Integration of Metal Catalysis and Organocatalysis in a Metal Nanocluster with Anchored Proline.

Chiral metal nanoclusters have recently been attracting great attention. It is challenging to realize asymmetric catalysis via atomically precise metal nanoclusters. Herein, we report the synthesis and total structure determination of chiral clusters [Au7Ag8(dppf)3(l-/d-proline)6](BF4)2 (l-/d-Au7Ag8). Superatomic clusters l-/d-Au7Ag8 display intense and mirror-image Cotton effects in their CD spectra. Density functional theory (DFT) calculations were carried out to understand the correlation between electronic structures and the optical activity of the enantiomeric pair. Surprisingly, the incorporation of proline in a metal nanocluster can significantly promote the catalytic efficiency in asymmetric Aldol reactions. The increase of catalytic activity of Au7Ag8 in comparison with organocatalysis by proline is attributed to the cooperative effect of the metal core and prolines, showing the advantages of the integration of metal catalysis and organocatalysis in a metal nanocluster.

Identification of Key Biomarkers and Candidate Molecules in Non-Small-Cell Lung Cancer by Integrated Bioinformatics Analysis.

Background: Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis. Methods: From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools. Results: We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma. Conclusions: The results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.

Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning.

The mechanism of transcriptional activation/repression of the nuclear receptors (NRs) involves two main conformations of the NR protein, namely, the active (agonistic) and inactive (antagonistic) conformations. Binding of agonists or antagonists to the ligand-binding pocket (LBP) of NRs can regulate the downstream signaling pathways with different physiological effects. However, it is still hard to determine the molecular type of a LBP-bound ligand because both the agonists and antagonists bind to the same position of the protein. Therefore, it is necessary to develop precise and efficient methods to facilitate the discrimination of agonists and antagonists targeting the LBP of NRs. Here, combining structural and energetic analyses with machine-learning (ML) algorithms, we constructed a series of structure-based ML models to determine the molecular category of the LBP-bound ligands. We show that the proposed models work robustly and with high accuracy (ACC > 0.9) for determining the category of molecules derived from docking-based and crystallized poses. Furthermore, the models are also capable of determining the molecular category of ligands with dual opposite functions on different NRs (i.e., working as an agonist in one NR target, whereas functioning as an antagonist in another) with reasonable accuracy. The proposed method is expected to facilitate the determination of the molecular properties of ligands targeting the LBP of NRs with structural interpretation.

Publisher Correction: Atomically engineering activation sites onto metallic 1T-MoS2 catalysts for enhanced electrochemical hydrogen evolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Measuring the areal density of nanomaterials by electron energy-loss spectroscopy.

Thickness measurements of nanomaterials are usually performed using transmission electron microscopy (TEM) techniques such as convergent beam electron diffraction (CBED) patterns analysis and the log-ratio method based on electron energy-loss spectroscopy (EELS) spectrum. However, it is challenging to obtain both the thickness and elemental information, especially in non-crystalline materials or for very thin samples. In this work, we establish a series of procedures to calculate the areal density of the material by directly measuring the inelastic scattering probability in a thin sample. Core-loss EELS are fit with a quantitative model to extract atomic areal density. Knowledge of one of the parameters (volume density or sample thickness) allows a measurement of the other. The absolute error between the known thicknesses and those measured was less than 4% using two-dimensional materials with a well-defined thickness as test samples, which is much better than the log-ratio method for very thin samples. One promising advantage of this method is the thickness/areal density determination in mixed phase/element systems. We use Ag-Co bimetallic triangles and black rutile as examples to calculate the thickness map in mixture systems in different cases. We also demonstrate this technique can be applied to measure the argon gas density in spherical cavities. This allows a temperature vs pressure curve to be obtained and illustrates the unique capability of this technique.

Atomically engineering activation sites onto metallic 1T-MoS2 catalysts for enhanced electrochemical hydrogen evolution.

