Showing papers by "Chao Zhang published in 2019"

Copper atom-pair catalyst anchored on alloy nanowires for selective and efficient electrochemical reduction of CO 2

Abstract: The electrochemical reduction of CO2 could play an important role in addressing climate-change issues and global energy demands as part of a carbon-neutral energy cycle. Single-atom catalysts can display outstanding electrocatalytic performance; however, given their single-site nature they are usually only amenable to reactions that involve single molecules. For processes that involve multiple molecules, improved catalytic properties could be achieved through the development of atomically dispersed catalysts with higher complexities. Here we report a catalyst that features two adjacent copper atoms, which we call an ‘atom-pair catalyst’, that work together to carry out the critical bimolecular step in CO2 reduction. The atom-pair catalyst features stable Cu10–Cu1x+ pair structures, with Cu1x+ adsorbing H2O and the neighbouring Cu10 adsorbing CO2, which thereby promotes CO2 activation. This results in a Faradaic efficiency for CO generation above 92%, with the competing hydrogen evolution reaction almost completely suppressed. Experimental characterization and density functional theory revealed that the adsorption configuration reduces the activation energy, which generates high selectivity, activity and stability under relatively low potentials. Anchored single-atom catalysts have recently been shown to be very active for various processes, however, a catalyst that features two adjacent copper atoms—which we call an atom-pair catalyst—is now reported. The Cu10–Cu1x+ pair structures work together to carry out the critical bimolecular step in CO2 reduction.

Sustained microglial depletion with CSF1R inhibitor impairs parenchymal plaque development in an Alzheimer's disease model.

Abstract: Many risk genes for the development of Alzheimer's disease (AD) are exclusively or highly expressed in myeloid cells. Microglia are dependent on colony-stimulating factor 1 receptor (CSF1R) signaling for their survival. We designed and synthesized a highly selective brain-penetrant CSF1R inhibitor (PLX5622) allowing for extended and specific microglial elimination, preceding and during pathology development. We find that in the 5xFAD mouse model of AD, plaques fail to form in the parenchymal space following microglial depletion, except in areas containing surviving microglia. Instead, Aβ deposits in cortical blood vessels reminiscent of cerebral amyloid angiopathy. Altered gene expression in the 5xFAD hippocampus is also reversed by the absence of microglia. Transcriptional analyses of the residual plaque-forming microglia show they exhibit a disease-associated microglia profile. Collectively, we describe the structure, formulation, and efficacy of PLX5622, which allows for sustained microglial depletion and identify roles of microglia in initiating plaque pathogenesis.

Ultrathin metal/covalent-organic framework membranes towards ultimate separation.

Abstract: Metal/covalent–organic framework (MOF/COF) membranes have attracted increasing research interest and have been considered as state-of-the-art platforms applied in various environment- and energy-related separation/transportation processes. To break the trade-off between permeability and selectivity to achieve ultimate separation, recent studies have been oriented towards how to design and exploit ultrathin MOF/COF membranes (i.e. sub-1 μm-thick). Given great advances made in the past five years, it is valuable to timely and systematically summarize the recent development and shed light on the future trend in this multidisciplinary field. In this review, we first present the advanced strategies in fabricating ultrathin defect-free MOF/COF membranes such as in situ growth, contra-diffusion method, layer-by-layer (LBL) assembly, metal-based precursor as the pre-functionalized layer, interface-assisted strategy, and laminated assembly of MOF/COF nanosheets. Then, the recent progress in some emerging applications of ultrathin MOF/COF membranes beyond gas separation is highlighted, including water treatment and seawater desalination, organic solvent nanofiltration, and energy-related separation/transportation (i.e. lithium ion separation and proton conductivity). Finally, some unsolved scientific and technical challenges associated with future perspectives in this field are discussed, inspiring the development of next-generation separation membranes.

