A new bifunctional catalyst for tandem Heck-asymmetric dihydroxylation of olefins

A new bifunctional catalyst consisting of active palladium and osmium species anchored on silica gel through a mercaptopropyl spacer and a cinchona alkaloid respectively has been prepared for the first time and used in the heterogeneous tandem Heck-asymmetric dihydroxylation of olefins to afford diols with excellent yields and enantiomeric excesses (ee's) in presence of N-methylmorpholine N-oxide or K3Fe(CN)6 as cooxidants.     

Identification of archaeal proteins that affect the exosome function in vitro

Background  

The archaeal exosome is formed by a hexameric RNase PH ring and three RNA binding subunits and has been shown to bind and degrade RNA in vitro. Despite extensive studies on the eukaryotic exosome and on the proteins interacting with this complex, little information is yet available on the identification and function of archaeal exosome regulatory factors.     

Modulation of humoral immune response to oral BCG vaccination by Mycobacterium bovis BCG Moreau Rio de Janeiro (RDJ) in healthy adults

We hypothesize that the energy strategy of a cell is a key factor for determining how, or if, the immune system interacts with that cell. Cells have a limited number of metabolic states, in part, depending on the type of fuels the cell consumes. Cellular fuels include glucose (carbohydrates), lipids (fats), and proteins. We propose that the cell's ability to switch to, and efficiently use, fat for fuel confers immune privilege. Additionally, because uncoupling proteins are involved in the fat burning process and reportedly in protection from free radicals, we hypothesize that uncoupling proteins play an important role in immune privilege. Thus, changes in metabolism (caused by oxidative stresses, fuel availability, age, hormones, radiation, or drugs) will dictate and initiate changes in immune recognition and in the nature of the immune response. This has profound implications for controlling the symptoms of autoimmune diseases, for preventing graft rejection, and for targeting tumor cells for destruction.     

The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices

We consider the eigenvalues and eigenvectors of finite, low rank perturbations of random matrices. Specifically, we prove almost sure convergence of the extreme eigenvalues and appropriate projections of the corresponding eigenvectors of the perturbed matrix for additive and multiplicative perturbation models.The limiting non-random value is shown to depend explicitly on the limiting eigenvalue distribution of the unperturbed random matrix and the assumed perturbation model via integral transforms that correspond to very well-known objects in free probability theory that linearize non-commutative free additive and multiplicative convolution. Furthermore, we uncover a phase transition phenomenon whereby the large matrix limit of the extreme eigenvalues of the perturbed matrix differs from that of the original matrix if and only if the eigenvalues of the perturbing matrix are above a certain critical threshold. Square root decay of the eigenvalue density at the edge is sufficient to ensure that this threshold is finite. This critical threshold is intimately related to the same aforementioned integral transforms and our proof techniques bring this connection and the origin of the phase transition into focus. Consequently, our results extend the class of ‘spiked’ random matrix models about which such predictions (called the BBP phase transition) can be made well beyond the Wigner, Wishart and Jacobi random ensembles found in the literature. We examine the impact of this eigenvalue phase transition on the associated eigenvectors and observe an analogous phase transition in the eigenvectors. Various extensions of our results to the problem of non-extreme eigenvalues are discussed.     

Anti-Inflammatory and Anti-Rheumatic Potential of Selective Plant Compounds by Targeting TLR-4/AP-1 Signaling: A Comprehensive Molecular Docking and Simulation Approaches

Plants are an important source of drug development and numerous plant derived molecules have been used in clinical practice for the ailment of various diseases. The Toll-like receptor-4 (TLR-4) signaling pathway plays a crucial role in inflammation including rheumatoid arthritis. The TLR-4 binds with pro-inflammatory ligands such as lipopolysaccharide (LPS) to induce the downstream signaling mechanism such as nuclear factor κappa B (NF-κB) and mitogen activated protein kinases (MAPKs). This signaling activation leads to the onset of various diseases including inflammation. In the present study, 22 natural compounds were studied against TLR-4/AP-1 signaling, which is implicated in the inflammatory process using a computational approach. These compounds belong to various classes such as methylxanthine, sesquiterpene lactone, alkaloid, flavone glycosides, lignan, phenolic acid, etc. The compounds exhibited different binding affinities with the TLR-4, JNK, NF-κB, and AP-1 protein due to the formation of multiple hydrophilic and hydrophobic interactions. With TLR-4, rutin had the highest binding energy (−10.4 kcal/mol), poncirin had the highest binding energy (−9.4 kcal/mol) with NF-κB and JNK (−9.5 kcal/mol), respectively, and icariin had the highest binding affinity (−9.1 kcal/mol) with the AP-1 protein. The root means square deviation (RMSD), root mean square fraction (RMSF), and radius of gyration (RoG) for 150 ns were calculated using molecular dynamic simulation (MD simulation) based on rutin’s greatest binding energy with TLR-4. The RMSD, RMSF, and RoG were all within acceptable limits in the MD simulation, and the complex remained stable for 150 ns. Furthermore, these compounds were assessed for the potential toxic effect on various organs such as the liver, heart, genotoxicity, and oral maximum toxic dose. Moreover, the blood–brain barrier permeability and intestinal absorption were also predicted using SwissADME software (Lausanne, Switzerland). These compounds exhibited promising physico-chemical as well as drug-likeness properties. Consequently, these selected compounds portray promising anti-inflammatory and drug-likeness properties.     

Graph spectra and the detectability of community structure in networks

We study networks that display community structure--groups of nodes within which connections are unusually dense. Using methods from random matrix theory, we calculate the spectra of such networks in the limit of large size, and hence demonstrate the presence of a phase transition in matrix methods for community detection, such as the popular modularity maximization method. The transition separates a regime in which such methods successfully detect the community structure from one in which the structure is present but is not detected. By comparing these results with recent analyses of maximum-likelihood methods, we are able to show that spectral modularity maximization is an optimal detection method in the sense that no other method will succeed in the regime where the modularity method fails.     

The effect of data scaling on dual prices and sensitivity analysis in linear programs

In many practical situations scaling the data is necessary to solve linear programs. This note explores the relationships in translating the sensitivity analysis between the original and the scaled problems.     

Modulation of humoral immune response to oral BCG vaccination by Mycobacterium bovis BCG Moreau Rio de Janeiro (RDJ) in healthy adults

Background  

Oral administration of BCG was the route initially used by Calmette and Guérin, but was replaced by intradermal administration in virtually all countries after the Lubeck accident. However, Brazil continued to administer oral BCG Moreau RDJ, which was maintained until the mid-1970s when it was substituted by the intradermal route. Although BCG vaccination has been used in humans since 1921, little is known of the induced immune response. The aim of this study was to analyse immunological responses after oral vaccination with M. bovis BCG Moreau RDJ.