Inhibition Effect and Molecular Mechanisms of Quercetin on the Aß42 Dimer: A Molecular Dynamics Simulation Study.

Amyloid-ß (Aß) dimer as the smallest oligomer has recently been drawing attention due to its neurotoxicity, transient nature, and heterogeneity. The inhibition of Aß dimer's aggregation is the key to primary intervention of Alzheimer's disease. Previous experimental studies have reported that quercetin, the widespread polyphenolic constituent of multiple fruits and vegetables, can hamper the formation of Aß protofibrils and disaggregate Aß fibrils. However, the molecular mechanisms of quercetin in the suppression of the Aß(1-42) dimer's conformational changes still remain elusive. In this work, to investigate the inhibitory mechanisms of quercetin molecules on the Aß(1-42) dimer, an Aß(1-42) dimer based on monomeric the Aß(1-42) peptide with enriched coil structures is constructed. The early molecular mechanisms of quercetin molecules on inhibiting the Aß(1-42) dimer at two different Aß42-to-quercetin molar ratios (1:5 and 1:10) are explored via all-atom molecular dynamics simulations. The results indicate that quercetin molecules can impede the configurational change of the Aß(1-42) dimer. The interactions and the binding affinity between the Aß(1-42) dimer and quercetin molecules in the Aß42 dimer + 20 quercetin system are stronger in comparison with that in the Aß42 dimer + 10 quercetin system. Our work may be helpful in developing new drug candidates for preventing the conformational transition and further aggregation of the Aß dimer.

Constructing the boundary between potent and ineffective siRNAs by MG-algorithm with C-features.

BACKGROUND: In siRNA based antiviral therapeutics, selection of potent siRNAs is an indispensable step, but these commonly used features are unable to construct the boundary between potent and ineffective siRNAs. RESULTS: Here, we select potent siRNAs by removing ineffective ones, where these conditions for removals are constructed by C-features of siRNAs, C-features are generated by MG-algorithm, Icc-cluster and the different combinations of some commonly used features, MG-algorithm and Icc-cluster are two different algorithms to search the nearest siRNA neighbors. For the ineffective siRNAs in test data, they are removed from test data by I-iteration, where I-iteration continually updates training data by adding these successively removed siRNAs. Furthermore, the efficacy of siRNAs of test data is predicted by their nearest neighbors of training data. CONCLUSIONS: By siRNAs of Hencken dataset, results show that our algorithm removes almost ineffective siRNAs from test data, gives the clear boundary between potent and ineffective siRNAs, and accurately predicts the efficacy of siRNAs also. We suggest that our algorithm can provide new insights for selecting the potent siRNAs.

Enhanced Stability and Mechanical Properties of a Graphene-Protein Nanocomposite Film by a Facile Non-Covalent Self-Assembly Approach.

Graphene-based nanocomposite films (NCFs) are in high demand due to their superior photoelectric and thermal properties, but their stability and mechanical properties form a bottleneck. Herein, a facile approach was used to prepare nacre-mimetic NCFs through the non-covalent self-assembly of graphene oxide (GO) and biocompatible proteins. Various characterization techniques were employed to characterize the as-prepared NCFs and to track the interactions between GO and proteins. The conformational changes of various proteins induced by GO determined the film-forming ability of NCFs, and the binding of bull serum albumin (BSA)/hemoglobin (HB) on GO's surface was beneficial for improving the stability of as-prepared NCFs. Compared with the GO film without any additive, the indentation hardness and equivalent elastic modulus could be improved by 50.0% and 68.6% for GO-BSA NCF; and 100% and 87.5% for GO-HB NCF. Our strategy should be facile and effective for fabricating well-designed bio-nanocomposites for universal functional applications.

A New Dinuclear Cobalt Complex for Copolymerization of CO2 and Propylene Oxide: High Activity and Selectivity.

Based on the ligand H4Salen-8tBu (salen-4), a new dinuclear cobalt complex (salen-4)[Co(III)TFA]2 (salen-4 = 3,5-di-tert-butylsalicylaldehyde-3,3'-diaminobiphenylamine; TFA = trifluoroacetic acid) has been firstly synthesized and characterized. It shows high catalytic activity for the copolymerization of propylene oxide (PO) and carbon dioxide (CO2), yielding regioregular poly(propylene carbonate) (PPC) with little generation of propylene carbonate (PC) by-product. It has been found that (salen-4)[Co(III)TFA]2 shows higher activity at milder conditions, generating a polymer with maximum Mn of 293 kg/mol and a narrow molecular weight distribution PDI of 1.35. The influences of reaction time, CO2 pressure, reaction temperature, nature of the cocatalyst, catalyst dosage and substrate concentration on the molecular weight, yield and selectivity of the polymer were explored in detail. The results showed that the (salen-4)[Co(III)TFA]2/[PPN]TFA catalyst system demonstrated a remarkable TOF as high as 735 h-1. In addition, a hypothetical catalytic reaction mechanism was proposed based on density functional theory (DFT) calculations and the catalytic reaction results of the (salen-4)[Co(III)TFA]2.

