Substrate co-doping modulates electronic metal-support interactions and significantly enhances single-atom catalysis

Transitional metal nanoparticles or atoms deposited on appropriate substrates can lead to highly economical, efficient, and selective catalysis. One of the greatest challenges is to control the electronic metal–support interactions (EMSI) between the supported metal atoms and the substrate so as to optimize their catalytic performance. Here, from first-principles calculations, we show that an otherwise inactive Pd single adatom on TiO2(110) can be tuned into a highly effective catalyst, e.g. for O2 adsorption and CO oxidation, by purposefully selected metal–nonmetal co-dopant pairs in the substrate. Such an effect is proved here to result unambiguously from a significantly enhanced EMSI. A nearly linear correlation is noted between the strength of the EMSI and the activation of the adsorbed O2 molecule, as well as the energy barrier for CO oxidation. Particularly, the enhanced EMSI shifts the frontier orbital of the deposited Pd atom upward and largely enhances the hybridization and charge transfer between the O2 molecule and the Pd atom. Upon co-doping, the activation barrier for CO oxidation on the Pd monomer is also reduced to a level comparable to that on the Pd dimer which was experimentally reported to be highly efficient for CO oxidation. The present findings provide new insights into the understanding of the EMSI in heterogeneous catalysis and can open new avenues to design and fabricate cost-effective single-atom-sized and/or nanometer-sized catalysts

Functional human T-cell immunity and osteoprotegerin ligand control alveolar bone destruction in periodontal infection

Periodontitis, a prime cause of tooth loss in humans, is implicated in the increased risk of systemic diseases such as heart failure, stroke, and bacterial pneumonia. The mechanisms by which periodontitis and antibacterial immunity lead to alveolar bone and tooth loss are poorly understood. To study the human immune response to specific periodontal infections, rye transplanted human peripheral blood lymphocytes (HuPBLs) from periodontitis patients into NOD/SCID mice. Oral challenge of HuPBL-NOD/SCID mice with Actinobacillus actinomycetemcomitans, a well-known Gram-negative anaerobic microorganism that causes human periodontitis, activates human CD4(+) T cells in the periodontium and triggers local alveolar bone destruction. Human CD4(+) T cells, but not CD8(+) T cells or B cells, are identified as essential mediators of alveolar bone destruction. Stimulation of CD4(+) T cells by A. actinomycetemcomitans induces production of osteoprotegerin ligand (OPG-L), a key modulator of osteoclastogenesis and osteoclast activation. In vivo inhibition of OPG-L function with the decoy receptor OPG diminishes alveolar bone destruction and reduces the number of peridontal osteoclasts after microbial challenge. These data imply that the molecular explanation for alveolar bone destruction observed in perio dental infections is mediated by microorganism-triggered induction of OPG-L expression on CD4(+) T cells and the consequent activation of osteoclasts. Inhibition of OPG-L may thus have therapeutic value to prevent alveolar bone and/or tooth loss in human periodontitis.open11263sciescopu

Novel SNPs polymorphism of bovine CACNA2D1 gene and their association with somatic cell score

Mastitis is a major cause of economic loss in dairy cattle. In this study, the bovine CACNA2D1 gene was taken as a candidate gene for mastitis resistance. The objective of this study was to identify single nucleotide polymorphisms (SNPs) in the bovine CACNA2D1 gene and evaluate the association of these SNPs with mastitis in cattle. Through DNA sequencing and PCR-RFLP analysis, three mutations C367400T, A496561G and G519663A were detected in the cattle CACNA2D1 gene. Altogether 240 dairy cattle of three breeds (Holstein, Simmental, and Sanhe cattle) were genotyped and allele frequencies were determined. The effects of CACNA2D1 polymorphisms on somatic cell score (SCS) were analyzed and a significant association was found between G519663A and SCS. The mean of genotype GG was significantly lower than those of genotypes AG and AA. The results of this research will be useful in further studies to determine the role of the CACNA2D1 gene in mastitis resistance and further work will be necessary to investigate whether the CACNA2D1 gene play a role in defending the host from mastitis.Key words: Association analysis, CACNA2D1 gene, dairy breeds, mastitis, somatic cell score

