Epsteinhernandez6559

The valence electron structures (VESs) and thermal and magnetic properties of R2Co17 intermetallics with rhombohedral (R = Ce, Pr, Nd, Sm, Gd, and Tb) and hexagonal (R = Y, Dy, Ho, and Er) structures are studied systematically with the empirical electron theory of solids and molecules (EET). The calculated values, which cover the bond length, cohesive energy, melting point, magnetic moment, and Curie temperature, fit the experimental ones well. The study reveals that the thermal and magnetic properties of R2Co17 are strongly related to their VESs. It shows that the properties of R2Co17 can be modulated by covalence electron number nc/atom for cohesive energy and melting point, the 3d magnetic electrons of various Co sublattices for magnetic moment, the electron transformation from covalence electrons to 3d magnetic electrons for the moments of various Co sublattices, and molecular moment for Curie temperature. The structural stability of R2Co17 depends upon the distribution probability of covalence electrons on various bonds. The pseudobinary La-Co 217 phase can be stabilized by doping a transition metal into La2Co17 by modulating the covalence electron number per Co atom to be very close to the stable nc/Co range of rhombohedral LR2Co17 (LR=light rare earth).Natural organic matter (NOM) components measured with ultrahigh-resolution mass spectrometry (UHRMS) are often assessed by molecular formula-based indices, particularly related to their aromaticity, which are further used as proxies to explain biogeochemical reactivity. An aromaticity index (AI) is calculated mostly with respect to carboxylic groups abundant in NOM. Here, we propose a new constrained AIcon based on the measured distribution of carboxylic groups among individual NOM components obtained by deuteromethylation and UHRMS. Applied to samples from diverse sources (coal, marine, peat, permafrost, blackwater river, and soil), the method revealed that the most probable number of carboxylic groups was two, which enabled to set a reference point n = 2 for carboxyl-accounted AIcon calculation. The examination of the proposed AIcon showed the smallest deviation to the experimentally determined index for all NOM samples under study as well as for individual natural compounds obtained from the Coconut database. In particular, AIcon performed better than AImod for all compound classes in which aromatic moieties are expected aromatics, condensed aromatics, and unsaturated compounds. Therefore, AIcon referenced with two carboxyl groups is preferred over conventional AI and AImod for biogeochemical studies where the aromaticity of compounds is important to understand the transformations and fate of NOM compounds.Metal-organic frameworks (MOFs) are a promising nanoporous functional material system; however, the practicality of shaping freeform MOF monoliths, while retaining their porosity, remains a challenge. Here, we demonstrate that meniscus-guided three-dimensional (3D) printing can produce pure MOF monoliths with high gas-uptake performance. The method exploits a femtoliter precursor ink meniscus to highly confine and guide supersaturation-driven crystallization in a layer-by-layer manner to print a pure HKUST-1 micro-monolith with a high spatial resolution of less then 3 μm. The proposed 3D printing technique does not involve rheological additives, binders, or mechanical forces. Thus, the resulting HKUST-1 monolith displays a prominently high Brunauer-Emmett-Teller surface area of 1192 m2/g, which is superior to monoliths produced using other 3D printing approaches. This technique enables both structural design freedom and high material performance in the manufacturing of MOFs for practical use.Unravelling unique molecular targets specific to viruses is challenging yet critical for diagnosing emerging viral diseases. Nucleic acids and proteins are the major targets in diagnostic assays of viral pathogens. Identification of novel sequences and conformations of nucleic acids as targets is desirable for developing diagnostic assays specific to a virus of interest. Here, we disclose the identification and characterization of a highly conserved antiparallel G-quadruplex (GQ)-forming DNA sequence present within the SARS-CoV-2 genome. The two-quartet GQ with unique loop compositions formed a distinct recognition motif. Design, synthesis, and fine tuning of structure-activity of a set of small molecules led to the identification of a benzobisthiazole-based fluorogenic probe which unambiguously recognizes the target SARS-CoV-2 GQ DNA. A robust cost-effective assay was developed through thermal cycler PCR-based amplification of the antiparallel GQ-forming ORF1ab region of the SARS-CoV-2 genome and endpoint fluorescence detection with the probe. An exclusive pH window (3.5-4) helped trigger reliable conformational polymorphism (RCP) involving DNA duplex to GQ transformation, which aided the development of a GQ-RCP platform for the diagnosis of SARS-CoV-2 clinical samples. This general strategy can be adapted for the development of specific diagnostic assays targeting different noncanonical nucleic acid sequences.Asymmetric induction of metal clusters by ligation of chiral ligands is intriguing in terms of the mechanism of chirality transfer and the stability of the resulting chiral structure. Here we report the asymmetric induction of C-centered hexagold(I) CAuI6 clusters into an asymmetrically twisted structure through monodentate, chiral benzimidazolylidene-based N-heterocyclic carbene (NHC) ligands. X-ray diffraction analysis revealed that the NHC-ligated CAuI6 cluster was diastereoselectively twisted with directionally selective, bond length expansion, and contraction of the Au···Au contacts and that the original cluster with high symmetry was transformed into an optically pure, asymmetric