Cobalt nanoparticle-embedded nitrogen-doped carbon/carbon nanotube frameworks derived from a metal–organic framework for tri-functional ORR, OER and HER electrocatalysis

Abstract: Developing active and stable electrocatalysts of earth-abundant elements towards the oxygen reduction reaction (ORR), oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) still remains a crucial challenge. Herein, a cobalt-containing metal-organic framework using adenine as a ligand was synthesized and pyrolyzed without any other precursors, forming a cobalt nanoparticle-embedded nitrogen-doped carbon/carbon nanotube framework (Co@N-CNTF). Due to the abundant active sites of homogeneously distributed cobalt nanoparticles within nitrogen-doped graphitic layers, the resultant Co@N-CNTF catalysts exhibit an efficient and stable electrocatalytic performance as a tri-functional catalyst towards the ORR, OER and HER, including a high half-wave potential of 0.81 V vs. RHE for the ORR, and a low overpotential at 10 mA cm -2 for the OER (0.35 V) and HER (0.22 V). As a proof-of-concept, the Co@N-CNTF as an OER/HER bifunctional catalyst for full water splitting affords an alkaline electrolyzer with 10 mA cm -2 under a stable voltage of 1.71 V. Moreover, an integrated unit of a water-splitting electrolyzer using the Co@N-CNTF catalysts, which is powered with a rechargeable Zn-air battery using the Co@N-CNTF as an ORR/OER bifunctional catalyst on air electrodes, can operate under ambient conditions with high cycling stability, demonstrating the viability and efficiency of the self-powered water-splitting system.

Electrochemical synthesis of nitric acid from air and ammonia through waste utilization.

Abstract: Commercial nitric acid (HNO3) and ammonia (NH3) are mostly produced through the Ostwald process and the Haber-Bosch process, respectively. However, high energy demand and enormous greenhouse gas accompy these processes. The development of economical and green ways to synthesize HNO3 and NH3 is highly desirable for solving the global energy and environmental crisis. Here, we present two energy-efficient and environmentally friendly strategies to synthesize HNO3 and NH3 at distributed sources, including the electrocatalytic oxidation of N2 in air to HNO3 and the electrocatalytic reduction of residual |${\\rm NO_{3}^{-}}$| contamination in water to NH3. The isotope-labeling studies combined with theoretical calculation reveal the reaction path of the two proposed strategies, confirming the origin of the electrochemical products. Importantly, the electrooxidation-generated |${\\rm NO_{3}^{-}}$| ions may also serve as reactants for the electroreduction synthesis of NH3 in the future. Our work may open avenues for energy-efficient and green production of HNO3 and NH3 at distributed sources.

Harnessing Solar-Driven Photothermal Effect toward the Water-Energy Nexus.

Abstract: Producing affordable freshwater has been considered as a great societal challenge, and most conventional desalination technologies are usually accompanied with large energy consumption and thus struggle with the trade-off between water and energy, i.e., the water-energy nexus. In recent decades, the fast development of state-of-the-art photothermal materials has injected new vitality into the field of freshwater production, which can effectively harness abundant and clean solar energy via the photothermal effect to fulfill the blue dream of low-energy water purification/harvesting, so as to reconcile the water-energy nexus. Driven by the opportunities offered by photothermal materials, tremendous effort has been made to exploit diverse photothermal-assisted water purification/harvesting technologies. At this stage, it is imperative and important to review the recent progress and shed light on the future trend in this multidisciplinary field. Here, a brief introduction of the fundamental mechanism and design principle of photothermal materials is presented, and the emerging photothermal applications such as photothermal-assisted water evaporation, photothermal-assisted membrane distillation, photothermal-assisted crude oil cleanup, photothermal-enhanced photocatalysis, and photothermal-assisted water harvesting from air are summarized. Finally, the unsolved challenges and future perspectives in this field are emphasized. It is envisioned that this work will help arouse future research efforts to boost the development of solar-driven low-energy water purification/harvesting.

