basin, consistent with the accumulation of emissions underneath inversions. In the Permian Basin in Texas and New Mexico, methane columns showed maxima over regions with the highest natural gas production and were correlated with nitrogen-dioxide columns at a ratio that is consistent with results from in-situ airborne measurements. The improved detail provided by TROPOMI will likely enable the timely monitoring from space of methane emissions associated with oil and natural gas production.

de Melo, R.D., Leão, P., Abreu, F., Acosta-Avalos, D., 2020. The swimming orientation of multicellular magnetotactic prokaryotes and uncultured magnetotactic cocci in magnetic fields similar to the geomagnetic field reveals differences in magnetotaxis between them. Antonie van Leeuwenhoek 113, 197-209.

https://doi.org/10.1007/s10482-019-01330-3 Magnetotactic bacteria have intracellular chains of magnetic nanoparticles, conferring to their cellular body a magnetic moment that permits the alignment of their swimming trajectories to the geomagnetic field lines. That property is known as magnetotaxis and makes them suitable for the study of bacterial motion. The present paper studies the swimming trajectories of uncultured magnetotactic cocci and of the multicellular magnetotactic prokaryote 'Candidatus Magnetoglobus multicellularis' exposed to magnetic fields lower than 80 μT. It was assumed that the trajectories are cylindrical helixes and the axial velocity, the helix radius, the frequency and the orientation of the trajectories relative to the applied magnetic field were determined from the experimental trajectories. The results show the paramagnetic model applies well to magnetotactic cocci but not to 'Ca. M. multicellularis' in the low magnetic field regime analyzed. Magnetotactic cocci orient their trajectories as predicted by classical magnetota xis but in general 'Ca. M. multicellularis' does not swim following the magnetic field direction, meaning that for it the inversion in the magnetic field direction represents a stimulus but the selection of the swimming direction depends on other cues or even on other mechanisms for magnetic field detection.

de Oliveira, F.C., Khani, S., Maia, J.M., Tavares, F.W., 2020. Concentration and solvent effects on structural, dynamical, and rheological properties of asphaltene suspensions. Energy &Fuels 34, 1071-1081.

https://doi.org/10.1021/acs.energyfuels.9b03315 The effects of different concentrations and solvents in asphaltene solutions properties were studied using a mesoscale simulation approach named dissipative particle dynamics (DPD). Structural analysis revealed the predominance of parallel stacking between molecular planes. The time evolution of number of aggregates showed that the number of aggregates diminishes for both solvents, which makes sense as initially each aggregate represents isolated molecules. Viscosity has been calculated for all cases, and the results show that solute - solvent interactions have a great impact on the viscosity of the material, which becomes less important as the entropy becomes dominant when mass fraction increases. The viscoelastic behavior of asphaltene suspensions has been analyzed for the first using a molecular dynamics approach. All systems presented greater viscous (liquidlike) behavior under high frequencies, which is consistent with soft particles.

de Sousa, J., Vencálek, O., Hron, K., Václavík, J., Friedecký, D., Adam, T., 2020. Bayesian multiple hypotheses testing in compositional analysis of untargeted metabolomic data. Analytica Chimica Acta 1097, 49-61.

http://www.sciencedirect.com/science/article/pii/S0003267019313492 Clinical metabolomics aims at finding statistically significant differences in metabolic statuses of patient and control groups with the intention of understanding pathobiochemical processes and identification of clinically useful biomarkers of particular diseases. After the raw measurements are integrated and pre-processed as intensities of chromatographic peaks, the differences between controls and patients are evaluated by both t univariate and multivariate statistical methods. The traditional univariate approach relies on -tests (or their nonparametric alternatives) and the results from multiple testing are misleadingly compared merely by p-values using the so-called volcano plot.