The Search for Higher TcT_c in Houston

It is a great pleasure to be invited to join the chorus on this auspicious occasion to celebrate Professor K. Alex Mueller's 90th birthday by Professors Annette Bussman-Holder, Hugo Keller, and Antonio Bianconi. As a student in high temperature superconductivity, I am forever grateful to Professor Alex Mueller and Dr. Georg Bednorz "for their important breakthrough in the discovery of superconductivity in the ceramic materials" in 1986 as described in the citation of their 1987 Nobel Prize in Physics. It is this breakthrough discovery that has ushered in the explosion of research activities in high temperature superconductivity (HTS) and has provided immense excitement in HTS science and technology in the ensuing decades till now. Alex has not been resting on his laurels and has continued to search for the origin of the unusual high temperature superconductivity in cuprates.Comment: Dedicated to Alex Mueller, whose "important breakthrough in the discovery of superconductivity in ceramic materials" in 1986 has changed the world of superconductivit

Artificial Topological Superconductor by the Proximity Effect

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An oxidized magnetic Au single atom on doped TiO2(110) becomes a high performance CO oxidation catalyst due to the charge effect

Catalysis using gold nanoparticles supported on oxides has been under extensive investigation for many important application processes. However, how to tune the charge state of a given Au species to perform a specific chemical reaction, e.g. CO oxidation, remains elusive. Here, using first-principles calculations, we show clearly that an intrinsically inert Au anion deposited on oxygen-deficient TiO2(110) (Au@TiO2(110)) can be tuned and optimized into a highly effective single atom catalyst (SAC), due to the depletion of the d-orbital by substrate doping. Particularly, Ni- and Cu-doped Au@TiO2 complexes undergo a reconstruction driven by one of the two dissociated O atoms upon CO oxidation. The remaining O atom heals the surface oxygen vacancy and results in a stable bow-shaped surface “O–Au–O” species; thereby the highly oxidized Au single atom now exhibits magnetism and dramatically enhanced activity and stability for O2 activation and CO oxidation, due to the emergence of high density of states near the Fermi level. Based on further extensive calculations, we establish the “charge selection rule” for O2 activation and CO oxidation on Au: the positively charged Au SAC is more active than its negatively charged counterpart for O2 activation, and the more positively charged the Au, the more active it is

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Shaping bursting by electrical coupling and noise

Gap-junctional coupling is an important way of communication between neurons and other excitable cells. Strong electrical coupling synchronizes activity across cell ensembles. Surprisingly, in the presence of noise synchronous oscillations generated by an electrically coupled network may differ qualitatively from the oscillations produced by uncoupled individual cells forming the network. A prominent example of such behavior is the synchronized bursting in islets of Langerhans formed by pancreatic \beta-cells, which in isolation are known to exhibit irregular spiking. At the heart of this intriguing phenomenon lies denoising, a remarkable ability of electrical coupling to diminish the effects of noise acting on individual cells. In this paper, we derive quantitative estimates characterizing denoising in electrically coupled networks of conductance-based models of square wave bursting cells. Our analysis reveals the interplay of the intrinsic properties of the individual cells and network topology and their respective contributions to this important effect. In particular, we show that networks on graphs with large algebraic connectivity or small total effective resistance are better equipped for implementing denoising. As a by-product of the analysis of denoising, we analytically estimate the rate with which trajectories converge to the synchronization subspace and the stability of the latter to random perturbations. These estimates reveal the role of the network topology in synchronization. The analysis is complemented by numerical simulations of electrically coupled conductance-based networks. Taken together, these results explain the mechanisms underlying synchronization and denoising in an important class of biological models