Damage and failure mechanism of thin composite laminates under low-velocity impact and compression-after-impact loading conditions

Abstract: Impact resistance and damage tolerance are of great significance in the design of composite structures. This study investigated the damage and failure mechanism of thin composite laminates under low-velocity impact and compression-after-impact (CAI) loading conditions. Four levels of impact energy were included in the test matrix. Delamination induced by low-velocity impact was captured using ultrasonic C-scan, and a three-dimensional (3D) digital image correlation (DIC) system was employed to measure full-field displacement during the CAI tests. Infrared thermography was also used to online monitor the thermal field variation of the test specimen during the impact and CAI process. The cross sections of typical tested specimens were inspected using an optical microscope and a scanning electron microscope (SEM). A 3D damage model that considers both interlaminar and intralaminar damage was proposed to study the complex damage and failure mechanism. Excellent correlation was obtained between the experimental results and the numerical results. The experimental results obtained from various tests and the results from the numerical simulation were combined to provide a new and deep insight of damage evolution and failure mechanisms under low-velocity impact and CAI loading conditions.

Room temperature conductive type metal oxide semiconductor gas sensors for NO2 detection

Abstract: Air pollution is nowadays a big issue regarding the health of human beings. Among the toxic gases emitted in the atmosphere, NO2 is the most problematic one and a lot of countries or cities want to monitor its concentration in order to be able to take measures to reduce it. Therefore, it is urgent to develop NO2 sensors with high performance, low power consumption and low cost. Several technologies have been developed for this purpose. A very popular technology is based on metal oxide semiconductor. The usual semiconductor gas sensors need to be operated at high temperature, but nowadays many efforts are put on metal oxide sensors that can work at room temperature. These sensors present many advantages: low power consumption, low manufacturing cost, as well as moderate stability and safety. However, due to the weak response to NO2 at room temperature, most semiconductor NO2 sensors need to be adapted. This review will present the main strategies and material modification methods studied so far. These include light illumination, sensitization with an organic, formation of heterojunctions, preparation of composites with 1D or 2D materials and an introduction of oxygen vacancies in high concentrations. The gas sensing mechanisms of these sensors are presented and discussed.

RAF inhibitor PLX8394 selectively disrupts BRAF dimers and RAS-independent BRAF-mutant-driven signaling

Abstract: Activating BRAF mutants and fusions signal as RAS-independent constitutively active dimers with the exception of BRAF V600 mutant alleles which can function as active monomers1. Current RAF inhibitors are monomer selective, they potently inhibit BRAF V600 monomers but their inhibition of RAF dimers is limited by induction of negative cooperativity when bound to one site in the dimer1–3. Moreover, acquired resistance to these drugs is usually due to molecular lesions that cause V600 mutants to dimerize4–8. We show here that PLX8394, a new RAF inhibitor9, inhibits ERK signaling by specifically disrupting BRAF-containing dimers, including BRAF homodimers and BRAF–CRAF heterodimers, but not CRAF homodimers or ARAF-containing dimers. Differences in the amino acid residues in the amino (N)-terminal portion of the kinase domain of RAF isoforms are responsible for this differential vulnerability. As a BRAF-specific dimer breaker, PLX8394 selectively inhibits ERK signaling in tumors driven by dimeric BRAF mutants, including BRAF fusions and splice variants as well as BRAF V600 monomers, but spares RAF function in normal cells in which CRAF homodimers can drive signaling. Our work suggests that drugs with these properties will be safe and useful for treating tumors driven by activating BRAF mutants or fusions. The new RAF inhibitor PLX8394 selectively blocks ERK signaling in tumors driven by class 1 and/or class 2 BRAF mutations and BRAF fusions while maintaining a broad therapeutic window.

