Palladium nanocatalysts encapsulated on porous silica @ magnetic carbon-coated cobalt nanoparticles for sustainable hydrogenations of nitroarenes, alkenes and alkynes

Palladium nanoparticles were impregnated on porous silica shell carbon-coated cobalt nanoparticles, resulting in a magnetically retrievable material that was evaluated in the catalytic hydrogenation of nitroarenes, alkenes and alkynes. The prepared material was characterized by HR-XRD, HR-TEM, elemental mapping EDX, ICP-OES and XPS analyses, revealing highly dispersed palladium nanoparticles within the porous platform that could account for the high activity observed. Mild reaction conditions, easy retrievability of the catalyst with the aid of an external magnet, recycling in four runs with a total leaching of 19 ppm (1.2 % of the initially employed Pd amount), and high stability makes this material attractive for sustainable and environmentally benign applications

Automated three-component synthesis of a library of γ-lactams

A three-component method for the synthesis of γ-lactams from commercially available maleimides, aldehydes, and amines was adapted to parallel library synthesis. Improvements to the chemistry over previous efforts include the optimization of the method to a one-pot process, the management of by-products and excess reagents, the development of an automated parallel sequence, and the adaption of the method to permit the preparation of enantiomerically enriched products. These efforts culminated in the preparation of a library of 169 γ-lactams.The authors are grateful to Ben Neuenswander for carrying out the purification of the libraries and to the National Institutes of General Medical Sciences for financial support through the University of Kansas Chemical Methodologies and Library Development center (P50 GM69663)

Enantioselective synthesis of (−)-paeonilide

The first enantioselective synthesis of (−)-paeonilide is reported. Starting from inexpensive furan-3-carboxylic acid the targeted monoterpene was obtained in 12 steps via an asymmetric cyclopropanation-lactonization cascade and a stereoselective side chain insertion at an acetal-like position

Copper Photocatalyzed Divergent Access to Organic Thio- and Isothiocyanates

We disclose a copper-photocatalyzed strategy that enables selective access to organic thiocyanates and isothiocyanates using benzylic thiocyanates as ATRA reagents. The electronic nature of the aromatic system is a crucial factor defining the outcome of the reaction for forging either the kinetic C–S or the thermodynamic C–N bonds. Mechanistic investigations support a radical pathway initiated by a reductive C–S bond cleavage of the substrates followed by a divergent inner-/outer-sphere interaction with copper depending on the electronic density of the formed intermediates. The developed protocol proceeds with high regio- and chemoselectivity and can also be applied for late-stage functionalization of bioactive molecules. The utility of the products is highlighted by their facile conversion to several building blocks that are relevant to organic synthesis

Developing a logical model of yeast metabolism

With the completion of the sequencing of genomes of increasing numbers of organisms, the focus of biology is moving to determining the role of these genes (functional genomics). To this end it is useful to view the cell as a biochemical machine: it consumes simple molecules to manufacture more complex ones by chaining together biochemical reactions into long sequences referred to as em metabolic pathways. Such metabolic pathways are not linear but often interesect to form complex networks. Genes play a fundamental role in these networks by providing the information to synthesise the enzymes that catalyse biochemical reactions. Although developing a complete model of metabolism is of fundamental importance to biology and medicine, the size and complexity of the network has proven beyond the capacity of human reasoning. This paper presents the first results of the Robot Scientist research programme that aims to automatically discover the function of genes in the metabolism of the yeast em Saccharomyces cerevisiae. Results include: (1) the first logical model of metabolism;(2) a method to predict phenotype by deductive inference; and (3) a method to infer reactions and gene function by aductive inference. We describe the em in vivo experimental set-up which will allow these em in silico predictions to be automatically tested by a laboratory robot

Combining inductive logic programming, active learning and robotics to discover the function of genes

