‐chain alkyl‐functionalized Si NPs undergo slow oxidation. Furthermore, the combination of NMR spectroscopy and DFT calculations showed that the employed hydrosilylation reaction involves anti‐Markovnikov addition of the 1‐alkene to the surface of the Si NPs.     

Particle-induced bridging in immiscible polymer blends

Pickering emulsions are emulsions whose drops are stabilized against coalescence by particles adsorbed at their interface. Recent research on oil/water/particle systems shows that particles can sometimes adsorb at two oil/water interfaces. Such “bridging particles” can glue together drops of oil in water or vice versa. We hypothesize that the same effect should apply in immiscible polymer blends with droplet-matrix morphologies, viz., added particles should glue together drops and give rise to particle-bridged drop clusters. We test this hypothesis in PIB-in-PDMS blends [PIB, poly(isobutylene); PDMS, poly(dimethylsiloxane)] with fumed silica particles. Direct visualization shows that the particles can indeed induce clustering of the drops, and the blends appear to show gel-like behavior. Such gel-like behavior is confirmed by dynamic oscillatory experiments. However, we are unable to conclusively attribute the gel-like behavior to droplet clustering: Association of the fumed silica particles in the bulk, which itself causes gel-like behavior, confounds the results and prevents clear analysis of the gluing effect of the particles. We conclude that PIB/PDMS/fumed silica is not a good model system, for studying particle-containing polymer blends. We instead propose that spherical monodisperse silica particles can offer a far more convenient model system, and provide direct visual evidence of gluing of PIB drops in a PDMS matrix.     

Self-accommodation in martensite

The shape-memory effect is a phenomenon wherein an apparently plastically deformed specimen recovers all strain when heated above a critical temperature. This is observed in some crystalline solids that undergo martensitic phase transformation. The martensitic transformation is a temperature-induced, diffusionless solid-to-solid phase transformation involving a change in crystalline symmetry. Shape-memory materials are able to transform from the high-temperature austenite to the low-temperature martensite phase without any apparent change in shape. This is known as self-accommodation. Necessary and sufficient conditions that the lattice parameters of a material must satisfy for the material to form a self-accommodating microstructure are derived. The main result states that if the austenite is cubic, the material is self-accommodating if and only if the transformation is volume preserving. On the other hand, if the symmetry of the austenite is not cubic, it is not possible to construct any microstructure that is self-accommodating unless the transformation strain or the Bain strain satisfies additional, rather strict, conditions. These results show good agreement with the available experimental data. The analysis here is significantly different from previous studies because it makes no a priori assumption on the microstructure.     

Classification of Indoor Human Fall Events Using Deep Learning

Human fall identification can play a significant role in generating sensor based alarm systems, assisting physical therapists not only to reduce after fall effects but also to save human lives. Usually, elderly people suffer from various kinds of diseases and fall action is a very frequently occurring circumstance at this time for them. In this regard, this paper represents an architecture to classify fall events from others indoor natural activities of human beings. Video frame generator is applied to extract frame from video clips. Initially, a two dimensional convolutional neural network (2DCNN) model is proposed to extract features from video frames. Afterward, gated recurrent unit (GRU) network finds the temporal dependency of human movement. Binary cross-entropy loss function is calculated to update the attributes of the network like weights, learning rate to minimize the losses. Finally, sigmoid classifier is used for binary classification to detect human fall events. Experimental result shows that the proposed model obtains an accuracy of 99%, which outperforms other state-of-the-art models.     

Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform

The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca²⁺-mediated SARS-CoV-2 cellular entry and replication are noteworthy. A combination of ACE inhibitors and calcium channel blockers (CCBs), a critical line of therapy for pulmonary hypertension, has shown therapeutic relevance in COVID-19 when investigated independently. To that end, we conducted in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the CCBs and ACEi compounds to tissues implicated in COVID-19 pathogenesis.     

In Vitro Anticancer Screening,Molecular Docking and Antimicrobial Studies of Triazole-Based Nickel(II) Metal Complexes

Herein we describe the synthesis of a series of nickel(II) complexes (C1–C3) with Schiff bases (HL1–HL3) derived from 4-amino-5-mercapto-3-methyl-1,2,4-triazole and ortho/meta/para-nitrobenzaldehyde having composition [Ni(L)₂(H₂O)₂]. The obtained ligands and their complexes were characterized using physico-chemical techniques viz., elemental analysis, magnetic moment study, spectral (electronic, FT-IR, 1H-NMR) and thermal analysis. The elemental analysis and spectral analysis revealed that Schiff bases behave as monoanionic bidentate ligands towards the Ni(II) ion. Whereas, the magnetic moment study suggested the octahedral geometry of all the Ni(II) complexes. The thermal behavior of the complexes has been studied by thermogravimetric analysis and agrees well with the composition of complexes. Further, the biological activities such as antimicrobial and antifungal studies of the Schiff bases and Ni(II) complexes have been screened against bacterial species (Staphylococcus aureus and Pseudomonas aeruginosa) and fungal species (Aspergillus niger and Candida albicans) activity by MIC method, the results of which revealed that metal complexes exhibited significant antimicrobial activities than their respective ligands against the tested microbial species. Furthermore, the molecular docking technique was employed to investigate the active sites of the selected protein, which indeed helped us to screen the potential anticancer agents among the synthesized ligand and complexes. Further, these compounds have been screened for their in vitro anticancer activity using OVCAR-3 cell line. The results revealed that the complexes are more active than the ligands.