Wear and corrosion resistant performance of thermal-sprayed Fe-based amorphous coatings: A review

Abstract: Thermal sprayed Fe-based amorphous coatings exhibit excellent wear and corrosion resistance, and thus have been widely utilized for enhancing the performance of material surfaces. In this paper, important research progresses achieved in regards to deposition technologies and properties of thermal sprayed Fe-based amorphous coatings are reviewed. In particular, the dependence of wear and corrosion resistance of the coatings on processing parameters, e.g., kinetic energy, particle size, gas flow rate, and heat treatment temperature are summarized. Moreover, the utilization of reinforced phases and alloy elements for enhancing the wear and corrosion resistance of the coatings are presented. It is expected that future endeavors will be dedicated to the formation mechanism of amorphous phase and “processing parameter-microstructure-macroscopic property” relationship of Fe-based amorphous coatings.

Antibacterial mechanism and activity of cerium oxide nanoparticles

Abstract: Nanomaterials have been applied as antibacterial agents by virtue of their unique functioning mechanism different from that of conventional antibiotics. Cerium oxide nanoparticles (CeO2 NPs) are important antibacterial agents due to their relatively low toxicity to normal cells and their distinct antibacterial mechanism based on the reversible conversion between two valence states of Ce(III)/Ce(IV). Some studies have been conducted to explore their antibacterial activities; however, systematic research reviews on the related mechanisms and influencing factors are still quite rare. In this review, we discuss the plausible mechanisms of the antibacterial activity of CeO2 NPs, analyze different influencing factors, and summarize various research reports on antibacterial effects on E . coli and S . aureus . We also propose the potential applications and prospects, and hope to provide an in-depth understanding on the antibacterial mechanism and a better guidance to the design and applications of this promising antibacterial material in the future.

An experimental and numerical investigation on low-velocity impact damage and compression-after-impact behavior of composite laminates

Abstract: This study investigated the damage and failure mechanism of composite laminates under low-velocity impact and compression-after-impact (CAI) loading conditions by numerical and experimental methods. Ultrasonic C-scan, DIC and SEM methods were combined to give a new and deep insight of damage evolution and failure mechanisms in composite laminates. A novel three-dimensional damage model based on continuum damage mechanics was developed to investigate the impact and CAI behavior with consideration of both interlaminar delamination damage and intralaminar damage. The maximum-strain failure criterion and an improved three-dimensional Puck criterion, which was physically-based, were employed to capture the initiation of fiber and matrix damage respectively and a bi-linear damage constitutive relation was used for characterization of damage evolution. The interlaminar delamination damage was simulated by the interfacial cohesive behavior. Good correlation between numerical and experimental results demonstrated the effectiveness and rationality of the proposed numerical model. The effects of impact energy level and multiple impacts were discussed.

Selenium vacancy-rich CoSe2 ultrathin nanomeshes with abundant active sites for electrocatalytic oxygen evolution

Abstract: CoSe2 is a promising electrocatalyst for the oxygen evolution reaction (OER), benefiting from its suitable electronic configuration and inherent metallic behavior. However, the low ratio of electrolyte-accessible active sites suppresses the OER performance of pure CoSe2. Engineering CoSe2 into a two-dimensional ultrathin nanomesh structure with abundant selenium vacancies is expected to increase its number of active sites and hence improve the OER activity, but, its synthesis is highly challenging. In this work, CoSe2 ultrathin nanomeshes with abundant selenium vacancies (CoSe2 UNMvac) were prepared through plasma treatment on CoSe2–diethylenetriamine (DETA) layered hybrids. The as-obtained CoSe2 UNMvac exhibited an excellent OER performance with a low overpotential of 284 mV at 10 mA cm−2, a small Tafel slope of 46.3 mV dec−1, good stability over 20 h and a large mass activity of 789.1 A g−1 at an overpotential of 300 mV. The greatly enhanced OER activity could be ascribed to the large number of highly active sites on the surface, which are exposed to the electrolyte.

NKG2A is a NK cell exhaustion checkpoint for HCV persistence.

