Exploring the protein–protein interaction landscape in plants

Protein–protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.     

Molecular simulation of the preferential adsorption of CH4 and CO2 in middle-rank coal

The adsorption of the CO₂/CH₄ mixture in coal affects the CO₂-enhanced coalbed methane recovery project. To gain a better understanding of CH₄ and CO₂ interaction with middle-rank coal, we developed a molecular concept with support for the sorption of CH₄ and CO₂ on Ximing-8 coal (XM-8) (1.8% vitrinite reflectance). A XM-8 coal model was built by using molecular dynamic (MD) simulations. The molecular simulations were established by the Grand Canonical Monte Carlo and MD methods to study the effects of the temperature, pressure, and species bulk mole fraction on the pure component adsorption isotherms, isosteric heat and adsorption selectivity. It turns out that the CO₂ selectivity decreases as the pressure and its own bulk mole fraction increases, but it increases as temperature increases, and the selectivity values are not always greater than 1. The interactions between the small molecules and XM-8 were determined by using density functional theory. It was found that the interactions between the CO₂ and XM-8 surface is greater, particularly for the heteroatoms than CH₄. The adsorption selectivity and interaction were simultaneously used to reveal that the advantageously substituted range is high temperature, low pressure and a high content of heteroatoms.     

Epidemiological Panel Studies of Older Adults: New Frontiers in the Research on Human– Animal Interaction

ABSTRACT

This paper discusses epidemiological studies of older adults and human–animal interaction (HAI), and potential relevance to future research on HAI and animal-assisted interventions (AAI) in aging populations. Key issues in epidemiological work are discussed, including target populations, treatment/exposures, follow up, and endpoint measures as they relate to interacting with or owning companion animals. In outlining the limits in our current state of knowledge, we also make recommendations for the design and analysis of epidemiological studies to advance research on HAI and aging.     

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.     

Bayesian Semiparametric Frailty Selection in Multivariate Event Time Data

Biomedical studies often collect multivariate event time data from multiple clusters (either subjects or groups) within each of which event times for individuals are correlated and the correlation may vary in different classes. In such survival analyses, heterogeneity among clusters for shared and specific classes can be accommodated by incorporating parametric frailty terms into the model. In this article, we propose a Bayesian approach to relax the parametric distribution assumption for shared and specific‐class frailties by using a Dirichlet process prior while also allowing for the uncertainty of heterogeneity for different classes. Multiple cluster‐specific frailty selections rely on variable selection‐type mixture priors by applying mixtures of point masses at zero and inverse gamma distributions to the variance of log frailties. This selection allows frailties with zero variance to effectively drop out of the model. A reparameterization of log‐frailty terms is performed to reduce the potential bias of fixed effects due to variation of the random distribution and dependence among the parameters resulting in easy interpretation and faster Markov chain Monte Carlo convergence. Simulated data examples and an application to a lung cancer clinical trial are used for illustration.     

Monitoring clinical trials with multiple arms

In order to benefit from the substantial overhead expenses of a large group sequential clinical trial, the simultaneous investigation of several competing treatments becomes more popular. If at some interim analysis any treatment arm reveals itself to be inferior to any other treatment under investigation, this inferior arm may be or may even need to be dropped for ethical and/or economic reasons. Recently proposed methods for monitoring and analysis of group sequential clinical trials with multiple treatment arms are compared and discussed. The main focus of the article is on the application and extension of (adaptive) closed testing procedures in the group sequential setting that strongly control the familywise error rate. A numerical example is given for illustration.     

A novel microtubule-associated protein-2 expressed in oligodendrocytes in multiple sclerosis lesions

Elucidation of the mechanisms involved in the regeneration of oligodendrocytes and remyelination is a central issue in multiple sclerosis (MS) research. We recently identified a novel alternatively spliced, developmentally regulated oligodendrocyte-specific protein designated microtubule-associated protein-2+13 [microtubule-associated protein-2 expressing exon 13 (MAP-2+13)]. MAP-2+13 is expressed in human fetal oligodendrocytes during process extension and myelination but is minimally expressed in normal mature CNS. To test the hypothesis that MAP-2+13 is reexpressed in regenerating oligodendrocytes in MS lesions, we examined the brains of MS patients for the expression of this protein. By immunocytochemistry using a series of monoclonal antibodies specific for MAP-2+13, we determined that MAP-2+13 expression was up-regulated in all 31 lesions from 10 different MS brains. MAP-2+13 was expressed in regenerating oligodendrocytes associated with demyelinated lesions, with the highest counts found in regions of extensive remyelination. By electron microscopy, MAP-2+13 was localized to oligodendrocytes engaged in remyelination, evident by their process extension and association with thinly myelinated (remyelinated) and demyelinated axons. These results suggest a hitherto unsuspected role for this microtubule-associated protein in oligodendrocyte function during development and myelin repair.