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.     

(E,E)-1,1′-[1,2-Bis(4-chlorophenyl)ethane-1,2-diyl]bis(phenyldiazene) revisited: threefold configurational disorder of (S,S), (R,R) and (S,R) isomers,a detailed critique

Crystal structures described as concomitant triclinic ( I ) and monoclinic ( II ) polymorphs of meso-(E,E)-1,1′-[1,2-bis(4-chlorophenyl)ethane-1,2-diyl]bis(phenyldiazene) [Mohamed et al. (2016). Acta Cryst. C 72 , 57–62] have been re-investigated. The published model for II was distorted due to forcing the symmetry of space group C2/c on an incomplete structure model. It is shown here to be a likely three-component superposition of S,S and R,R enantiomers with a lesser amount of the meso form. A detailed analysis of how the improbable distortion in the published model aroused suspicion and the subsequent construction of undistorted chemically and crystallographically plausible alternatives having the symmetry of Cc and C2/c is presented. For the sake of completeness, an improved model for the triclinic P structure of the meso isomer I , revised to include a minor disorder component, is also given.     

Lithium Promotes Acetylide Formation on MgO During Methane Coupling Under Non-Oxidative Conditions

A prototypical material for the oxidative coupling of methane (OCM) is Li/MgO, for which Li is known to be essential as a dopant to obtain high C₂ selectivities. Herein, Li/MgO is demonstrated to be an effective catalyst for non-oxidative coupling of methane (NOCM). Moreover, the presence of Li is shown to favor the formation of magnesium acetylide (MgC₂), while pure MgO promotes coke formation as evidenced by solid-state ¹³C NMR, thus indicating that Li promotes C−C bond formation. Metadynamic simulations of the carbon mobility in MgC₂ and Li₂C₂ at the density functional theory (DFT) level show that carbon easily diffuses as a C₂ unit at 1000 °C. These insights suggest that the enhanced C₂ selectivity for Li-doped MgO is related to the formation of Li and Mg acetylides.