Supported 3-D Pt nanostructures: the straightforward synthesis and enhanced electrochemical performance for methanol oxidation in an acidic medium

Noble metal nanostructures with branched morphologies [i.e., 3-D Pt nanoflowers (NFs)] by tridimensionally integrating onto conductive carbon materials are proved to be an efficient and durable electrocatalysts for methanol oxidation. The well-supported 3-D Pt NFs are readily achieved by an efficient cobalt-induced/carbon-mediated galvanic reaction approach. Due to the favorable nanostructures (3-D Pt configuration allowing a facile mass transfer) and supporting effects (including framework stabilization, spatially separate feature, and improved charge transport effects), these 3-D Pt NFs manifest much higher electrocatalytic activity and stability toward methanol oxidation than that of the commercial Pt/C and Pt-based electrocatalysts.Web of Scienc

Early events in the photochemistry of 5-diazo Meldrum's acid : Formation of a product manifold in C-N bound and pre-dissociated intersection seam regions

5-Diazo Meldrum's acid (DMA) undergoes a photo-induced Wolff rearrangement (WR). Recent gas-phase experiments have identified three photochemical products formed in a sub-ps scale after irradiation, a carbene formed after nitrogen loss, a ketene formed after WR and a second carbene formed after nitrogen and CO elimination (A. Steinbacher, et al. Phys. Chem. Chem. Phys., 2014, 16, 7290-7298). In this work, ground- and excited-state potential energy surfaces (PESs) have been investigated at the MS-CASPT2// CASSCF level. The key element of the PESs is an extended S0/S1 conical intersection seam along the C-N dissociation coordinate. The C-N predissociated region of the seam is accessed after excitation to the bright S2 state, and decay paths from the seam to the three primary products have been characterized. For the ketene and carbene II products, we show two possible formation pathways, a direct and a stepwise one, which suggests that these products may be formed in a bi-modal fashion. We have also characterized two possible mechanisms for triplet formation, one occurring before C-N dissociation involving a (S1/T2/T1) crossing region, and another one through the carbene. In contrast, excitation to S1 leads to a C-N bound region of the seam from where DMA regeneration or diazirine formation is possible, with a preference for the first case. The results are in good agreement with experimental data. Together with our previous work on diazonaphthoquinone, they show the importance of an extended seam in the photochemistry of a-diazoketones

Will EGFRvIII and neuronal-derived EGFR be targets for imipramine?

Tricyclic antidepressant is an old and well-established therapeutic agent with a good safety profile, making them an excellent candidate for repurposing. In light of the growing understanding of the importance of nerves in the development and progression of cancer, attention is now being turned to using nerve-targeting drugs for the treatment of cancer, particularly TCAs. However, the specific mechanism by which antidepressants affect the tumor microenvironment of glioblastoma (GBM) is still unclear. Here, we combined bulk RNA sequencing, network pharmacology, single-cell sequencing, molecular docking and molecular dynamics simulation to explore the potential molecular mechanism of imipramine in the treatment of GBM. We first revealed that the imipramine treatment is presumed to target EGFRvIII and neuronal-derived EGFR, which may play a pivotal role in treating GBM by reducing the GABAergic synapse and vesicle-mediated release and other processes thereby modulating immune function. The novel pharmacological mechanisms might provide further research directions

ecGBMsub: an integrative stacking ensemble model framework based on eccDNA molecular profiling for improving IDH wild-type glioblastoma molecular subtype classification

IDH wild-type glioblastoma (GBM) intrinsic subtypes have been linked to different molecular landscapes and outcomes. Accurate prediction of molecular subtypes of GBM is very important to guide clinical diagnosis and treatment. Leveraging machine learning technology to improve the subtype classification was considered a robust strategy. Several single machine learning models have been developed to predict survival or stratify patients. An ensemble learning strategy combines several basic learners to boost model performance. However, it still lacked a robust stacking ensemble learning model with high accuracy in clinical practice. Here, we developed a novel integrative stacking ensemble model framework (ecGBMsub) for improving IDH wild-type GBM molecular subtype classification. In the framework, nine single models with the best hyperparameters were fitted based on extrachromosomal circular DNA (eccDNA) molecular profiling. Then, the top five optimal single models were selected as base models. By randomly combining the five optimal base models, 26 different combinations were finally generated. Nine different meta-models with the best hyperparameters were fitted based on the prediction results of 26 different combinations, resulting in 234 different stacked ensemble models. All models in ecGBMsub were comprehensively evaluated and compared. Finally, the stacking ensemble model named “XGBoost.Enet-stacking-Enet” was chosen as the optimal model in the ecGBMsub framework. A user-friendly web tool was developed to facilitate accessibility to the XGBoost.Enet-stacking-Enet models (https://lizesheng20190820.shinyapps.io/ecGBMsub/)

Abnormal thermal expansion coefficients in (Nd1−xDyx)2Zr2O7 pyrochlore: The effect of low-lying optical phonons