CAuI6 cluster with C1 symmetry. Moreover, the circular dichroism spectroscopy and the time-dependent density functional theory calculation confirmed that the asymmetrically twisted CAuI6 structure was maintained even in solution. Such asymmetric induction of configurationally stable metal clusters would greatly expand the molecular design possibilities of asymmetric catalysts and chiroptical materials by utilizing library chiral NHC ligands.Accurate assignment of protein function from sequence remains a fascinating and difficult challenge. The periplasmic-binding protein (PBP) superfamily present an interesting case of function prediction because they are both ubiquitous in prokaryotes and tend to diversify through gene duplication "explosions" that can lead to large numbers of paralogs in a genome. An engineered version of the moderately thermostable glucose-binding PBP from Escherichia coli has been used successfully as a reagentless fluorescent biosensor both in vitro and in vivo. To develop more robust sensors that meet the challenges of real-world applications, we report the discovery of thermostable homologues that retain a glucose-mediated conformationally coupled fluorescence response. Accurately identifying a glucose-binding PBP homologue among closely related paralogs is challenging. We demonstrate that a structure-based method that filters sequences by residues that bind glucose in an archetype structure is highly effective. Using fully sequenced bacterial genomes, we found that this filter reduced high paralog numbers to single hits in a genome, consistent with the accurate separation of glucose binding from other functions. We expressed engineered proteins for eight homologues, chosen to represent different degrees of sequence identity, and tested their glucose-mediated fluorescence responses. We accurately predicted the presence of glucose binding down to 31% sequence identity. We have also successfully identified suitable candidates for next-generation robust, fluorescent glucose sensors.Glycans are critical to every facet of biology and medicine, from viral infections to embryogenesis. find more Tools to study glycans are rapidly evolving; however, the majority of our knowledge is deeply dependent on binding by glycan binding proteins (e.g., lectins). The specificities of lectins, which are often naturally isolated proteins, have not been well-defined, making it difficult to leverage their full potential for glycan analysis. Herein, we use a combination of machine learning algorithms and expert annotation to define lectin specificity for this important probe set. Our analysis uses comprehensive glycan microarray analysis of commercially available lectins we obtained using version 5.0 of the Consortium for Functional Glycomics glycan microarray (CFGv5). This data set was made public in 2011. We report the creation of this data set and its use in large-scale evaluation of lectin-glycan binding behaviors. Our motif analysis was performed by integrating 68 manually defined glycan features with systematic probing of computational rules for significant binding motifs using mono- and disaccharides and linkages. Combining machine learning with manual annotation, we create a detailed interpretation of glycan-binding specificity for 57 unique lectins, categorized by their major binding motifs mannose, complex-type N-glycan, O-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.The intranasal (i.n.) route is an ideal vaccination approach for infectious respiratory diseases like influenza. Polycationic polyethylenimine (PEI) could form nanoscale complexes with negatively charged viral glycoproteins. Here we fabricated PEI-hemagglutinin (HA) and PEI-HA/CpG nanoparticles and investigated their immune responses and protective efficacies with an i.n. vaccination regimen in mice. Our results revealed that the nanoparticles significantly enhanced HA immunogenicity, providing heterologous cross-protection. The conserved HA stalk region induced substantial antibodies in the nanoparticle immunization groups. In contrast to the Th2-biased, IgG1-dominant antibody response generated by PEI-HA nanoparticles, PEI-HA/CpG nanoparticles generated more robust and balanced IgG1/IgG2a antibody responses with augmented neutralization activity and Fc-mediated antibody-dependent cellular cytotoxicity (ADCC). PEI-HA/CpG nanoparticles also induced enhanced local and systemic cellular immune responses. These immune responses did not decay over six months of observation postimmunization. PEI and CpG synergized these comprehensive immune responses. Thus, the PEI-HA/CpG nanoparticle is a potential cross-protective influenza vaccine candidate. Polycationic PEI nanoplatforms merit future development into mucosal vaccine systems.Among various H2 purification technologies, the use of membrane technology has been considered an ecofriendly approach for addressing the increasing hydrogen demand. Although many H2-selective membrane materials have been reported, processing them into hollow fibers or thin-film composites (TFCs) via traditional methods either affects the performance of the materials or renders their further processing into applicable membrane forms infeasible. Herein, we propose a water-casting method for fabricating TFC membranes for hydrogen purification with high permselectivity. The film integrity and thickness were manipulated by controlling the spreadability of the casting solution, and the resultant water-cast TFC membrane that comprised an ∼30 nm selective layer demonstrated high H2 permeance and H2/CH4 selectivity of approximately 190 GPU and 100, respectively, under optimized conditions. We performed a mixed-gas permeation test using a simulated off-gas of steam-methane reforming from natural gas in a single-stage system and obtained hydrogen gas of >99 mol % purity.