Glyconanoparticle–DNA Interactions: An Atomic Force Microscopy Study

Glyconanoparticles which present carbohydrate and amino groups motifs at their surface were produced. These particles were highly stable and soluble in aqueous solutions. The presence of the carbohydrate groups also allowed the inclusion of more strongly binding groups, without affecting solubility. The binding of a model DNA, plasmid by these nanoparticles was studied by atomic force microscopy, transmission electron microscopy, and gel electrophoresis. Significant differences between the nanoparticles based on their affinities for the DNA were found, with implications for their potential use as nonviral gene delivery agents.     

Glyconanoparticle-DNA interactions: an atomic force microscopy study.

Glyconanoparticles which present carbohydrate and amino groups motifs at their surface were produced. These particles were highly stable and soluble in aqueous solutions. The presence of the carbohydrate groups also allowed the inclusion of more strongly binding groups, without affecting solubility. The binding of a model DNA, plasmid by these nanoparticles was studied by atomic force microscopy, transmission electron microscopy, and gel electrophoresis. Significant differences between the nanoparticles based on their affinities for the DNA were found, with implications for their potential use as nonviral gene delivery agents.     

Control of peptide deformylase activity by metal cations

Previously, CT was considered insensitive in the evaluation of the acute ischemic stroke patient; however, more recently detection of early CT findings has proved to be of prognostic value in the evaluation of these patients. The use of CT coupled with early acute phase therapy of stroke such as thrombolytic therapy has been shown to improve outcome in the acute stroke patient.     

The GAUGAA Motif Is Responsible for the Binding between circSMARCA5 and SRSF1 and Related Downstream Effects on Glioblastoma Multiforme Cell Migration and Angiogenic Potential

Circular RNAs (circRNAs) are a large class of RNAs with regulatory functions within cells. We recently showed that circSMARCA5 is a tumor suppressor in glioblastoma multiforme (GBM) and acts as a decoy for Serine and Arginine Rich Splicing Factor 1 (SRSF1) through six predicted binding sites (BSs). Here we characterized RNA motifs functionally involved in the interaction between circSMARCA5 and SRSF1. Three different circSMARCA5 molecules (Mut1, Mut2, Mut3), each mutated in two predicted SRSF1 BSs at once, were obtained through PCR-based replacement of wild-type (WT) BS sequences and cloned in three independent pcDNA3 vectors. Mut1 significantly decreased its capability to interact with SRSF1 as compared to WT, based on the RNA immunoprecipitation assay. In silico analysis through the “Find Individual Motif Occurrences” (FIMO) algorithm showed GAUGAA as an experimentally validated SRSF1 binding motif significantly overrepresented within both predicted SRSF1 BSs mutated in Mut1 (q-value = 0.0011). U87MG and CAS-1, transfected with Mut1, significantly increased their migration with respect to controls transfected with WT, as revealed by the cell exclusion zone assay. Immortalized human brain microvascular endothelial cells (IM-HBMEC) exposed to conditioned medium (CM) harvested from U87MG and CAS-1 transfected with Mut1 significantly sprouted more than those treated with CM harvested from U87MG and CAS-1 transfected with WT, as shown by the tube formation assay. qRT-PCR showed that the intracellular pro- to anti-angiogenic Vascular Endothelial Growth Factor A (VEGFA) mRNA isoform ratio and the amount of total VEGFA mRNA secreted in CM significantly increased in Mut1-transfected CAS-1 as compared to controls transfected with WT. Our data suggest that GAUGAA is the RNA motif responsible for the interaction between circSMARCA5 and SRSF1 as well as for the circSMARCA5-mediated control of GBM cell migration and angiogenic potential.     

