Activation and discovery of earth-abundant metal catalysts using sodium tert-butoxide

First-row, earth-abundant metals offer an inexpensive and sustainable alternative to precious-metal catalysts. As such, iron and cobalt catalysts have garnered interest as replacements for alkene and alkyne hydrofunctionalization reactions. However, these have required the use of air- and moisture-sensitive catalysts and reagents, limiting both adoption by the non-expert as well as applicability, particularly in industrial settings. Here, we report a simple method for the use of earth-abundant metal catalysts by general activation with sodium tert-butoxide. Using only robust air- and moisture-stable reagents and pre-catalysts, both known and, significantly, novel catalytic activities have been successfully achieved, covering hydrosilylation, hydroboration, hydrovinylation, hydrogenation and [2π+2π] alkene cycloaddition. This activation method allows for the easy use of earth-abundant metals, including iron, cobalt, nickel and manganese, and represents a generic platform for the discovery and application of non-precious metal catalysis

Cerebrospinal Fluid Viral Load and Intrathecal Immune Activation in Individuals Infected with Different HIV-1 Genetic Subtypes

Background: HIV-1 exhibits a high degree of genetic diversity and is presently divided into 3 distinct HIV-1 genetic groups designated major (M), non-M/non-O (N) and outlier (O). Group M, which currently comprises 9 subtypes (A-D, F-H, J and K), at least 34 circulating recombinant forms (CRFs) and several unique recombinant forms (URFs) is responsible for most of the HIV-1 epidemic. Most of the current knowledge of HIV-1 central nervous system (CNS) infection is based on subtype B. However, subtypes other than subtype B account for the majority of global HIV-1 infections. Therefore, we investigated whether subtypes have any influence on cerebrospinal fluid (CSF) markers of HIV-1 CNS infection. Methodology/Principal Findings: CSF HIV-1 RNA, CSF neopterin and CSF white blood cell (WBC) count were measured in patients infected with different HIV-1 subtypes. Using multivariate regression analysis, no differences in the CSF WBC count, neopterin and viral load were found between various HIV-1 subtypes

HIV-1 Nef Protein Structures Associated with Brain Infection and Dementia Pathogenesis

The difference between regional rates of HIV-associated dementia (HAD) in patients infected with different subtypes of HIV suggests that genetic determinants exist within HIV that influence the ability of the virus to replicate in the central nervous system (in Uganda, Africa, subtype D HAD rate is 89%, while subtype A HAD rate is 24%). HIV-1 nef is a multifunctional protein with known toxic effects in the brain compartment. The goal of the current study was to identify if specific three-dimensional nef structures may be linked to patients who developed HAD. HIV-1 nef structures were computationally derived for consensus brain and non-brain sequences from a panel of patients infected with subtype B who died due to varied disease pathologies and consensus subtype A and subtype D sequences from Uganda. Site directed mutation analysis identified signatures in brain structures that appear to change binding potentials and could affect folding conformations of brain-associated structures. Despite the large sequence variation between HIV subtypes, structural alignments confirmed that viral structures derived from patients with HAD were more similar to subtype D structures than to structures derived from patient sequences without HAD. Furthermore, structures derived from brain sequences of patients with HAD were more similar to subtype D structures than they were to their own non-brain structures. The potential finding of a brain-specific nef structure indicates that HAD may result from genetic alterations that alter the folding or binding potential of the protein

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented