Metallierung von Triisopropylsilylarsan durch Bis(tetrahydrofuran)calcium‐bis[tris(trimethylsilylmethyl)zinkat]

Metalation of Triisopropylsilylarsane with Bis(tetrahydrofuran)calcium‐bis[tris(trimethylsilylmethyl)zincate] The transmetalation of bis(trimethylsilylmethyl)zinc with distilled calcium in THF yields bis(tetrahydrofuran)calcium bis[tris‐(trimethylsilylmethyl)zincate] ( 1 ). The trialkylzincate anion appears as a bidentate ligand with Ca‐C‐Zn three‐center‐bonds. The CaC bond lengths show values of 265.5(2) and 271.7(2) pm. The metalation of triisopropylsilylarsane gives tetrakis(tetrahydrofuran)calcium [1, 3‐bis(triisopropylsilylarsanyl)‐2, 4‐bis(triisopropylsilyl)‐1, 3‐dizinca‐2, 4‐diarsacyclobutane‐2, 4‐diide] ( 2 ). The central moiety is a sligthly distorted trigonal As₂CaZn₂ bipyramid with the arsenic atoms in apical positions. The mean Ca‐As bond lengths lie with a mean value of 291.4 pm in the charakteristic region for calcium bis‐(arsanides).     

A New Bacterial Adenosine-Derived Nucleoside as an Example of RNA Modification Damage

The fields of RNA modification and RNA damage both exhibit a plethora of non-canonical nucleoside structures. While RNA modifications have evolved to improve RNA function, the term RNA damage implies detrimental effects. Based on stable isotope labelling and mass spectrometry, we report the identification and characterisation of 2-methylthio-1,N6-ethenoadenosine (ms²ϵA), which is related to 1,N6-ethenoadenine, a lesion resulting from exposure of nucleic acids to alkylating chemicals in vivo. In contrast, a sophisticated isoprene labelling scheme revealed that ms²ϵA biogenesis involves cleavage of a prenyl moiety in the known transfer RNA (tRNA) modification 2-methylthio-N6-isopentenyladenosine (ms²i⁶A). The relative abundance of ms²ϵA in tRNAs from translating ribosomes suggests reduced function in comparison to its parent RNA modification, establishing the nature of the new structure in a newly perceived overlap of the two previously separate fields, namely an RNA modification damage.     

Polynomial multivariate least‐squares regression for modeling nonlinear data applied to in‐depth characterization of chromatographic resolution

Well‐established, linear multivariate calibration methods such as multivariate least‐squares regression (MLR), principal component regression (PCR), or partial least squares (PLS) have two limitations: (i) measured data must be linearly related to the response variables and (ii) predictor variables x_{n = 1, …, N} cannot be coupled to each other. For evaluation of nonlinear data, however, these restrictions need to be overcome and thus polynomial multivariate least‐squares regression (PMLR or “response surfaces”) has been introduced here. PMLR is based on multivariate least squares but incorporates all combinations of predictor variables up to a user‐selected polynomial order (e.g., including u or v = 0). Because of the inclusion of such coupled terms and their powers, PMLR models are better adapted to model nonlinear data and can help to enhance the prediction step's accuracy and precision. PMLR has been based on MLR because it facilitates—unlike PCR or PLS—a physical and chemical interpretation of the predictors. Hence, the origins and the relevance of nonlinear and/or coupled predictors can be investigated. The details of the PMLR algorithm and its implementation are presented along with a method for model optimization utilizing gradients of response surfaces. Newly developed PMLR models up to quintic order have been applied to predict a chromatograph's peak resolution as a function of six‐instrument parameters. It has been demonstrated that PMLR is better capable than MLR and PCR to describe these nonlinear and coupled instrument parameters. In addition, the novel software tool has been utilized for model optimization to determine instrument parameters, which result in the best chromatographic resolution. Copyright © 2011 John Wiley & Sons, Ltd.     

Monitoring chemical impacts on cell cultures by means of image analyses

Many chemical processes are involved in the interactions of living cells with their environment; however, monitoring such processes often requires sophisticated analyzers. In this study, a sensing strategy based on imaging techniques has been developed to (i) enable cell discrimination based on their physical appearance such as size and shape and (ii) to build predictive models that relate the measured cell appearance to chemical parameters in their environment. Both goals aim at innovative and straightforward sensing strategies for analyzing cell–environment interactions. Image analyses offer several advantages such as the use of simpler, more robust sensors and the omission of extensive sample/sensor preparations. Imaging can analyze numerous cells and thus gains a culture representative insight rather than a potentially nonrepresentative single‐cell response. As a proof‐of‐principle application, different species of microalgae cells have been exposed to various nutrient conditions. Microalgae are known to sensitively adapt to changing nutrient conditions and could potentially become biological “probes” for chemical shifts in ecosystems. Because of considerable spreads of cell size and shapes within one class, size and shape distributions have been derived from visible images of cell cultures. It is shown that the novel image analyses are capable of discriminating different cell species based on their cell shapes and sizes. It is also demonstrated that in conjunction with the recently introduced, nonlinear multivariate “predictor surfaces”, the nutrient availability has a quantifiable impact on the cell size distributions. In this application, predictor surfaces are somewhat more precise than partial least squares. Copyright © 2012 John Wiley & Sons, Ltd.     

Slow Inversion of Coordinated Thioether Groups in SNS-Type Ruthenium Pincer Complexes

The thioether-group-containing SNS-type pincer complex [({EtSCH₂CH₂}₂NH)RuCl(H)(PPh₃)] ( 2 ) exists in three different diastereomers ( 2 a – c ). The molecular structures obtained from single crystal X-Ray diffraction studies of all three isomers reveal a difference in the relative orientation of the respective EtS-groups, while other commonly observed diastereomers as the result of cis-/trans- or fac-/mer-isomerism are not observed. Chemical exchange between the three diastereomers 2 a – c was discovered by phase-sensitive ¹H and ³¹P NOESY NMR spectroscopy, and further quantified by line shape analysis of ¹H NMR spectra. The experimentally derived averaged Gibbs energies of activation for the interconversion of the isomers (65–70 kJ/mol) are in good agreement with the results obtained from DFT calculations, which suggest an inversion of the ligating sulfur atoms, although a dissociative pathway for the configurational inversion can be competitive.     

Carbon Deposit Analysis in Catalyst Deactivation,Regeneration, and Rejuvenation

Hydrocarbon conversion catalysts suffer from deactivation by deposition or formation of carbon deposits. Carbon deposit formation is thermodynamically favored above 350 °C, even in some hydrogen-rich environments. We discuss four basic mechanisms: a carbenium-ion based mechanism taking place on acid sites of zeolites or bifunctional catalysts, a metal-induced formation of soft coke (i.e., oligomers of small olefins) on bifunctional catalysts, a radical-mediated mechanism in higher-temperature processes, and fast-growing carbon filament formation. Catalysts deactivate because carbon deposits block pores at different length scales, or directly block active sites. Some deactivated catalysts can be re-used, others can be regenerated or have to be discarded. Catalyst and process design can mitigate the effects of deactivation. New analytical tools allow for the direct observation (in some cases even under in situ or operando conditions) of the 3D-distribution of coke-type species as a function of catalyst structure and lifetime.