Goldsteinrosario6719

Volatile compounds of raw and cooked green kohlrabi were investigated using a sensomics approach. A total of 55 odor-active compounds were detected and identified in raw and cooked green kohlrabi using GC-O. Twenty-eight odor-active compounds with high flavor dilution (FD) factors ranging from 64 to 1024 were quantitated, and odor activity values (OAVs) were determined. Eight compounds showed high OAVs in raw and cooked kohlrabi five sulfur compounds (dimethyl trisulfide, methyl 2-methyl-3-furyl disulfide, and three isothiocyanates (1-isothiocyanato-3-(methylsulfanyl)propane, benzyl isothiocyanate, and 1-isothiocyanato-4-(methylsulfanyl)butane)), two lipid oxidation products (1-octen-3-one and trans-4,5-epoxy-(2E)-dec-2-enal), and 2-isopropyl-3-methoxypyrazine. Among these, the sulfur compounds contributed most to the overall smell of the raw and cooked vegetables. The quantitation analysis indicates that the eight odorants are the backbone compounds for raw and cooked kohlrabi. The OAVs for the backbone compounds and also for minor odorants are clearly higher in raw kohlrabi than in the cooked one. Differences can be explained by the influence of the cooking process.As molecular dynamics simulations increase in complexity, new analysis tools are necessary to facilitate interpreting the results. Lipids, for instance, are known to form many complicated morphologies, because of their amphipathic nature, becoming more intricate as the particle count increases. A few lipids might form a micelle, where aggregation of tens of thousands could lead to vesicle formation. Millions of lipids comprise a cell and its organelle membranes, and are involved in processes such as neurotransmission and transfection. To study such phenomena, it is useful to have analysis tools that understand what is meant by emerging entities such as micelles and vesicles. Studying such systems at the particle level only becomes extremely tedious, counterintuitive, and computationally expensive. To address this issue, we developed a method to track all the individual lipid leaflets, allowing for easy and quick detection of topological changes at the mesoscale. By using a voxel-based approach and focusing on locality, we forego costly geometrical operations without losing important details and chronologically identify the lipid segments using the Jaccard index. Thus, we achieve a consistent sequential segmentation on a wide variety of (lipid) systems, including monolayers, bilayers, vesicles, inverted hexagonal phases, up to the membranes of a full mitochondrion. It also discriminates between adhesion and fusion of leaflets. We show that our method produces consistent results without the need for prefitting parameters, and segmentation of millions of particles can be achieved on a desktop machine.Hydrophilic gold nanoclusters (Au NCs) whose physical and chemical properties are not susceptible to large changes in pH are greatly desired for diverse applications. Here, we design Au NCs protected by a hydroxyl-thiol ligand (e.g., 1-thioglycerol (TG)) with a molecular formula of Au34(TG)22 as a proof-of-concept for a Au NC model with near-neutral surface charge. Unlike hydrophilic thiols with charged functional groups (e.g., carboxylate-thiol) that are usually used for hydrophilic Au NCs, this type of Au NCs is protected by hydroxyl-thiols, which are less susceptible to the prevailing pH conditions as the hydroxyl group is less acidic than water. More interestingly, the resulting Au NCs also possess pH-independent fluorescence intensity, making them suitable for applications under strong acidic conditions, which are currently not available in the reported hydrophilic Au NCs.The boundary between molecular and metallic gold nanoclusters is of special interest. The difficulty in obtaining atomically precise nanoclusters larger than 2 nm limits the determination of such a boundary. The synthesis and total structural determination of the largest all-alkynyl-protected gold nanocluster (Ph4P)6[Au156(C≡CR)60] (R = 4-CF3C6H4-) (Au156) are reported. It presents an ideal platform for studying the relationship between the structure and the metallic nature. Au156 has a rod shape with the length and width of the kernel being 2.38 and 2.04 nm, respectively. The cluster contains a concentric Au126 core structure (Au46@Au50@Au30) protected by 30 linear RC≡C-Au-C≡CR staple motifs. It is interesting that Au156 displays multiple excitonic peaks in the steady-state absorption spectrum (molecular) and pump-power-dependent excited-state dynamics as revealed in the transient absorption spectrum (metallic), which indicates that Au156 is a critical crossover cluster for the transition from molecular to metallic state. Au156 is the smallest-sized gold nanocluster showing metal-like electron dynamics, and it is recognized that the cluster shape is one of the important factors determining the molecular or metallic nature of a gold nanocluster.The BaAl4 prototype structure and its derivatives have been identified to host several topological quantum materials and noncentrosymmetric superconductors. Single crystals up to ∼3 mm × 3 mm × 5 mm of Ln2Co3Ge5 (Ln = Pr, Nd, and Sm) are obtained via flux growth utilizing Sn as metallic flux. The crystal structure is isostructural to the Lu2Co3Si5 structure type in the crystallographic space group C2/c. The temperature-dependent magnetization indicates magnetic ordering at 30 K for all three compounds. Pr2Co3Ge5 and Nd2Co3Ge5 exhibit complex magnetic behavior with spin reorientations before ordering antiferromagnetically around 6 K, whereas Sm2Co3Ge5 shows a clear antiferromagnetic behavior at 26 K. The structures and properties of Ln2Co3Ge5 (Ln = Pr, Nd, and Sm) are compared to those of the ThCr2Si2 and BaNiSn3 structure types. Herein, we present the optimized crystal growth, structure, and physical properties of Ln2Co3Ge5 (Ln = Pr, Nd, and Sm).Guanidinium ion is a toxic