Chemical doping is a normal strategy to tune thermal expansion coefficient (TEC) of ceramics in engineering applications, but the resultant TEC values usually follow Vegard’s law, as doping does not modify the nature of chemical bonding in ceramics and its anharmonicity. In this paper, we report abnormal TEC behavior in (Nd1−xDyx)2Zr2O7 ceramics, where the TEC values remarkably exceed the values predicted by Vegard’s law and even exceed the values obtained for two constituents Nd2Zr2O7 and Dy2Zr2O7. In addition to a reduction in lattice energy with an increasing molar fraction of Dy (x) value, we attribute the additional increase in the TEC to the high concentration of Dy dopants in a pyrochlore (P) region, which can soften low-lying optical phonon modes and induce strongly avoided crossing with acoustic phonon branches and enhanced anharmonicity. We believe that this finding can provide a new route to break through the restriction imposed by the conventional Vegard’s law on the TEC values and bring new opportunities for thermal barrier coatings (TBCs) or ceramic/metal composites towards realizing minimized thermal mismatch and prolonged service life during thermal cycling

Clustering mechanism of oxocarboxylic acids involving hydration reaction : Implications for the atmospheric models

The formation of atmospheric aerosol particles from condensable gases is a dominant source of particulate matter in the boundary layer, but the mechanism is still ambiguous. During the clustering process, precursors with di↵erent reactivities can induce various chemical reactions in addition to the formation of hydrogen bonds. However, the clustering mechanism involving chemical reactions is rarely considered in most of the nucleation process models. Oxocarboxylic acids are common compositions of secondary organic aerosol, but the role of oxocarboxylic acids in secondary organic aerosol formation is still not fully understood. In this paper, glyoxylic acid, the simplest and the most abundant atmospheric oxocarboxylic acids, has been selected as a representative example of oxocarboxylic acids in order to study the clustering mechanism involving hydration reaction using Density Functional Theory combined with the Atmospheric Clusters Dynamic Code. The hydration reaction of glyoxylic acid can occur either in the gas phase or during the clustering process. In atmospheric conditions, the total conversion ratio of glyoxylic acid to its hydration reaction product (2,2-dihydroxyacetic acid) in both gas phase and clusters can be up to 85%, andthe product can further participate in the clustering process. The di↵erences in cluster structures and properties induced by the hydration reaction lead to significant di↵erences in cluster formation rates and pathways at relatively low temperatures.Peer reviewe

Identification of the GRAS gene family in the Brassica juncea genome provides insight into its role in stem swelling in stem mustard

GRAS transcription factors are known to play important roles in plant signal transduction and development. A comprehensive study was conducted to explore the GRAS family in the Brassica juncea genome. A total of 88 GRAS genes were identified which were categorized into nine groups according to the phylogenetic analysis. Gene structure analysis showed a high group-specificity, which corroborated the gene grouping results. The chromosome distribution and sequence analysis suggested that gene duplication events are vital for the expansion of GRAS genes in the B. juncea genome. The changes in evolution rates and amino acid properties among groups might be responsible for their functional divergence. Interaction networks and cis-regulatory elements were analyzed including DELLA and eight interaction proteins (including four GID1, two SLY1, and two PIF3 proteins) that are primarily involved in light and hormone signaling. To understand their regulatory role in growth and development, the expression profiles of BjuGRASs and interaction genes were examined based on transcriptome data and qRT-PCR, and selected genes (BjuGRAS3, 5, 7, 8, 10, BjuB006276, BjuB037910, and BjuA021658) had distinct temporal expression patterns during stem swelling, indicating that they possessed diverse regulatory functions during the developmental process. These results contribute to our understanding on the GRAS gene family and provide the basis for further investigations on the evolution and functional characterization of GRAS genes

Recent Advances in Understanding the Influence of Maillard Reaction on the Allergenicity of Crustacean Allergens in Aquatic Products

Crustacean products are popular for its rich nutritional value, despite causing serious allergy symptoms. The presence of allergens is one of the main factors restricting the further development of the consumer market of crustacean products. The Maillard reaction widely exists in the processing and storage of aquatic products and can affect the allergenicity of foods. This review systematically introduces readers to the Maillard reaction, and summarizes the recent progress in research on the structure and epitopes of crustacean allergens. More importantly, it reviews the changes in the allergenicity of crustacean allergens after Maillard reaction and the underlying mechanism. It is our hope that this paper will provide a reference for controlling and reducing the allergenicity of crustacean products by Maillard reaction

xPath: Human-AI Diagnosis in Pathology with Multi-Criteria Analyses and Explanation by Hierarchically Traceable Evidence

Data-driven AI promises support for pathologists to discover sparse tumor patterns in high-resolution histological images. However, from a pathologist's point of view, existing AI suffers from three limitations: (i) a lack of comprehensiveness where most AI algorithms only rely on a single criterion; (ii) a lack of explainability where AI models tend to work as 'black boxes' with little transparency; and (iii) a lack of integrability where it is unclear how AI can become part of pathologists' existing workflow. Based on a formative study with pathologists, we propose two designs for a human-AI collaborative tool: (i) presenting joint analyses of multiple criteria at the top level while (ii) revealing hierarchically traceable evidence on-demand to explain each criterion. We instantiate such designs in xPath -- a brain tumor grading tool where a pathologist can follow a top-down workflow to oversee AI's findings. We conducted a technical evaluation and work sessions with twelve medical professionals in pathology across three medical centers. We report quantitative and qualitative feedback, discuss recurring themes on how our participants interacted with xPath, and provide initial insights for future physician-AI collaborative tools.Comment: 31 pages, 11 figure