14 research outputs found

    Synthesis of Biaryl Carboxylic Acids through a Cascade Suzuki–Miyaura Coupling/Friedel–Crafts Alkylation/Lewis-Acid-Catalyzed Rearrangement/Aromatization Process

    No full text
    In this study, we present a series of 1,3-dicarbonyls that can undergo a cascade Suzuki coupling, followed by a Friedel–Crafts reaction to produce molecules containing polycyclic alcohols. These polycyclic alcohols can then be converted into biaryl carboxylic acids through ring-opening rearrangement reactions catalyzed by a Lewis acid. The Friedel–Crafts reaction exhibits selective para-positioning of the hydroxyl group and demonstrates good compatibility with functional groups with a yield of up to 82%. Substrates with substituted hydroxyl groups can also be converted into biaryl carboxylic acids through a Lewis-acid-catalyzed ring-opening rearrangement

    Direct Catalytic Asymmetric Reductive Amination of Simple Aromatic Ketones

    No full text
    A green method for chiral amine synthesis, the direct catalytic asymmetric reductive amination, was developed. Phenylhydrazide is an ideal nitrogen source for reductive amination. Molecular sieves play dual roles in this reaction. They help to remove H<sub>2</sub>O to form imine, as well as promote an imine reduction. f-Binaphane minimizes the inhibition effect from amines and helps the coordination of sterically demanding imines to the iridium center, thus leading to a smooth reaction

    Iridium Catalysts with f‑Amphox Ligands: Asymmetric Hydrogenation of Simple Ketones

    No full text
    A series of modular and rich electronic tridentate ferrocene aminophosphoxazoline ligands (f-amphox) have been successfully developed and used in iridium-catalytic asymmetric hydrogenation of simple ketones to afford corresponding enantiomerically enriched alcohols under mild conditions with superb activities and excellent enantioselectivities (up to 1 000 000 TON, almost all products up to >99% ee, full conversion). The resulting chiral alcohols and their derivatives are important intermediates in pharmaceuticals

    Optimizing nitrogen application rate and plant density for improving cotton yield and nitrogen use efficiency in the North China Plain - Fig 1

    No full text
    <p>Leaf area index(LAI) of cotton at different growth periods in 2013(A) and 2014(B)Note: D1, D2, D3 indicate planting density at 3.00, 5.25, 7.50 plants m<sup>−2</sup> respectively, and N0, N1, N2, N3, N4 indicate nitrogen application rate at 0, 112.5, 225.0, 337.5 kg ha<sup>−1</sup> respectively. A, B indicate 2013 and 2014. Numbers at the same growth stage followed by the same small alphabet are not significantly different at the 5% level.</p

    iTRAQ-Based Quantitative Proteomic Analysis of Cotton Roots and Leaves Reveals Pathways Associated with Salt Stress

    No full text
    <div><p>Salinity is a major abiotic stress that affects plant growth and development. In this study, we performed a proteomic analysis of cotton roots and leaf tissue following exposure to saline stress. 611 and 1477 proteins were differentially expressed in the roots and leaves, respectively. In the roots, 259 (42%) proteins were up-regulated and 352 (58%) were down-regulated. In the leaves, 748 (51%) proteins were up-regulated and 729 (49%) were down-regulated. On the basis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we concluded that the phenylalanine metabolism and starch and sucrose metabolism were active for energy homeostasis to cope with salt stress in cotton roots. Moreover, photosynthesis, pyruvate metabolism, glycolysis / gluconeogenesis, carbon fixation in photosynthetic organisms and phenylalanine metabolism were inhabited to reduce energy consumption. Characterization of the signaling pathways will help elucidate the mechanism activated by cotton in response to salt stress.</p></div

    Identification and analysis of DEPs from roots and leaves in cotton.

    No full text
    <p>(A) Total spectra, spectra, unique spectra, peptides, unique peptide, and proteins identified from iTRAQ proteomic analysis. (B) Identified proteins were grouped according to the protein mass. (C) Number of peptides that match to proteins as indicated by MASCOT 2.3.02.</p
    corecore