13 research outputs found

    Poly[di-μ9-citrato-cobalt(II)tetra­sodium]

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    The title compound, [CoNa4(C6H5O7)2]n, was obtained under hydro­thermal conditions as a minor product. The Co2+ cation is located on a crystallographic inversion center and is coordinated by six O atoms from two different citrate units, forming a [Co(C6H5O7)2]4− building unit with Co—O bond lengths between 2.0578 (17) and 2.0813 (16) Å. The structure features two crystallographically independent Na+ ions. The first Na+ cation is five-coordinated by O atoms of five carboxylate groups from four different citrate anions. The second Na+ cation is surrounded by six O atoms of five carboxylate groups from five different citrate anions. The carboxylate groups of the citrate are completely depronona­ted, the hydroxyl group, however, is not. It is coordinated to the Co2+ cation, and through an O—H⋯O hydrogen bond connected to a neighboring [Co(C6H5O7)2]4− building unit. The coordination modes of the carboxyl­ate O atoms vary, with one O atom being coordinated to three different Na+ cations, three are bridging O atoms bound to two Na+ cations and two are connected to a Co2+ cation and a Na+ cation, respectively. Through these inter­connections, the basic [Co(C6H5O7)2]4− building units are linked with each other through coordination of their carboxyl­ate groups to the Na+ cations, forming a three-dimensional framework

    catena-Poly[[[triaqua­copper(II)]-μ-2,2′-bipyridine-3,3′-dicarboxyl­ato-κ3 N,N′:O] monohydrate]

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    The title compound, {[Cu(C12H6N2O4)(H2O)3]·H2O}n, was synthesized under hydro­thermal conditions. The Cu2+ ion is six-coordinated by three water O atoms, and two N atoms and one O atom of the 2,2′-bipyridine-3,3′-dicarboxyl­ate bridging ligand in a sligthly distorted octa­hedral environment. The 2,2-bipyridine-3,3′-dicarboxyl­ate bridges link the Cu2+ ions into chains along the b-axis direction. These chains are further linked by O—H⋯O hydrogen bonds involving the water solvent mol­ecules, forming a three-dimensional framework

    Identification of Heat-Tolerant Genes in Non-Reference Sequences in Rice by Integrating Pan-Genome, Transcriptomics, and QTLs.

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    The availability of large-scale genomic data resources makes it very convenient to mine and analyze genes that are related to important agricultural traits in rice. Pan-genomes have been constructed to provide insight into the genome diversity and functionality of different plants, which can be used in genome-assisted crop improvement. Thus, a pan-genome comprising all genetic elements is crucial for comprehensive variation study among the heat-resistant and -susceptible rice varieties. In this study, a rice pan-genome was firstly constructed by using 45 heat-tolerant and 15 heat-sensitive rice varieties. A total of 38,998 pan-genome genes were identified, including 37,859 genes in the reference and 1141 in the non-reference contigs. Genomic variation analysis demonstrated that a total of 76,435 SNPs were detected and identified as the heat-tolerance-related SNPs, which were specifically present in the highly heat-resistant rice cultivars and located in the genic regions or within 2 kbp upstream and downstream of the genes. Meanwhile, 3214 upregulated and 2212 downregulated genes with heat stress tolerance-related SNPs were detected in one or multiple RNA-seq datasets of rice under heat stress, among which 24 were located in the non-reference contigs of the rice pan-genome. We then mapped the DEGs with heat stress tolerance-related SNPs to the heat stress-resistant QTL regions. A total of 1677 DEGs, including 990 upregulated and 687 downregulated genes, were mapped to the 46 heat stress-resistant QTL regions, in which 2 upregulated genes with heat stress tolerance-related SNPs were identified in the non-reference sequences. This pan-genome resource is an important step towards the effective and efficient genetic improvement of heat stress resistance in rice to help meet the rapidly growing needs for improved rice productivity under different environmental stresses. These findings provide further insight into the functional validation of a number of non-reference genes and, especially, the two genes identified in the heat stress-resistant QTLs in rice

    Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

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    Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ‘‘SpatioTemporal Omics Consortium’’ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen, China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute, Boston, USA) for their help. This work was supported by the grant of Top Ten Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu was supported by the National Natural Science Foundation of China (31900466) and Miguel A. Esteban’s laboratory at the Guangzhou Institutes of Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075).S

    MPI Parallelization of Numerical Simulations for Pulsed Vacuum Arc Plasma Plumes Based on a Hybrid DSMC/PIC Algorithm

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    The transport characteristics of the unsteady flow field in rarefied plasma plumes is crucial for a pulsed vacuum arc in which the particle distribution varies from 1016 to 1022 m−3. The direct simulation Monte Carlo (DSMC) method and particle-in-cell (PIC) method are generally combined to study this kind of flow field. The DSMC method simulates the motion of neutral particles, while the PIC method simulates the motion of charged ions. A hybrid DSMC/PIC algorithm is investigated here to determine the unsteady axisymmetric flow characteristics of vacuum arc plasma plume expansion. Numerical simulations are found to be consistent with the experiments performed in the plasma mass and energy analyzer (EQP). The electric field is solved by Poisson’s equation, which is usually computationally expensive. The compressed sparse row (CSR) format is used to store the huge diluted matrix and PETSc library to solve Poisson’s equation through parallel calculations. Double weight factors and two timesteps under two grid sets are investigated using the hybrid DSMC/PIC algorithm. The fine PIC grid is nested in the coarse DSMC grid. Therefore, METIS is used to divide the much smaller coarse DSMC grid when dynamic load imbalances arise. Two parameters are employed to evaluate and distribute the computational load of each process. Due to the self-adaption of the dynamic-load-balancing parameters, millions of grids and more than 150 million particles are employed to predict the transport characteristics of the rarefied plasma plume. Atomic Ti and Ti2+ are injected into the small cylinders. The comparative analysis shows that the diffusion rate of Ti2+ is faster than that of atomic Ti under the electric field, especially in the z-direction. The fully diffuse reflection wall model is adopted, showing that neutral particles accumulate on the wall, while charged ions do not—due to their self-consistent electric field. The maximum acceleration ratio is about 17.94

    MPI Parallelization of Numerical Simulations for Pulsed Vacuum Arc Plasma Plumes Based on a Hybrid DSMC/PIC Algorithm

    No full text
    The transport characteristics of the unsteady flow field in rarefied plasma plumes is crucial for a pulsed vacuum arc in which the particle distribution varies from 1016 to 1022 m−3. The direct simulation Monte Carlo (DSMC) method and particle-in-cell (PIC) method are generally combined to study this kind of flow field. The DSMC method simulates the motion of neutral particles, while the PIC method simulates the motion of charged ions. A hybrid DSMC/PIC algorithm is investigated here to determine the unsteady axisymmetric flow characteristics of vacuum arc plasma plume expansion. Numerical simulations are found to be consistent with the experiments performed in the plasma mass and energy analyzer (EQP). The electric field is solved by Poisson’s equation, which is usually computationally expensive. The compressed sparse row (CSR) format is used to store the huge diluted matrix and PETSc library to solve Poisson’s equation through parallel calculations. Double weight factors and two timesteps under two grid sets are investigated using the hybrid DSMC/PIC algorithm. The fine PIC grid is nested in the coarse DSMC grid. Therefore, METIS is used to divide the much smaller coarse DSMC grid when dynamic load imbalances arise. Two parameters are employed to evaluate and distribute the computational load of each process. Due to the self-adaption of the dynamic-load-balancing parameters, millions of grids and more than 150 million particles are employed to predict the transport characteristics of the rarefied plasma plume. Atomic Ti and Ti2+ are injected into the small cylinders. The comparative analysis shows that the diffusion rate of Ti2+ is faster than that of atomic Ti under the electric field, especially in the z-direction. The fully diffuse reflection wall model is adopted, showing that neutral particles accumulate on the wall, while charged ions do not—due to their self-consistent electric field. The maximum acceleration ratio is about 17.94
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