Engineering catalytic sites at the atomic level provides an opportunity to understand the catalyst's active sites, which is vital to the development of improved catalysts. Here we show a reliable and tunable polyoxometalate template-based synthetic strategy to atomically engineer metal doping sites onto metallic 1T-MoS2, using Anderson-type polyoxometalates as precursors. Benefiting from engineering nickel and oxygen atoms, the optimized electrocatalyst shows great enhancement in the hydrogen evolution reaction with a positive onset potential of ~ 0 V and a low overpotential of -46 mV in alkaline electrolyte, comparable to platinum-based catalysts. First-principles calculations reveal co-doping nickel and oxygen into 1T-MoS2 assists the process of water dissociation and hydrogen generation from their intermediate states. This research will expand on the ability to improve the activities of various catalysts by precisely engineering atomic activation sites to achieve significant electronic modulations and improve atomic utilization efficiencies.

[V4Mo3O14(NAr)3(µ2-NAr)3]2-: the first polyarylimido-stabilized molybdovanadate cluster.

The first molybdovanadate cluster with a polyarylimido trimetal fragment, [V4Mo3O14(NAr)3(µ2-NAr)3]2-, was in situ synthesized by using (TBA)3[H3V10O28] as proton and vanadium sources. Additional aniline hydrochlorides will give rise to the formation of phenyl guanidines, which will serve as cations and proton donors to form chain-like and dimeric supermolecules via H-bonding.

A Novel TetR Family Transcriptional Regulator, CalR3, Negatively Controls Calcimycin Biosynthesis in Streptomyces chartreusis NRRL 3882.

Calcimycin is a unique ionophoric antibiotic that is widely used in biochemical and pharmaceutical applications, but the genetic basis underlying the regulatory mechanisms of calcimycin biosynthesis are unclear. Here, we identified the calR3 gene, which encodes a novel TetR family transcriptional regulator and exerts a negative effect on calcimycin biosynthesis. Disruption of calR3 in Streptomyces chartreusis NRRL 3882 led to significantly increased calcimycin and its intermediate cezomycin. Gene expression analysis showed that the transcription of calR3 and its adjacent calT gene were dramatically enhanced (30- and 171-fold, respectively) in GLX26 (ΔcalR3) mutants compared with the wild-type strains. Two CalR3-binding sites within the bidirectional calR3-calT promoter region were identified using a DNase I footprinting assay, indicating that CalR3 directly repressed the transcription of its own gene and the calT gene. In vitro electrophoretic mobility shift assays suggested that both calcimycin and cezomycin can act as CalR3 ligands to induce CalR3 to dissociate from its binding sites. These findings indicate negative feedback for the regulation of CalR3 in calcimycin biosynthesis and suggest that calcimycin production can be improved by manipulating its biosynthetic machinery.

Ferroplasmons: intense localized surface plasmons in metal-ferromagnetic nanoparticles.

Interaction of photons with matter at length scales far below their wavelengths has given rise to many novel phenomena, including localized surface plasmon resonance (LSPR). However, LSPR with narrow bandwidth (BW) is observed only in a select few noble metals, and ferromagnets are not among them. Here, we report the discovery of LSPR in ferromagnetic Co and CoFe alloy (8% Fe) in contact with Ag in the form of bimetallic nanoparticles prepared by pulsed laser dewetting. These plasmons in metal-ferromagnetic nanostructures, or ferroplasmons (FP) for short, are in the visible spectrum with comparable intensity and BW to those of the LSPRs from the Ag regions. This finding was enabled by electron energy-loss mapping across individual nanoparticles in a monochromated scanning transmission electron microscope. The appearance of the FP is likely due to plasmonic interaction between the contacting Ag and Co nanoparticles. Since there is no previous evidence for materials that simultaneously show ferromagnetism and such intense LSPRs, this discovery may lead to the design of improved plasmonic materials and applications. It also demonstrates that materials with interesting plasmonic properties can be synthesized using bimetallic nanostructures in contact with each other.