Abstract: Exhaustion of cytotoxic effector natural killer (NK) and CD8+ T cells have important functions in the establishment of persistent viral infections, but how exhaustion is induced during chronic hepatitis C virus (HCV) infection remains poorly defined. Here we show, using the humanized C/OTg mice permissive for persistent HCV infection, that NK and CD8+ T cells become sequentially exhausted shortly after their transient hepatic infiltration and activation in acute HCV infection. HCV infection upregulates Qa-1 expression in hepatocytes, which ligates NKG2A to induce NK cell exhaustion. Antibodies targeting NKG2A or Qa-1 prevents NK exhaustion and promotes NK-dependent HCV clearance. Moreover, reactivated NK cells provide sufficient IFN-γ that helps rejuvenate polyclonal HCV CD8+ T cell response and clearance of HCV. Our data thus show that NKG2A serves as a critical checkpoint for HCV-induced NK exhaustion, and that NKG2A blockade sequentially boosts interdependent NK and CD8+ T cell functions to prevent persistent HCV infection.

Room-temperature NO2 gas sensors based on rGO@ZnO1-x composites: Experiments and molecular dynamics simulation

Abstract: Recently, room-temperature gas sensors have become very attractive due to the fact that they can be operated without heating, and thus simplifying the sensor design, reducing the fabrication cost, decreasing the power consumption and increasing the long-term stability. In this study, we propose a facile one-step hydrothermal method to prepare a composite of reduced graphene (rGO)/oxygen-deficient zinc oxide (ZnO1-x), which exhibits obvious room-temperature gas sensing response. X-ray diffraction, Raman and X-ray photoelectron spectroscopy demonstrate that the rGO@ZnO1-x composite is successfully synthesized and large numbers of dual donor defects, oxygen vacancy and zinc interstitial, are introduced into the composite. Field-emission scanning electron microscopy and transmission electron microscopy results reveal that many nanoscale p-n junctions are in-situ formed between ZnO nanosheets and rGO sheets. UV–vis spectra show that the light absorption of the rGO@ZnO1-x composite is red-shifted and extended to the whole visible light region in comparison. The fraction of rGO in the composites plays an important role in the sensing performance. 2.0% is the optimal proportion to obtain the best sensing properties in terms of sensitivity, response and recovery times. The rGO@ZnO1-x composite exhibits significant responses to ppb-level NO2 with white LED light stimulation at room temperature. The enhanced sensing properties can be attributed to three factors: light activation, synergistic effects between rGO and ZnO1-x, and high concentration in donor defects. Molecular Dynamics (MD) is used to quantitively simulate the adsorption process, and the results show that the incorporation of rGO decreases the adsorption energy of NO2. It means that more NO2 species would adsorb on the rGO@ZnO1-x composites, which greatly improves the sensitivity. A new gas sensing mechanism based on the MD calculated results and Langmuir adsorption model is used to explain the reason that the rGO@ZnO1-x composites have a much faster response and recovery process. In addition, the rGO@ZnO1-x sensor shows a weaker response to other interference gases.

Orientation-Aware Semantic Segmentation on Icosahedron Spheres

Abstract: We address semantic segmentation on omnidirectional images, to leverage a holistic understanding of the surrounding scene for applications like autonomous driving systems. For the spherical domain, several methods recently adopt an icosahedron mesh, but systems are typically rotation invariant or require significant memory and parameters, thus enabling execution only at very low resolutions. In our work, we propose an orientation-aware CNN framework for the icosahedron mesh. Our representation allows for fast network operations, as our design simplifies to standard network operations of classical CNNs, but under consideration of north-aligned kernel convolutions for features on the sphere. We implement our representation and demonstrate its memory efficiency up-to a level-8 resolution mesh (equivalent to 640 x 1024 equirectangular images). Finally, since our kernels operate on the tangent of the sphere, standard feature weights, pretrained on perspective data, can be directly transferred with only small need for weight refinement. In our evaluation our orientation-aware CNN becomes a new state of the art for the recent 2D3DS dataset, and our Omni-SYNTHIA version of SYNTHIA. Rotation invariant classification and segmentation tasks are additionally presented for comparison to prior art.

