Despite recent progress in the chemistry of frustrated Lewis pairs (FLPs), direct FLP‐catalyzed hydrogenation of CO2 remains elusive. From a near‐infinite array of plausible Lewis pairs, it is ...challenging to identify individual combinations that are appropriate for catalyzing this reaction. To this end, we propose a mapping of the chemical composition of FLPs to their activity towards direct catalytic hydrogenation of CO2 into formate. The maps, built upon linear scaling relationships, pinpoint specific FLP combinations with the proper complementary acidity and basicity to optimally balance the energetics of the catalytic cycle. One such combination was experimentally validated to achieve hitherto unreported catalytic turnover for this transformation.
The chemical composition of frustrated Lewis pairs is mapped to their performance in catalytic direct hydrogenation of CO2 to formate using linear scaling relationships. This map highlights the need for appropriately balancing the acidity and basicity of the components for enhanced activity, which led to the demonstration of hitherto unreported catalytic turnover for this transformation.
For the past 60 years Caulobacter spp. have been commonly attributed an aquatic and oligotrophic lifestyle yet are not uncommon in nutrient-rich or soil environments. This study evaluates the ...environmental and ecological associations of Caulobacter to reconcile past evidence, largely limited to culturing and microscopy, with currently available metagenomic and genomic data. The distribution of Caulobacter species and their characteristic adhesion-conferring genes, holdfast (hfaAB), were determined using collections of 10,641 16S rRNA gene libraries (196 studies) and 2625 shotgun metagenomes (190 studies) from a range of terrestrial and aquatic environments. Evidence for ecotypic variation was tested in 26 genomes sourced from soil, rhizosphere, plant, groundwater, and water. Caulobacter were, on average, fourfold more relatively abundant in soil than in aquatic environments, and abundant in decomposing wood, compost, and particulate matter (in air and water). Caulobacter holdfast genes were 35-fold more abundant in soils than aquatic environments. Ecotypic differences between soil and aquatic Caulobacter were evident in the environmental associations of several species and differences in genome size and content among isolates. However, most abundant species were common to both environments, suggesting populations exist in a continuum that was evident in the re-analysis of studies on the temporal dynamics of, and sources of bacterioplankton to, lakes and rivers. This study provides a new perspective on the ecological profile of Caulobacter, demonstrating that members of this genus are predominantly soil-borne, possess an overlooked role in plant matter decomposition and a dependency on water-mediated dispersal.
In ecological analyses of species and community distributions there is interest in the nature of their responses to environmental gradients and in identifying the most important environmental ...variables, which may be used for predicting patterns of biodiversity. Methods such as random forests already exist to assess predictor importance for individual species and to indicate where along gradients abundance changes. However, there is a need to extend these methods to whole assemblages, to establish where along the range of these gradients the important compositional changes occur, and to identify any important thresholds or change points. We develop such a method, called "gradient forest," which is an extension of the random forest approach. By synthesizing the cross-validated
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and accuracy importance measures from univariate random forest analyses across multiple species, sampling devices, and surveys, gradient forest obtains a monotonic function of each predictor that represents the compositional turnover along the gradient of the predictor. When applied to a synthetic data set, the method correctly identified the important predictors and delineated where the compositional change points occurred along these gradients. Application of gradient forest to a real data set from part of the Great Barrier Reef identified mud fraction of the sediment as the most important predictor, with highest compositional turnover occurring at mud fraction values around 25%, and provided similar information for other predictors. Such refined information allows for more accurate capturing of biodiversity patterns for the purposes of bioregionalization, delineation of protected areas, or designing of biodiversity surveys.
Mice and men: An antibody conjugate with trans‐cyclooctene was administered to tumor‐bearing mice, and the resulting chemically tagged tumors were subsequently treated with an 111In‐labeled tetrazine ...probe in an inverse‐electron‐demand Diels–Alder reaction. The adduct was formed in a remarkable 52–57 % yield in vivo and used for non‐invasive pretargeted tumor imaging in mice (see picture).
