Anisotropic assembly of Ag nanoprisms

The Ag nanoprisms with controlled arrangements show distinct optical, crystallographic, and surface-enhanced Raman scattering properties depending on their orientation in the assemblies, demonstrating that the controlled assembly of anisotropic nanostructures can be utilized as a powerful tool for studying their physicochemical properties and for the creation of new classes of functional materials.     

Activation of PPAR�� induces profound multilocularization of adipocytes in adult mouse white adipose tissues

We sought to determine the effects of activation of peroxisome proliferator-activated receptor-γ (PPAR-γ) on multilocularization of adipocytes in adult white adipose tissue (WAT). Male C57BL/6 normal, db/db, and ob/ob mice were treated with agonists of PPAR-γ, PPAR-α, or β₃-adrenoceptor for 3 weeks. To distinguish multilocular adipocytes from unilocular adipocytes, whole-mounted adipose tissues were co-immunostained for perilipin and collagen IV. PPAR-γ activation with rosiglitazone or pioglitazone induced a profound change of unilocular adipocytes into smaller, multilocular adipocytes in adult WAT in a time-dependent, dose-dependent, and reversible manner. PPAR-α activation with fenofibrate did not affect the number of locules or remodeling. db/db and ob/ob obese mice exhibited less multilocularization in response to PPAR-γ activation compared to normal mice. Nevertheless, all adipocytes activated by PPAR-γ contained a single nucleus regardless of locule number. Multilocular adipocytes induced by PPAR-γ activation contained substantially increased mitochondrial content and enhanced expression of uncoupling protein-1, PPAR-γ coactivator-1-α , and perilipin. Taken together, PPAR-γ activation induces profound multilocularization and enhanced mitochondrial biogenesis in the adipocytes of adult WAT. These changes may affect the overall function of WAT.     

Anhydrous proton conducting membranes based on crosslinked graft copolymer electrolytes

A comb-like copolymer consisting of a poly(vinylidene fluoride-co-chlorotrifluoroethylene) backbone and poly(hydroxy ethyl acrylate) side chains, i.e. P(VDF-co-CTFE)-g-PHEA, was synthesized through atom transfer radical polymerization (ATRP) using CTFE units as a macroinitiator. Successful synthesis and a microphase-separated structure of the copolymer were confirmed by proton nuclear magnetic resonance (¹H NMR), FT-IR spectroscopy, and transmission electron microscopy (TEM). This comb-like polymer was crosslinked with 4,5-imidazole dicarboxylic acid (IDA) via the esterification of the –OH groups of PHEA and the –COOH groups of IDA. Upon doping with phosphoric acid (H₃PO₄) to form imidazole–H₃PO₄ complexes, the proton conductivity of the membranes continuously increased with increasing H₃PO₄ content. A maximum proton conductivity of 0.015 S/cm was achieved at 120 °C under anhydrous conditions. In addition, these P(VDF-co-CTFE)-g-PHEA/IDA/H₃PO₄ membranes exhibited good mechanical properties (765 MPa of Young's modulus), and high thermal stability up to 250 °C, as determined by a universal testing machine (UTM) and thermal gravimetric analysis (TGA), respectively.     

Adsorption of 1,3‐Benzenedithiol and 1,3‐Benzenedimethanethiol on Gold Surfaces

The adsorption characteristics of 1,3‐benzenedithiol (1,3‐BDT) and 1,3‐benzenedimethanethiol (1,3‐BDMT) on Au surfaces are investigated by means of surface‐enhanced Raman scattering, UV/Vis absorption spectroscopy, and cyclic voltammetry (CV). 1,3‐BDMT is found to adsorb via two S–Au linkages at concentrations below monolayer coverage, but to have an upright geometry as the concentration increases on Au nanoparticles. On the other hand, 1,3‐BDT is found to adsorb by forming two S–Au linkages, regardless of concentration, based on the disappearance of the ν(SH)_free stretching band. Because of the absence of the methylene unit, 1,3‐BDT appeares not to self‐assemble efficiently on Au surfaces. The UV/Vis absorption spectroscopy and CV techniques are also applied to check the formation of self‐assembled monolayers of 1,3‐BDT and 1,3‐BDMT on Au. Density functional theory calculations based on a simple adsorption model using an Au₈ cluster are performed to better understand the nature of the adsorption characteristics of 1,3‐BDT and 1,3‐BDMT on Au surfaces.     

Tuning Local Coordination Environments of Manganese Single-Atom Nanozymes with Multi-Enzyme Properties for Selective Colorimetric Biosensing

Single-atom nanozymes (SAzymes) are promising in next-generation nanozymes, nevertheless, how to rationally modulate the microenvironment of SAzymes with controllable multi-enzyme properties is still challenging. Herein, we systematically investigate the relationship between atomic configuration and multi-enzymatic performances. The constructed Mn_SA−N₃-coordinated SAzymes (Mn_SA−N₃−C) exhibits much more remarkable oxidase-, peroxidase-, and glutathione oxidase-like activities than that of Mn_SA−N₄−C. Based on experimental and theoretical results, these multi-enzyme-like behaviors are highly dependent on the coordination number of single atomic Mn sites by local charge polarization. As a consequence, a series of colorimetric biosensing platforms based on Mn_SA−N₃−C SAzymes is successfully built for specific recognition of biological molecules. These findings provide atomic-level insight into the microenvironment of nanozymes, promoting rational design of other demanding biocatalysts.     