Self‐Templated Conversion of Metallogel into Heterostructured TMP@Carbon Quasiaerogels Boosting Bifunctional Electrocatalysis

Abstract: Integration of nanostructured electrocatalysts into a 3D ordered assembly is beneficial for boosting their catalytic performance across various energy conversion applications In this work, a self-templated carbonization strategy for synthesizing heterostructures of transition metal phosphide@nitrogen/phosphorus dual-doped carbon quasiaerogels (TMP@NPCA) is presented using a rationally designed precursor of a metallogel with Zn/M (M = Co, Fe, and Ni) bimetallic clusters (BMOG) and nitrogen/phosphorus chelate ligands During the self-templated carbonization, the Zn ions among the BMOG boost a simultaneous catalytic carbonization and activation process of the resultant TMP@NPCA, whereas the M ions offer a versatile self-phosphating preparation of TMP nanoparticles (eg, CoP, FeP, and Ni2P) within the TMP@NPCA As a proof of concept, the TMP@NPCA catalysts deliver an excellent bifunctional catalytic activity and outstanding stability toward the oxygen reduction reaction and hydrogen evolution reaction, offering competitive advantages to achieve supreme bifunctional catalysis performance over the state-of-the-art TMP catalysts for renewable energy conversion systems

Stereoselectively Assembled Metal–Organic Framework (MOF) Host for Catalytic Synthesis of Carbon Hybrids for Alkaline-Metal-Ion Batteries

Abstract: Cost-effective metal-based nanostructured hybrids have been widely dedicated to potential energy storage and conversion applications. Herein, we develop a facile methodology for the synthesis of precise carbon-confined hybrid nanostructures by stereoselective assembly accompanied by catalytic pyrolysis. Polyacrylonitrile fiber films favors not only metal-polymer coordination, but also oriented assembly to ensure the well-defined nanostructure of the carbon hybrids. During chemical vapor deposition (CVD), cobalt-nanoparticle-catalyzed growth of carbon-nanotube branches driven by organic molecules (e.g. melamine) delivers hierarchical carbon hybrids. The resulting carbon hybrids exhibit outstanding electrochemical performance for metal-ion batteries, for example, a high specific capacity of 680 mAh g-1 after 320 cycles (Li-storage) and 220 mAh g-1 after 500 cycles (Na-storage) without decay.

Palmitoylation of NOD1 and NOD2 is required for bacterial sensing.

Abstract: The nucleotide oligomerization domain (NOD)-like receptors 1 and 2 (NOD1/2) are intracellular pattern-recognition proteins that activate immune signaling pathways in response to peptidoglycans associated with microorganisms. Recruitment to bacteria-containing endosomes and other intracellular membranes is required for NOD1/2 signaling, and NOD1/2 mutations that disrupt membrane localization are associated with inflammatory bowel disease and other inflammatory conditions. However, little is known about this recruitment process. We found that NOD1/2 S-palmitoylation is required for membrane recruitment and immune signaling. ZDHHC5 was identified as the palmitoyltransferase responsible for this critical posttranslational modification, and several disease-associated mutations in NOD2 were found to be associated with defective S-palmitoylation. Thus, ZDHHC5-mediated S-palmitoylation of NOD1/2 is critical for their ability to respond to peptidoglycans and to mount an effective immune response.

DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data

Abstract: Online services are playing critical roles in almost all aspects of users' life. Users usually have multiple online identities (IDs) in different online services. In order to fuse the separated user data in multiple services for better business intelligence, it is critical for service providers to link online IDs belonging to the same user. On the other hand, the popularity of mobile networks and GPS-equipped smart devices have provided a generic way to link IDs, i.e., utilizing the mobility traces of IDs. However, linking IDs based on their mobility traces has been a challenging problem due to the highly heterogeneous, incomplete and noisy mobility data across services. In this paper, we propose DPLink, an end-to-end deep learning based framework, to complete the user identity linkage task for heterogeneous mobility data collected from different services with different properties. DPLink is made up by a feature extractor including a location encoder and a trajectory encoder to extract representative features from trajectory and a comparator to compare and decide whether to link two trajectories as the same user. Particularly, we propose a pre-training strategy with a simple task to train the DPLink model to overcome the training difficulties introduced by the highly heterogeneous nature of different source mobility data. Besides, we introduce a multi-modal embedding network and a co-attention mechanism in DPLink to deal with the low-quality problem of mobility data. By conducting extensive experiments on two real-life ground-truth mobility datasets with eight baselines, we demonstrate that DPLink outperforms the state-of-the-art solutions by more than 15% in terms of hit-precision. Moreover, it is expandable to add external geographical context data and works stably with heterogeneous noisy mobility traces. Our code is publicly available1.

