Crystal and Molecular Structures of (η4-Cyclohexa-1,3-Diene) (2-Tert-Butyl-1,1,4,4-Tetrafluoro-1,4-Disilabutene) Metal Carbonyls. M?Fe,W

Molecular structures of the two title compounds were investigated to reveal the relationship between the structure of the reaction intermediates and the reaction pathways in the transition metal-mediated cycloaddition reaction between tetrafluorodisilacyclobutene and conjugated dienes. The structures were determined by X-ray diffraction. Both cyrstals are orthorhombic. Compound I. C₁₄H₁₈O₂Si₂F₄Fe. is of space group P2₁2₁2₁ with Z=4; a=6.862(7) Å. b=10.9560(10) Å. c=23.597(25) Å. and Dc=1.562 gcm^?1. Compound II, C₁₅H₁₈O₃Si₂F₄W, is of space group Pbca with Z=8; a=16.999(8) Å, b=15.948(6), c=14.045(7) Å, and Dc=1.962 gcm^?1. Both structures were solved by heavy-atom methods and refined by full-matrix least-squares using anisotropic temperature factors for all non-hydrogen atoms to R values of 0.092 for 1544 observed reflections and 0.078 for 2751 observed reflections, respectively, for compound I and compound II. The butadiene segment of the cyclohexadiene ligand is essentially planar in compound I while it is twisted with a torsional angle of 22° (2) in compound II. The five-membered disilametallacycle ring is planar in compound II while ii is in an envelope comformation in compound I. The coordination geometry of the iron atom may be considered as a distorted tetragonal-pyramidal with the diene unit occupying the apical site, That of tungsten is a distorted seven-coordinated pentagonal-bipyramidal with the two axial carbonyl groups displaced toward the disilabutene ligand. The disilabutene of compound I lies almost parallel and cis to the plane of the butadiene segment while that of compound II orients almost perpendicular to the diene group. The differences in the structural features of the two complexes explain clearly their product patterns and the reactions are apparently stereo-controlled.     

Supramolecular Polymerization of a Pyrene-Substituted Diamide and Its Ensemble of Kinetically Trapped Configurations

The prevalence of kinetically accessible states in supramolecular polymerization pathways has been exploited to control the growth of the polymer and thereby to obtain niche morphologies. Yet, these pathways themselves are not easily amenable for experimental delineation but could potentially be understood through molecular dynamics (MD) simulations. Herein, we report an extensive investigation of the self-assembly of pyrene-substituted diamide (PDA) monomers in solution, conducted using atomistic MD simulations and advanced sampling methods. We characterize such kinetic and thermodynamic states as well as the transition pathways and free energy barriers between them. PDA forms a dimeric segment with the N- to C-termini vectors of the diamide moieties arranged either in parallel or anti-parallel fashion. This characteristic, combined with the molecule's torsional flexibility and pyrene–solvent interactions, presents an ensemble of molecular configurations contributing to the kinetic state in the polymerization pathway. While this ensemble primarily comprises short oligomers containing a mix of anti-parallel and parallel dimeric segments, the thermodynamic state of the assembly is a right-handed polymer featuring parallel ones only. Our work thus offers an approach by which the landscape of any specific supramolecular polymerization can be deconstructed.     

Biomedical application and hidden toxicity of Zinc oxide nanoparticles

Zinc oxide nanoparticles (ZnO NPs) represent a novel type of metal oxide nanoparticles enabling a new horizon for biomedical applications spanning from diagnosis to treatment. ZnO NPs are extensively used in commercial products such as sunscreens and daily-care products. Apart from that, ZnO NPs are used in food packaging and ointments and as an antimicrobial and antifungal agent. They are extensively used for many biomedical applications noticeably in pharmaceutics and theranostics. Its exceptional optical, electrical, and physiochemical properties, notably its incredible surface chemistry, make ZnO NPs a reliable option for bioimaging, biosensors, antimicrobial action, and drug and gene delivery. The present review covers findings and developments in ZnO NPs research in relation to its application and toxicity mechanism. A special emphasis has been given to the neurotoxic potential of the ZnO NPs and glial cell toxicity. Various factors contributing to the toxic potential of ZnO NPs and cell signaling pathways concerning its toxicity are also discussed. Available data point toward the risk of uncontrollable use of zinc nanoformulation. With increasing use, ZnO NPs pose a severe threat both to the ecosystem and human beings. In a nutshell, the review outlines the current state of the art of ZnO NPs.     

Gene function classification using NCI-60 cell line gene expression profiles

Gene expression patterns from NCI's panel of 60 cell lines were used to train a Neural Network model for classifying genes to pathways. The model assigns probabilities to each gene for each of the 21 modeled pathways assigned by the Kyoto Encyclopedia of Genes and Genomes. Cross-validation of the model showed that 10 of the 21 pathways exhibited good performance in statistical significance and accuracy. The model was designed to output gene probabilities that could be screened for higher probabilities resulting in higher confidence in classification though yielding fewer genes per pathway. The model was deployed on 5798 genes and our approach allowed us to ascertain the most relevant genes above an estimated background. Eight pathways were identified with both good cross-validation and significant numbers above background, TCA Cycle, Oxidative Phosphorylation, Porphyrin Biosynthesis, Ribosome, Polymerases, Proteasome, Cell Cycle, and Cell Adhesion. Gene Ontology (GO) annotation was used for additional validation of gene classification results. A total of 551 GO annotated genes and 468 unannotated genes were classified to the 8 pathways. The primary and secondary classifications of genes revealed known pathway relationships and provide the potential for discovering new pathway relationships.     

