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In this study we revisit one of the simplest RO2 + RO2 reactions: the self-reaction of the ethene derived hydroxyperoxy radical formed via sequential addition of ·OH and O2 to ethene. Previous studies of this reaction suggested that the branching to ‘accretion products,’ compounds containing the carbon backbone of both reactants, was minimal. Here, CF3O− GC-CIMS is used to quantify the yields of ethylene glycol, glycolaldehyde, a hydroxy hydroperoxide produced from RO2 + HO2, and a C4O4H10 accretion product. These experiments were performed in an environmental chamber at 993 hPa and 294 K. We provide evidence that the accretion product is likely dihydroxy diethyl peroxide (HOC2H4OOC2H4OH = ROOR) and forms in the gas-phase with a branching fraction of 23 ± 5%. We suggest a new channel in the RO2+RO2 chemistry leading directly to the formation of HO2 (together with glycolaldehyde and an alkoxy radical). Finally, by varying the ratio of the formation rate of RO2 and HO2 in our chamber, we constrain the ratio of the rate coefficient for the reaction of RO2 + RO2 to that of RO2 + HO2 and find that this ratio is .22±.07, consistent with previous flash photolysis studies. 

We compare the structure of synthetic dust polarization with synthetic molecular line emission from radiative transfer calculations using a three-dimensional, turbulent collapsing-cloud magnetohydrodynamics simulation. The histogram of relative orientation (HRO) technique and the projected Rayleigh statistic (PRS) are considered. In our trans-Alfvénic (more strongly magnetized) simulation, there is a transition to perpendicular alignment at densities above ∼4 × 103 cm−3. This transition is recovered in most of our synthetic observations of optically thin molecular tracers; however, for 12CO it does not occur and the PRS remains in parallel alignment across the whole observer space. We calculate the physical depth of the optical depth τ = 1 surface and find that for 12CO it is largely located in front of the cloud mid-plane, suggesting that 12CO is too optically thick and instead mainly probes low-volume density gas. In our super-Alfvénic simulation, the magnetic field becomes significantly more tangled, and all observed tracers tend towards no preference for perpendicular or parallel alignment. An observable difference in alignment between optically thin and optically thick tracers may indicate the presence of a dynamically important magnetic field, though there is some degeneracy with viewing angle. We convolve our data with a Gaussian beam and compare it with HRO results of the Vela C molecular cloud. We find good agreement between these results and our sub-Alfvénic simulations when viewed with the magnetic field in the plane of the sky (especially when sensitivity limitations are considered), though the observations are also consistent with an intermediately inclined magnetic field.

 

Glioblastoma (GBM) is a heterogeneous tumor made up of cell states that evolve over time. Here, we modeled tumor evolutionary trajectories during standard-of-care treatment using multi-omic single-cell analysis of a primary tumor sample, corresponding mouse xenografts subjected to standard of care therapy, and recurrent tumor at autopsy. We mined the multi-omic data with single-cell SYstems Genetics Network AnaLysis (scSYGNAL) to identify a network of 52 regulators that mediate treatment-induced shifts in xenograft tumor-cell states that were also reflected in recurrence. By integrating scSYGNAL-derived regulatory network information with transcription factor accessibility deviations derived from single-cell ATAC-seq data, we developed consensus networks that modulate cell state transitions across subpopulations of primary and recurrent tumor cells. Finally, by matching targeted therapies to active regulatory networks underlying tumor evolutionary trajectories, we provide a framework for applying single-cell-based precision medicine approaches to an individual patient in a concurrent, adjuvant, or recurrent setting.

 

Deep neural networks (DNNs) show promise in image-based medical diagnosis, but cannot be fully trusted since they can fail for reasons unrelated to underlying pathology. Humans are less likely to make such superficial mistakes, since they use features that are grounded on medical science. It is therefore important to know whether DNNs use different features than humans. Towards this end, we propose a framework for comparing human and machine perception in medical diagnosis. We frame the comparison in terms of perturbation robustness, and mitigate Simpson’s paradox by performing a subgroup analysis. The framework is demonstrated with a case study in breast cancer screening, where we separately analyze microcalcifications and soft tissue lesions. While it is inconclusive whether humans and DNNs use different features to detect microcalcifications, we find that for soft tissue lesions, DNNs rely on high frequency components ignored by radiologists. Moreover, these features are located outside of the region of the images found most suspicious by radiologists. This difference between humans and machines was only visible through subgroup analysis, which highlights the importance of incorporating medical domain knowledge into the comparison.

