12 methods for taking your manuscript published

Amyloid-β (Aβ) plaques, which form by aggregation of harmless Aβ peptide monomers into larger fibrils, are characteristic of neurodegenerative disorders such as Alzheimer's disease. Efforts to treat Alzheimer's disease focus on stopping or reversing the aggregation process that leads to fibril formation. However, effective treatments are elusive due to certain unknown aspects of the process. Many hypotheses point to disruption of cell membranes by adsorbed Aβ monomers or oligomers, but how Aβ behaves and aggregates on surfaces of widely varying properties, such as those present in a cell, is unclear. Elucidating the effects of various surfaces on the dynamics of Aβ and the kinetics of the aggregation process from bulk solution to a surface-adsorbed multimer can help identify what drives aggregation, leading to new methods of intervention by inhibitory drugs or other means. In this work, we used all-atom Brownian dynamics simulations to study the association of two distinct Aβ42 monomer conformations with a surface-adsorbed or free-floating Aβ42 dimer. We calculated the association time, surface interaction energy, surface diffusion coefficient, surface residence time, and the mechanism of association on four different surfaces and two different bulk solution scenarios. In the presence of a surface, the majority of monomers underwent a two-dimensional surface-mediated association that depended primarily on an Aβ42 electrostatic interaction with the self-assembled monolayer (SAM) surfaces. Moreover, aggregation could be inhibited greatly by surfaces with high affinity for Aβ42 and heterogeneous charge distribution. Our results can be used to identify new opportunities for disrupting or reversing the Aβ42 aggregation process.Depleted oil reservoirs are considered a viable solution to the global challenge of CO2 storage. A key concern is whether the wells can be suitably sealed with cement to hinder the escape of CO2. Under reservoir conditions, CO2 is in its supercritical state, and the high pressures and temperatures involved make real-time microscopic observations of cement degradation experimentally challenging. Here, we present an in situ 3D dynamic X-ray micro computed tomography (μ-CT) study of well cement carbonation at realistic reservoir stress, pore-pressure, and temperature conditions. The high-resolution time-lapse 3D images allow monitoring the progress of reaction fronts in Portland cement, including density changes, sample deformation, and mineral precipitation and dissolution. By switching between flow and nonflow conditions of CO2-saturated water through cement, we were able to delineate regimes dominated by calcium carbonate precipitation and dissolution. For the first time, we demonstrate experimentally the impact of the flow history on CO2 leakage risk for cement plugging. In-situ μ-CT experiments combined with geochemical modeling provide unique insight into the interactions between CO2 and cement, potentially helping in assessing the risks of CO2 storage in geological reservoirs.Drug metabolism is a common cause of adverse drug reactions. Drug molecules can be metabolized into reactive metabolites, which can conjugate to biomolecules, like protein and DNA, in a process termed bioactivation. To mitigate adverse reactions caused by bioactivation, both experimental and computational screening assays are utilized. Experimental assays for assessing the formation of reactive metabolites are low throughput and expensive to perform, so they are often reserved until later stages of the drug development pipeline when the drug candidate pools are already significantly narrowed. In contrast, computational methods are high throughput and cheap to perform to screen thousands to millions of compounds for potentially toxic molecules during the early stages of the drug development pipeline. Commonly used computational methods focus on detecting and structurally characterizing reactive metabolite-biomolecule adducts or predicting sites on a drug molecule that are liable to form reactive metabolites. Dubs-IN-1 mouse Hd product pair with a recall of 88 and 46%, respectively. Using likelihood scoring, XenoNet also achieves a top-one pathway and intermediate metabolite accuracy of 93.6 and 51.9%, respectively. We further validate XenoNet against prior methods for metabolite prediction. XenoNet significantly outperforms all prior methods across multiple metrics. XenoNet is available at https//swami.wustl.edu/xenonet.Nematode-trapping fungus Arthrobotrys oligospora can produce a type of sesquiterpenyl epoxy-cyclohexenoid (SEC) metabolites that are regarded as characteristic chemtaxonomic markers. Here we reported investigation on the functions of a putatively cupin-like family gene 277 and a dehydrogenase gene 279, respectively, by gene engineering, chemical metabolite profiling and phenotype analysis. Ten targeted metabolites were isolated from two mutants 277 and 279 and four novel metabolites including three polyketide-terpenoid (PK-TP) hybrid ones were characterized. Metabolite C277-1 from mutant 277 shared the characteristic feature of the first and simplest PK-TP hybrid precursor, prenyl toluquinol, and metabolites C279-1 and C279-2 from mutant 279 shared the basic carbon skeleton of the key PK-TP hybrid precursor, farnesyl toluquinol, for biosynthesis of SEC metabolites. These results suggested that gene 277 should be involved in biosynthesis of the second prenyl unit for farnesyl toluquinol precursor, and gene 279 might be responsible for the diagnostic epoxy formation. Further analysis revealed that genes 277 and 279 might play roles in fungal conidiation, predatory trap formation and nematode-capturing ability.A series of six-coordinate [Cu(L)L1][BF4]2 (L1 = 2,6-bis1-oxyl-4,4,5,5-tetramethyl-4,5-dihydro-1H-imidazol-2-ylpyridine) complexes are reported. Ferromagnetic coupling between the Cu and L1 ligand spins is enhanced by an L coligand with distal methyl substituents, which is attributed to a sterically induced suppression of its Jahn-Teller distortion.Following our recent work to reduce a dimension of a set of reference structures along the intrinsic reaction coordinate (IRC) by a classical multidimensional scaling (CMDS) approach (J. Chem. Theory Comput. 2018, 14, 4263-4270), we propose the method to project on-the-fly trajectories into a reduced-dimension subspace determined by the IRC network, using the out-of-sample extension of CMDS. The method was applied to the SN2 reaction, OH- + CH3F, in which trajectories show a bifurcating nature around the highly curved region of the IRC path, and to the structural transformation of Au5 cluster in which the global reaction path network consists of five equilibrium structures and 14 IRCs. It was demonstrated that the present analysis can visualize the dynamics effect by showing a dynamic reaction route on the basis of the static reaction paths.