Computing Trajectory Similarity in Linear Time: A Generic Seed-Guided Neural Metric Learning Approach

Abstract: Trajectory similarity computation is a fundamental problem for various applications in trajectory data analysis. However, the high computation cost of existing trajectory similarity measures has become the key bottleneck for trajectory analysis at scale. While there have been many research efforts for reducing the complexity, they are specific to one similarity measure and often yield limited speedups. We propose NeuTraj to accelerate trajectory similarity computation. NeuTraj is generic to accommodate any existing trajectory measure and fast to compute the similarity of a given trajectory pair in linear time. Furthermore, NeuTraj is elastic to collaborate with all spatial-based trajectory indexing methods to reduce the search space. NeuTraj samples a number of seed trajectories from the given database, and then uses their pair-wise similarities as guidance to approximate the similarity function with a neural metric learning framework. NeuTraj features two novel modules to achieve accurate approximation of the similarity function: (1) a spatial attention memory module that augments existing recurrent neural networks for trajectory encoding; and (2) a distance-weighted ranking loss that effectively transcribes information from the seed-based guidance. With these two modules, NeuTraj can yield high accuracies and fast convergence rates even if the training data is small. Our experiments on two real-life datasets show that NeuTraj achieves over 80% accuracy on Fre chet, Hausdorff, ERP and DTW measures, which outperforms state-of-the-art baselines consistently and significantly. It obtains 50x-1000x speedup over bruteforce methods and 3x-500x speedup over existing approximate algorithms, while yielding more accurate approximations of the similarity functions.

DPPA2/4 and SUMO E3 ligase PIAS4 opposingly regulate zygotic transcriptional program

Abstract: The molecular mechanism controlling the zygotic genome activation (ZGA) in mammals remains poorly understood. The 2-cell (2C)-like cells spontaneously emerging from cultures of mouse embryonic stem cells (ESCs) share some key transcriptional and epigenetic programs with 2C-stage embryos. By studying the transition of ESCs into 2C-like cells, we identified developmental pluripotency associated 2 and 4 (Dppa2/4) as important regulators controlling zygotic transcriptional program through directly up-regulating the expression of double homeobox (Dux). In addition, we found that DPPA2 protein is sumoylated and its activity is negatively regulated by small ubiquitin-like modifier (Sumo) E3 ligase protein inhibitor of activated STAT 4 (PIAS4). PIAS4 is down-regulated during ZGA process and during transitioning of ESCs into 2C-like cells. Depleting Pias4 or overexpressing Dppa2/4 is sufficient to activate 2C-like transcriptional program, whereas depleting Dppa2/4 or forced expression of Pias4 or Sumo2–Dppa2 inhibits 2C-like transcriptional program. Furthermore, ectopic expression of Pias4 or Sumo2–Dppa2 impairs early mouse embryo development. In summary, our study identifies key molecular rivals consisting of transcription factors and a Sumo2 E3 ligase that regulate zygotic transcriptional program upstream of Dux.

Isolated Iron Single-Atomic Site-Catalyzed Chemoselective Transfer Hydrogenation of Nitroarenes to Arylamines.

Abstract: Selective hydrogenation of nitroarenes to arylamines is a great challenge because of the complicated mechanism and competitive hydrogenation of reducible functional groups. Isolated single-atomic s...