Drug-likeness scoring based on unsupervised learning

Drug-likeness prediction is important for the virtual screening of drug candidates. It is challenging because the drug-likeness is presumably associated with the whole set of necessary properties to pass through clinical trials, and thus no definite data for regression is available. Recently, binary classification models based on graph neural networks have been proposed but with strong dependency of their performances on the choice of the negative set for training. Here we propose a novel unsupervised learning model that requires only known drugs for training. We adopted a language model based on a recurrent neural network for unsupervised learning. It showed relatively consistent performance across different datasets, unlike such classification models. In addition, the unsupervised learning model provides drug-likeness scores that well separate distributions with increasing mean values in the order of datasets composed of molecules at a later step in a drug development process, whereas the classification model predicted a polarized distribution with two extreme values for all datasets presumably due to the overconfident prediction for unseen data. Thus, this new concept offers a pragmatic tool for drug-likeness scoring and further can be applied to other biochemical applications.

A new quantification method of drug-likeness based on unsupervised learning. The method only uses drug molecules as training set without any non-drug-like molecules.     

Recent Advances in Divergent Synthetic Strategies for Indole-Based Natural Product Libraries

Considering the potential bioactivities of natural product and natural product-like compounds with highly complex and diverse structures, the screening of collections and small-molecule libraries for high-throughput screening (HTS) and high-content screening (HCS) has emerged as a powerful tool in the development of novel therapeutic agents. Herein, we review the recent advances in divergent synthetic approaches such as complexity-to-diversity (Ctd) and biomimetic strategies for the generation of structurally complex and diverse indole-based natural product and natural product-like small-molecule libraries.     

Solvent effects on resonant first hyperpolarizabilities and Raman and hyper-Raman spectra of DANS and a water-soluble analog

The two-photon-resonant first hyperpolarizabilities associated with hyper-Rayleigh and hyper-Raman scattering are reported for 4-dimethylamino-4-nitrostilbene in 1,4-dioxane, dichloromethane, acetonitrile, and methanol, and for an ionic analog, 4-N,N-bis(6-(N,N,N-trimethylammonium)-hexyl)amino-4-nitrostilbene dibromide in methanol and water. Resonance Raman and hyper-Raman excitation profiles are also measured and modeled. The resonance Raman and hyper-Raman spectra show very similar relative intensities which do not vary much as the excitation frequency is tuned across the lowest-energy strong linear absorption band, suggesting that a single resonant electronic state dominates the one- and two-photon absorptions in this region. The absorption, resonance Raman, and hyper-Raman profiles can be simulated reasonably well with a common set of parameters. The peak resonant (absolute value of beta)2, measured by hyper-Rayleigh scattering, varies by about 50% over the range of solvents examined and shows a weak correlation with the linear absorption maximum, with the redder-absorbing systems exhibiting larger peak hyperpolarizabilities. The experimental hyper-Rayleigh intensities are higher than those calculated, possibly reflecting contributions from nonresonant electronic states.     

Expression of a supramolecular complex at a multivalent interface

The multivalent binding of a supramolecular complex at a multivalent host surface by combining the orthogonal beta-cyclodextrin (CD) host-guest and metal ion-ethylenediamine coordination motifs is described. As a heterotropic, divalent linker, an adamantyl-functionalized ethylenediamine derivative was used. This was complexed with Cu(II) or Ni(II). The binding of the complexes to a CD self-assembled monolayer (SAM) was studied as a function of pH by means of surface plasmon resonance (SPR) spectroscopy. A heterotropic, multivalent binding model at interfaces was used to quantify the multivalent enhancement at the surface. The Cu(II) complex showed divalent binding to the CD surface with an enhancement factor higher than 100 relative to the formation of the corresponding divalent complex in solution. Similar behavior was observed for the Ni(II) system. Although the Ni(II) system could potentially be trivalent, only divalent binding was observed at the CD SAMs, which was confirmed by desorption experiments.     

Bi2Sn2O7 nanoparticles attached to SnO2 nanowires and used as catalysts

We introduce a simple method of synthesizing SnO₂ nanowire-Bi₂Sn₂O₇ nanoparticle composites based on the principle that SnO₂ nanowires can be grown by using Bi as catalysts. A mixture of Bi and Sn powders was thermally evaporated, and the effects of growth temperature on the morphology and structure of the products were investigated. We obtained Bi₂Sn₂O₇-tipped SnO₂ nanowires at 700 °C through a vapor–liquid–solid (VLS) process, whereas particle-free SnO₂ nanowires were produced at higher temperatures. We have investigated the oxygen sensing properties of the as-synthesized product.