 

[Mn(bpy)(CO) 3 Br] is recognized as a benchmark electrocatalyst for CO 2 reduction to CO, with the doubly reduced [Mn(bpy)(CO) 3 ] − proposed to be the active species in the catalytic mechanism. The reaction of this intermediate with CO 2 and two protons is expected to produce the tetracarbonyl cation, [Mn(bpy)(CO) 4 ] + , thereby closing the catalytic cycle. However, this species has not been experimentally observed. In this study, [Mn(bpy)(CO) 4 ][SbF 6 ] ( 1 ) was directly synthesized and found to be an efficient electrocatalyst for the reduction of CO 2 to CO in the presence of H 2 O. Complex 1 was characterized using X-ray crystallography as well as IR and UV-Vis spectroscopy. The redox activity of 1 was determined using cyclic voltammetry and compared with that of benchmark manganese complexes, e.g. , [Mn(bpy)(CO) 3 Br] ( 2 ) and [Mn(bpy)(CO) 3 (MeCN)][PF 6 ] ( 3 ). Infrared spectroscopic analyses indicated that CO dissociation occurs after a single-electron reduction of complex 1 , producing a [Mn(bpy)(CO) 3 (MeCN)] + species. Complex 1 was experimentally verified as both a precatalyst and an on-cycle intermediate in homogeneous Mn-based electrocatalytic CO 2 reduction. 

Microscopic organisms known as bacteria are found in virtually every environment on the planet. One reason bacteria are so successful is that they are able to form communities known as biofilms on surfaces in animals and other living things, as well as on rocks and other features in the environment. These biofilms protect the bacteria from fluctuations in the environment and toxins. For over 30 years, a class of enzymes called the GGDEF enzymes were thought to make a single signal known as cyclic di-GMP that regulates the formation of biofilms. However, in 2016, a team of researchers reported that some GGDEF enzymes, including one from a bacterium called Geobacter sulfurreducens, were also able to produce two other signals known as cGAMP and cyclic di-AMP. The experiments involved making the enzymes and testing their activity outside the cell. Therefore, it remained unclear whether these enzymes (dubbed ‘Hypr’ GGDEF enzymes) actually produce all three signals inside cells and play a role in forming bacterial biofilms. G. sulfurreducens is unusual because it is able to grow on metallic minerals or electrodes to generate electrical energy. As part of a community of microorganisms, they help break down pollutants in contaminated areas and can generate electricity from wastewater. Now, Hallberg, Chan et al. – including many of the researchers involved in the 2016 work – combined several experimental and mathematical approaches to study the Hypr GGDEF enzymes in G. sulfurreducens. The experiments show that the Hypr GGDEF enzymes produced cGAMP, but not the other two signals, inside the cells. This cGAMP regulated the ability of G. sulfurreducens to grow by extracting electrical energy from the metallic minerals, which appears to be a new, biofilm-less lifestyle. Further experiments revealed how Hypr GGDEF enzymes have evolved to preferentially make cGAMP over the other two signals. Together, these findings demonstrate that enzymes with the ability to make several different signals, are capable of generating specific responses in bacterial cells. By understanding how bacteria make decisions, it may be possible to change their behaviors. The findings of Hallberg, Chan et al. help to identify the signaling pathways involved in this decision-making and provide new tools to study them in the future. 

3′,3′‐cyclic GMP‐AMP (cGAMP) is the third cyclic dinucleotide (CDN) to be discovered in bacteria. No activators of cGAMP signaling have yet been identified, and the signaling pathways for cGAMP have been inferred to display a narrow distribution based upon the characterized synthases, DncV and Hypr GGDEFs. Here, we report that the ubiquitous second messenger cyclic AMP (cAMP) is an activator of the Hypr GGDEF enzyme GacB fromMyxococcus xanthus. Furthermore, we show that GacB is inhibited directly by cyclic di‐GMP, which provides evidence for cross‐regulation between different CDN pathways. Finally, we reveal that the HD‐GYP enzyme PmxA is a cGAMP‐specific phosphodiesterase (GAP) that promotes resistance to osmotic stress inM. xanthus. A signature amino acid change in PmxA was found to reprogram substrate specificity and was applied to predict the presence of non‐canonical HD‐GYP phosphodiesterases in many bacterial species, including phyla previously not known to utilize cGAMP signaling.