Delignification, or lignin-modification, facilitates the decomposition of lignocellulose in woody plant biomass. The extant diversity of lignin-degrading bacteria and fungi is underestimated by ...culture-dependent methods, limiting our understanding of the functional and ecological traits of decomposers populations. Here, we describe the use of stable isotope probing (SIP) coupled with amplicon and shotgun metagenomics to identify and characterize the functional attributes of lignin, cellulose and hemicellulose-degrading fungi and bacteria in coniferous forest soils from across North America. We tested the extent to which catabolic genes partitioned among different decomposer taxa; the relative roles of bacteria and fungi, and whether taxa or catabolic genes correlated with variation in lignocellulolytic activity, measured as the total assimilation of
C-label into DNA and phospholipid fatty acids. We found high overall bacterial degradation of our model lignin substrate, particularly by gram-negative bacteria (Comamonadaceae and Caulobacteraceae), while fungi were more prominent in cellulose-degradation. Very few taxa incorporated
C-label from more than one lignocellulosic polymer, suggesting specialization among decomposers. Collectively, members of Caulobacteraceae could degrade all three lignocellulosic polymers, providing new evidence for their importance in lignocellulose degradation. Variation in lignin-degrading activity was better explained by microbial community properties, such as catabolic gene content and community structure, than cellulose-degrading activity. SIP significantly improved shotgun metagenome assembly resulting in the recovery of several high-quality draft metagenome-assembled genomes and over 7500 contigs containing unique clusters of carbohydrate-active genes. These results improve understanding of which organisms, conditions and corresponding functional genes contribute to lignocellulose decomposition.
Recent experimental results on the dynamics of glass-forming materials, particularly polymers, are surveyed. The focus is on aspects of the behavior that are connected to or correlated with ...structural relaxation. These results include the invariance to thermodynamic conditions (temperature, pressure, volume) of a number of propertiesbreadth of the relaxation dispersion, number of dynamically correlating molecules, Johari−Goldstein secondary relaxation time, onset of the dynamic crossover, and the product of temperature and specific volume with the latter raised to a material constantprovided the structural relaxation time is maintained constant. Additional salient experimental findings include the correlation of various high-frequency processes, usually measured in the glassy state, with properties of the equilibrium material above T g. These correlations indicate that the glass transition, although conventionally defined by the relaxation time becoming larger than experimental time scales (>100 s), has its beginning many orders of magnitude sooner. Also described herein are effects of spatial confinement on the glass transition; these can be dramatic, yet taken in toto are rather discombobulating. Such generally observed phenomena must be included in a comprehensive theory or model of the glass transition, since properties intimately connected to structural relaxation cannot be derived separately and be expected to exhibit such correlations by coincidence.
Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a 'big data compacting and data fusion'-concept to capture diverse adverse ...outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a 'predictive toxicogenomics space' (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 10
data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy.
•Novel machine learning architecture for data-driven constitutive modeling.•Reducing required training data by incorporation of continuum mechanical knowledge.•Predictive constitutive modeling as ...required for designing new materials.
In this paper we introduce constitutive artificial neural networks (CANNs), a novel machine learning architecture for data-driven modeling of the mechanical constitutive behavior of materials. CANNs are able to incorporate by their very design information from three different sources, namely stress-strain data, theoretical knowledge from materials theory, and diverse additional information (e.g., about microstructure or materials processing). CANNs can easily and efficiently be implemented in standard computational software. They require only a low-to-moderate amount of training data and training time to learn without human guidance the constitutive behavior also of complex nonlinear and anisotropic materials. Moreover, in a simple academic example we demonstrate how the input of microstructural data can endow CANNs with the ability to describe not only the behavior of known materials but to predict also the properties of new materials where no stress-strain data are available yet. This ability may be particularly useful for the future in-silico design of new materials. The developed source code of the CANN architecture and accompanying example data sets are available at https://github.com/ConstitutiveANN/CANN.
Immune checkpoint receptor-induced T cell dysfunction is a major cause of CAR T cell treatment failure. In this issue, Agarwal et al. report that CRISPR/Cas9 deletion of CTLA4, but not PDCD1 or CTLA4 ...and PDCD1, enhances CD28 signaling, restoring fitness and antitumor function of CAR T cells, including those derived from patients who failed CAR T cell therapy.
Immune checkpoint receptor-induced T cell dysfunction is a major cause of CAR T cell treatment failure. In this issue, Agarwal et al. report that CRISPR/Cas9 deletion of CTLA4, but not PDCD1 or CTLA4 and PDCD1, enhances CD28 signaling, restoring fitness and antitumor function of CAR T cells, including those derived from patients who failed CAR T cell therapy.
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