The paper is addressed to AI workers with an interest in biomolecular genetics and also to biomolecular geneticists interested in what AI tools may do for them. The authors are engaged in a collaborative enterprise aimed at partially automating some aspects of scientific work. These aspects include the processes of forming hypotheses, devising trials to discriminate between these competing hypotheses, physically performing these trials and then using the results of these trials to converge upon an accurate hypothesis. As a potential component of the reasoning carried out by an "artificial scientist" this paper describes ASE-Progol, an Active Learning system which uses Inductive Logic Programming to construct hypothesised first-order theories and uses a CART-like algorithm to select trials for eliminating ILP derived hypotheses. In simulated yeast growth tests ASE-Progol was used to rediscover how genes participate in the aromatic amino acid pathway of Saccharomyces cerevisiae. The cost of the chemicals consumed in converging upon a hypothesis with an accuracy of around 88% was reduced by five orders of magnitude when trials were selected by ASE-Progol rather than being sampled at random. While the naive strategy of always choosing the cheapest trial from the set of candidate trials led to lower cumulative costs than ASE-Progol, both the naive strategy and the random strategy took significantly longer to converge upon a final hypothesis than ASE-Progol. For example to reach an accuracy of 80%, ASE-Progol required 4 days while random sampling required 6 days and the naive strategy required 10 days

Carbon coated magnetic nanoparticles as supports in microwave-assisted palladium catalyzed Suzuki-Miyaura couplings

A palladium bis-N-heterocyclic carbene complex was immobilized on polystyrene modified, magnetic carbon coated iron nanoparticles and evaluated in Suzuki-Miyaura cross-coupling reactions under conventional and microwave heating. Under the latter conditions, both aryl bromides and aryl chlorides could be employed as substrates at low loading of catalyst (0.2 mol%), which could be readily recovered by an external magnet and reused in at least four cycles. As a possible deactivation pathway of the catalyst, the formation of palladium nanoparticles in the course of the reaction that became encapsulated in the polystyrene matrix of the support is suggeste

Model-free functional MRI analysis based on unsupervised clustering

AbstractConventional model-based or statistical analysis methods for functional MRI (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms. However, they are not applicable in situations in which patterns of neural response are complicated and when fMRI response is unknown. In this paper the “neural gas” network is adapted and rigourosly studied for analyzing fMRI data. The algorithm supports spatial connectivity aiding in the identification of activation sites in functional brain imaging. A comparison of this new method with Kohonen’s self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative evaluations. The most important findings in this paper are: (1) both “neural gas” and the fuzzy clustering technique outperform Kohonen’s map in terms of identifying signal components with high correlation to the fMRI stimulus, (2) the “neural gas” outperforms the two other methods with respect to the quantization error, and (3) Kohonen’s map outperforms the two other methods in terms of computational expense. The applicability of the new algorithm is demonstrated on experimental data

Effect of Reaction Media on Photosensitized [2+2]- Cycloaddition of Cinnamates

The outcome of photosensitized [2+2]-cycloaddition reactions of various cinnamates has been compared in different reaction media, including homogeneous organic solutions under inert conditions, degassed water, and aerated physical gels. The reactions were performed under LED blue light (λmax=455 nm) irradiation and [Ir{dF(CF3)ppy}2(dtb-bpy)]PF6 (1.0 mol%) as photocatalyst. The processes were optimized taking into consideration solvent, gelator, and substrate. Comparative kinetics analyses, as well as the effect of the reaction media on the diastereoselectivity of the process, were evaluated during this investigation. In a number of cases, carrying out the reaction in a less polar solvent, like toluene or highly polar solvent, like water had a tremendous impact on the diastereoselectivity of the process, pointing towards an effect on the stabilization of the putative diradical intermediate in this medium. Moreover, while for reactions run in homogeneous solution oxygen needs to be excluded, no erosion in yield is observed when the photoadditions were run in aerated gel media.Deutsche ForschungsgemeinschaftElitenetzwerk BayernMinisterio de Ciencia, Innovación y Universidade