cellular metabolite. The ykkC-III riboswitch, an mRNA stretch, regulates the gene expression by undergoing a conformational change in response to the binding of a free guanidinium ion and thereby plays a potentially important role in alleviating guanidinium toxicity in cells. An experimental crystal structure of the guanidinium-bound aptamer domain of the riboswitch from Thermobifida Fusca revealed the overall RNA architecture and mapped the specific noncovalent interactions that stabilize the ligand within the binding pocket aptamer. However, details of how the aptamer domain discriminates the cognate ligand from its closest structurally analogous physiological metabolites (arginine and urea), and how the binding of cognate ligand arrays information from the aptamer domain to the expression platform for regulating the gene expression, are not well understood. To fill this void, we perform a cumulative of 2 μs all-atom explicit-solvent molecular dynamics (MD) simulations on the fullic class of riboswitches and may hopefully inspire future studies to further understand the gene regulation by riboswitches.Computing quantum chemical properties of small molecules and polymers can provide insights valuable into physicists, chemists, and biologists when designing new materials, catalysts, biological probes, and drugs. Deep learning can compute quantum chemical properties accurately in a fraction of time required by commonly used methods such as density functional theory. Most current approaches to deep learning in quantum chemistry begin with geometric information from experimentally derived molecular structures or pre-calculated atom coordinates. These approaches have many useful applications, but they can be costly in time and computational resources. In this study, we demonstrate that accurate quantum chemical computations can be performed without geometric information by operating in the coordinate-free domain using deep learning on graph encodings. Coordinate-free methods rely only on molecular graphs, the connectivity of atoms and bonds, without atom coordinates or bond distances. We also find that the choice of graph-encoding architecture substantially affects the performance of these methods. The structures of these graph-encoding architectures provide an opportunity to probe an important, outstanding question in quantum mechanics what types of quantum chemical properties can be represented by local variable models? We find that Wave, a local variable model, accurately calculates the quantum chemical properties, while graph convolutional architectures require global variables. Furthermore, local variable Wave models outperform global variable graph convolution models on complex molecules with large, correlated systems.Among the parameters determining the efficiency of an organic solar cell, the open-circuit voltage (VOC) is the one with most room for improvement. Existing models for the description of VOC assume that photogenerated charge carriers are thermalized. Here, we demonstrate that quasi-equilibrium concepts cannot fully describe VOC of disordered organic devices. selleck products For two representative donoracceptor blends, it is shown that VOC is actually 0.1-0.2 V higher than it would be if the system was in thermodynamic equilibrium. Extensive numerical modeling reveals that the excess energy is mainly due to incomplete relaxation in the disorder-broadened density of states. These findings indicate that organic solar cells work as nonequilibrium devices, in which part of the photon excess energy is harvested in the form of an enhanced VOC.The reaction of excited nitrogen atoms N(2D) with CH3CCH (methylacetylene) was investigated under single-collision conditions by the crossed molecular beams (CMB) scattering method with mass spectrometric detection and time-of-flight analysis at the collision energy (Ec) of 31.0 kJ/mol. Synergistic electronic structure calculations of the doublet potential energy surface (PES) were performed to assist the interpretation of the experimental results and characterize the overall reaction micromechanism. Theoretically, the reaction is found to proceed via a barrierless addition of N(2D) to the carbon-carbon triple bond of CH3CCH and an insertion of N(2D) into the CH bond of the methyl group, followed by the formation of cyclic and linear intermediates that can undergo H, CH3, and C2H elimination or isomerize to other intermediates before unimolecularly decaying to a variety of products. Kinetic calculations for addition and insertion mechanisms and statistical (Rice-Ramsperger-Kassel-Marcus) computations of produial precursors to form other nitriles (C2N2, C3N) or more complex organic species containing N atoms in planetary atmospheres, such as those of Titan and Pluto. Overall, the results are expected to have a potentially significant impact on the understanding of the gas-phase chemistry of Titan's atmosphere and the modeling of that atmosphere.To overcome the resistance of cancer cells to platinum-based drugs and effectively suppress tumor growth, we developed a novel indium (In) agent based on liposomes (Lips). Thus, we not only obtained an In(III) thiosemicarbazone agent (5b) with remarkable cytotoxicity by optimizing a series of In(III) thiosemicarbazone agents (1b-5b) but also successfully constructed a novel 5b-loaded Lip (5b-Lip) delivery system. Importantly, in vitro and in vivo results revealed that 5b/5b-Lip overcame the tumor cell resistance and effectively inhibited MCF-7/DDP tumor growth. In addition, Lips improved the intracellular accumulation of 5b. We also confirmed the mechanism by which 5b/5b-Lip overcomes breast cancer cell resistance. 5b/5b-Lip cannot act against DNA in cancer cells but attacks the two cell components in the tumor microenvironment, namely, by inducing apoptosis and lethal autophagy of cancer cells and resetting tumor-promoting M2 macrophages to the tumor-killing M1 phenotype.