Gene Regulation Network Inference With Joint Sparse Gaussian Graphical Models

Revealing biological networks is one key objective in systems biology. With microarrays, researchers now routinely measure expression profiles at the genome level under various conditions, and such data may be used to statistically infer gene regulation networks. Gaussian graphical models (GGMs) have proven useful for this purpose by modeling the Markovian dependence among genes. However, a single GGM may not be adequate to describe the potentially differing networks across various conditions, and hence it is more natural to infer multiple GGMs from such data. In this article we propose a class of nonconvex penalty functions aiming at the estimation of multiple GGMs with a flexible joint sparsity constraint. We illustrate the property of our proposed nonconvex penalty functions by simulation study. We then apply the method to a gene expression dataset from the GenCord Project, and show that our method can identify prominent pathways across different conditions. Supplementary materials for this article are available online.     

Characterization of in Vitro Metabolism of Loganin by Human Intestinal Microflora Using Ultra-High Performance Liquid Chromatography–Quadrupole Time-of-Flight Mass Spectrometry

Human intestinal microbiota comprise a complex biological system with considerable metabolic activity. Various studies have focused on the bioconversion of flavonoids. However, in addition to flavonoids, bioactive components such as iridoids also exist in many natural and traditional Chinese medicines. Little is known about the interactions of the iridoids with bacteria. Loganin, one of the main effective iridoids in the valuable traditional Chinese herbal medicine Cornus officinalis, exhibits various pharmacological activities and biological effects. Human intestinal bacteria were isolated and the conversion capability of loganin was investigated. The metabolites were determined by ultra-high performance liquid chromatography–quadrupole time-of-flight mass spectrometry. Loganin was metabolized to hydrogenated and hydroxylated loganin sulfate, acetylated loganin, loganetin, methylated loganetin, hydrogenated, and hydroxylated loganetin. The metabolic routes and metabolites of loganin were reported for the first time. These metabolites may influence the biological activities of loganin in vivo. Thus, this study provides fundamental information about a traditional Chinese medicine.     

Probabilistic assessment of biodegradability based on metabolic pathways: CATABOL System

A novel mechanistic modeling approach has been developed that assesses chemical biodegradability in a quantitative manner. It is an expert system predicting biotransformation pathway working together with a probabilistic model that calculates probabilities of the individual transformations. The expert system contains a library of hierarchically ordered individual transformations and matching substructure engine. The hierarchy in the expert system was set according to the descending order of the individual transformation probabilities. The integrated principal catabolic steps are derived from set of metabolic pathways predicted for each chemical from the training set and encompass more than one real biodegradation step to improve the speed of predictions. In the current work, we modeled O 2 yield during OECD 302 C (MITI I) test. MITI-I database of 532 chemicals was used as a training set. To make biodegradability predictions, the model only needs structure of a chemical. The output is given as percentage of theoretical biological oxygen demand (BOD). The model allows for identifying potentially persistent catabolic intermediates and their molar amounts. The data in the training set agreed well with the calculated BODs ( r 2 =0.90) in the entire range i.e. a good fit was observed for readily, intermediate and difficult to degrade chemicals. After introducing 60% ThOD as a cut off value the model predicted correctly 98% ready biodegradable structures and 96% not ready biodegradable structures. Crossvalidation by four times leaving 25% of data resulted in Q 2 =0.88 between observed and predicted values. Presented approach and obtained results were used to develop computer software for biodegradability prediction CATABOL.     

Long-Range Cationic Disordering Induces two Distinct Degradation Pathways in Co-Free Ni-Rich Layered Cathodes

Ni-rich layered oxides are one of the most attractive cathode materials in high-energy-density lithium-ion batteries, their degradation mechanisms are still not completely elucidated. Herein, we report a strong dependence of degradation pathways on the long-range cationic disordering of Co-free Ni-rich Li_1−m(Ni_0.94Al_0.06)_1+mO₂ (NA). Interestingly, a disordered layered phase with lattice mismatch can be easily formed in the near-surface region of NA particles with very low cation disorder (NA-LCD, m≤0.06) over electrochemical cycling, while the layered structure is basically maintained in the core of particles forming a “core–shell” structure. Such surface reconstruction triggers a rapid capacity decay during the first 100 cycles between 2.7 and 4.3 V at 1 C or 3 C. On the contrary, the local lattice distortions are gradually accumulated throughout the whole NA particles with higher degrees of cation disorder (NA-HCD, 0.06≤m≤0.15) that lead to a slow capacity decay upon cycling.     

Regulating Degradation Pathways of Polymers by Radical-Triggered Luminescence

Understanding the radical behaviours during polymer degradation is beneficial to unveil and regulate the degradation pathways of polymers to achieve a sustainable polymer development. However, it is a long-standing challenge to study radical behaviours owing to the ultra-short lifetime of the transient radicals generated during the polymer degradation. In this contribution, we have proposed the radical-triggered luminescence to monitor the radical behaviours during polymer degradation without/with the addition of inorganic additives. It was disclosed that the pure polymers showed a single sigmoidal dynamic curve from peroxy radicals (ROO⋅) emissions, leading to the exponential proliferation for the degradation evolution. Alternatively, the degradation pathways with the addition of additives, layered double hydroxides (LDHs) with positively charged Al centers, could be modulated into a double sigmoidal dynamics, involving the main product of alkoxy radicals (RO⋅) with the activation energy of 40.2 kJ/mol and a small amount of ROO⋅ with 76.3 kJ/mol, respectively. Accordingly, the polymers with the additive-regulated pathways could exhibit prominently anti-degradation behaviours. This work is beneficial for the deep understanding of the radical mechanisms during polymer degradation, and for the rational design of anti-degradation polymers.