Synthesis and Optimization of Ti/Li/Al Ternary Layered Double Hydroxides for Efficient Photocatalytic Reduction of CO2 to CH4.

A series of Ti/Li/Al ternary layered double hydroxides (TiLiAl-LDHs) with different Ti:Li:Al molar ratios were prepared by a coprecipitation method for photocatalytic CO2 reduction. It was demonstrated that the contents of anions between the layers of Ti/Li/Al-LDHs greatly determined the photocatalytic activity for CO2 reduction. With Ti:Li:Al molar ratios optimized to be 1:3:2, the largest contents of [Formula: see text]- anion and hydroxyl group were obtained for the Ti1Li3Al2-LDHs sample, which exhibited the highest photocatalytic activity for CO2 reduction, with CH4 production rate achieving 1.33 mmol h-1 g-1. Moreover, the theoretical calculations show that Ti1Li3Al2-LDHs is a p-type semiconductor with the narrowest band gap among all the obtained TiLiAl-LDHs. After calcined at high temperatures such as 700 °C, and the obtained TiLiAl-700 sample showed much increased photocatalytic activity for CO2 reduction, with CH4 production rate reaching about 1.59 mmol h-1 g-1. This calcination induced photocatalytic enhancement should be related to the cystal structure transformation from hydrotalcite to mixed oxides containing high reactive oxygen species for more efficient CO2 reduction.

Non-covalent loading of ionic liquid-functionalized nanoparticles for bovine serum albumin: experiments and theoretical analysis.

Biomacromolecule-based nanomaterials have attracted much attention due to their excellent function in sensing, catalysis, medicine, biology and recognition. In this work, a silane-coupling ionic liquid, 1-(3-trimethoxysilylpropyl)-3-methylimidazolium chloride ([TMIM]Cl), was synthesized and applied to prepare ionic liquid-functionalized nanoparticles (SiO2@IL) using surface grafting technology. By employing multiple non-covalent interactions, including electrostatic interactions, hydrogen bonding and π-π stacking, the obtained functional nanoparticles were able to bind bovine serum albumin (BSA) with strong binding affinity, which has been illustrated through experiments and theoretical calculations. Moreover, the stability of SiO2@IL further demonstrated that it is promising in applications for biomacromolecule immobilization.

Analyzing the similarity of samples and genes by MG-PCC algorithm, t-SNE-SS and t-SNE-SG maps.

BACKGROUND: For analyzing these gene expression data sets under different samples, clustering and visualizing samples and genes are important methods. However, it is difficult to integrate clustering and visualizing techniques when the similarities of samples and genes are defined by PCC(Person correlation coefficient) measure. RESULTS: Here, for rare samples of gene expression data sets, we use MG-PCC (mini-groups that are defined by PCC) algorithm to divide them into mini-groups, and use t-SNE-SSP maps to display these mini-groups, where the idea of MG-PCC algorithm is that the nearest neighbors should be in the same mini-groups, t-SNE-SSP map is selected from a series of t-SNE(t-statistic Stochastic Neighbor Embedding) maps of standardized samples, and these t-SNE maps have different perplexity parameter. Moreover, for PCC clusters of mass genes, they are displayed by t-SNE-SGI map, where t-SNE-SGI map is selected from a series of t-SNE maps of standardized genes, and these t-SNE maps have different initialization dimensions. Here, t-SNE-SSP and t-SNE-SGI maps are selected by A-value, where A-value is modeled from areas of clustering projections, and t-SNE-SSP and t-SNE-SGI maps are such t-SNE map that has the smallest A-value. CONCLUSIONS: From the analysis of cancer gene expression data sets, we demonstrate that MG-PCC algorithm is able to put tumor and normal samples into their respective mini-groups, and t-SNE-SSP(or t-SNE-SGI) maps are able to display the relationships between mini-groups(or PCC clusters) clearly. Furthermore, t-SNE-SS(m)(or t-SNE-SG(n)) maps are able to construct independent tree diagrams of the nearest sample(or gene) neighbors, where each tree diagram is corresponding to a mini-group of samples(or genes).

New Coordination Complexes Based on the 2,6-bis[1-(Phenylimino)ethyl] Pyridine Ligand: Effective Catalysts for the Synthesis of Propylene Carbonates from Carbon Dioxide and Epoxides.

We aimed to develop new effective catalysts for the synthesis of propylene carbonate from propylene oxide and carbon dioxide. A kind of Mx+LClx coordination complex was fabricated based on the chelating tridentate ligand 2,6-bis[1-(phenylimino)ethyl] pyridine (L). The obtained products were characterized by elemental analysis, infrared spectroscopy, ultraviolet spectroscopy, thermogravimetric analysis, and single-crystal X-ray diffraction. It was found that the catalytic activity of the complexes with different metal ions, the same ligand differed and co-catalyst, where the order of greatest to least catalytic activity was 2 > 3 > 1. The catalytic system composed of complex 2 and DMAP proved to have the better catalytic performance. The yields for complex 2 systems was 86.7% under the reaction conditions of 100 °C, 2.5 MPa, and 4 h. The TOF was 1026 h-¹ under the reaction conditions of 200 °C, 2.5 MPa, and 1 h. We also explored the influence of time, pressure, temperature, and reaction substrate concentration on the catalytic reactions. A hypothetical catalytic reaction mechanism is proposed based on density functional theory (DFT) calculations and the catalytic reaction results.

Multiple-cumulative probabilities used to cluster and visualize transcriptomes.

Analysis of gene expression data by clustering and visualizing played a central role in obtaining biological knowledge. Here, we used Pearson's correlation coefficient of multiple-cumulative probabilities (PCC-MCP) of genes to define the similarity of gene expression behaviors. To answer the challenge of the high-dimensional MCPs, we used icc-cluster, a clustering algorithm that obtained solutions by iterating clustering centers, with PCC-MCP to group genes. We then used t-statistic stochastic neighbor embedding (t-SNE) of KC-data to generate optimal maps for clusters of MCP (t-SNE-MCP-O maps). From the analysis of several transcriptome data sets, we demonstrated clear advantages for using icc-cluster with PCC-MCP over commonly used clustering methods. t-SNE-MCP-O was also shown to give clearly projecting boundaries for clusters of PCC-MCP, which made the relationships between clusters easy to visualize and understand.

The biological knowledge discovery by PCCF measure and PCA-F projection.

In the process of biological knowledge discovery, PCA is commonly used to complement the clustering analysis, but PCA typically gives the poor visualizations for most gene expression data sets. Here, we propose a PCCF measure, and use PCA-F to display clusters of PCCF, where PCCF and PCA-F are modeled from the modified cumulative probabilities of genes. From the analysis of simulated and experimental data sets, we demonstrate that PCCF is more appropriate and reliable for analyzing gene expression data compared to other commonly used distances or similarity measures, and PCA-F is a good visualization technique for identifying clusters of PCCF, where we aim at such data sets that the expression values of genes are collected at different time points.

A novel mutation in the GJA3 (connexin46) gene is associated with autosomal dominant congenital nuclear cataract in a Chinese family.

PURPOSE: Congenital cataract is both a clinically and genetically heterogeneous lens disorder. The purpose of this study is to map and identify the mutation in an autosomal dominant congenital nuclear cataract in a Chinese family. METHODS: Patients were given physical examinations and their blood samples were collected for DNA extraction. Genotyping was performed by microsatellite markers and logarithm of odds (LOD) scores were calculated using the LINKAGE programs. Mutation detection was performed by direct sequencing. RESULTS: Linkage to the gap-junction protein α3 (GJA3) locus was verified. Sequencing of GJA3 revealed a G>A transition at nucleotide position c.139, which causes an Asn substitution for the conservative Asp at codon 47 (P.D47N).This mutation is identified in all affected individuals but is not found in 100 control chromosomes. CONCLUSIONS: Our results identify that the mutation (D47N) in GJA3 is responsible for this Chinese pedigree. It is further identified that GJA3 is responsible for congenital cataract. In our study, the novel mutation broadens the spectrum of GJA3 mutations.

[Spectra analyses of chitosans degraded by hydrogen peroxide under optimal conditions].

Chitosans with different average molecular weight (1,500-156 kDa) were prepared under optimal conditions based on our previous research by the depolymerization of initial chitosan using hydrogen peroxide, with maintaining the native structure of natural chitosan as principal consideration. Nitrogen and Carbon components of initial chitosan and degraded products were analyzed by BUCHI fully automatic nitrogen determination system and Liquid total organic carbon (TOC) analyzer respectively. Fourier transform infrared (FTIR), 13C nuclear magnetic resonance (13C NMR), X-ray diffraction and circular dichroism (CD) analyses were used to characterize the structure properties of samples. The results indicated that the maximum standard deviations of carbon content and nitrogen content and the degree of deacetylation (DD) of degraded products with the corresponding values of the initial chitosan are 2.4%, 2.3% and 6.9% respectively. Besides, the differentiations of the nitrogen content and DD value of the degraded product with the corresponding values of the initial chitosan are narrowed with the increase in the reaction time. FTIR spectra of resulting products are similar to that of initial chitosan in terms of peak number and position, indicating that there are no other functional groups formed during the degradation. 13C-NMR analyses of initial chitosan and degraded products revealed that the chemical structures of resulting chitosans are not changed to any noticeable extent. X-ray diffraction patterns of initial chitosan and degraded chitosans are alike and show characteristic peaks at 2theta = 10. 4 degrees and 19.8 degrees under the condition that the initial chitosan was disposed as degraded chitosans. Circular dichroism analyses showed that all the samples exhibit a broad negative band located at about 210 nm assigned to n --> pi* electronic transition of the --NH--CO-- chromophore on a glycosidic ring in acidic media, which demonstrated that degraded chitosans maintain their natural conformation in liquid state substantially. All these confirmed that the degraded chtiosans maintain their natural structure and conformation, and the breakage of beta-1,4-glucoside bonds in macromolecule is the basic process under optimal degradation conditions.