Synthesis,Pharmacological Evaluation,and Docking Studies of Novel Pyridazinone‐Based Cannabinoid Receptor Type 2 Ligands

In recent years, cannabinoid type 2 receptors (CB₂R) have emerged as promising therapeutic targets in a wide variety of diseases. Selective ligands of CB₂R are devoid of the psychoactive effects typically observed for CB₁R ligands. Based on our recent studies on a class of pyridazinone 4‐carboxamides, further structural modifications of the pyridazinone core were made to better investigate the structure–activity relationships for this promising scaffold with the aim to develop potent CB₂R ligands. In binding assays, two of the new synthesized compounds [6‐(3,4‐dichlorophenyl)‐2‐(4‐fluorobenzyl)‐cis‐N‐(4‐methylcyclohexyl)‐3‐oxo‐2,3‐dihydropyridazine‐4‐carboxamide ( 2 ) and 6‐(4‐chloro‐3‐methylphenyl)‐cis‐N‐(4‐methylcyclohexyl)‐3‐oxo‐2‐pentyl‐2,3‐dihydropyridazine‐4‐carboxamide ( 22 )] showed high CB₂R affinity, with K_i values of 2.1 and 1.6 nm , respectively. In addition, functional assays of these compounds and other new active related derivatives revealed their pharmacological profiles as CB₂R inverse agonists. Compound 22 displayed the highest CB₂R selectivity and potency, presenting a favorable in silico pharmacokinetic profile. Furthermore, a molecular modeling study revealed how 22 produces inverse agonism through blocking the movement of the toggle‐switch residue, W6.48.     

Three-dimensional h-adaptivity for the multigroup neutron diffusion equations

Adaptive mesh refinement (AMR) has been shown to allow solving partial differential equations to significantly higher accuracy at reduced numerical cost. This paper presents a state-of-the-art AMR algorithm applied to the multigroup neutron diffusion equation for reactor applications. In order to follow the physics closely, energy group-dependent meshes are employed. We present a novel algorithm for assembling the terms coupling shape functions from different meshes and show how it can be made efficient by deriving all meshes from a common coarse mesh by hierarchic refinement. Our methods are formulated using conforming finite elements of any order, for any number of energy groups. The spatial error distribution is assessed with a generalization of an error estimator originally derived for the Poisson equation.Our implementation of this algorithm is based on the widely used Open Source adaptive finite element library deal.II and is made available as part of this library's extensively documented tutorial. We illustrate our methods with results for 2-D and 3-D reactor simulations using 2 and 7 energy groups, and using conforming finite elements of polynomial degree up to 6.     

Changes of mitochondrial cytochrome c oxidase and FoF1 ATP synthase subunits in rat cerebral cortex during aging

The contents of subunits I, II/III, and IV of cytochrome c oxidase and of subunits alpha, beta and gamma of FoF1 ATP synthase in inner mitochondrial membrane proteins purified from cerebral cortex of rat at 2, 6, 12, 18, 24, and 26 months of age were analyzed by western blot. Age-related changes in the content of subunits, either of mitochondrial or nuclear origin, were observed. All the cytochrome c oxidase (COX) subunits examined showed an age-related increase from 2-month-old rats up to 24 months with a decrease at the oldest age (26 months). The same pattern of age-dependent changes was observed for gamma ATP synthase, while the alpha and beta subunits increased progressively up to 26 months.     

Environmental data processing by clustering methods for energy forecast and planning

This paper presents a statistical approach based on the k-means clustering technique to manage environmental sampled data to evaluate and to forecast of the energy deliverable by different renewable sources in a given site. In particular, wind speed and solar irradiance sampled data are studied in association to the energy capability of a wind generator and a photovoltaic (PV) plant, respectively. The proposed method allows the sub-sets of useful data, describing the energy capability of a site, to be extracted from a set of experimental observations belonging the considered site. The data collection is performed in Sicily, in the south of Italy, as case study. As far as the wind generation is concerned, a suitable generator, matching the wind profile of the studied sites, has been selected for the evaluation of the producible energy. With respect to the photovoltaic generation, the irradiance data have been taken from the acquisition system of an actual installation. It is demonstrated, in both cases, that the use of the k-means clustering method allows data that do not contribute to the produced energy to be grouped into a cluster, moreover it simplifies the problem of the energy assessment since it permits to obtain the desired information on energy capability by managing a reduced amount of experimental samples. In the studied cases, the proposed method permitted a reduction of the 50% of the data with a maximum discrepancy of 10% in energy estimation compared to the classical statistical approach. Therefore, the adopted k-means clustering technique represents an useful tool for an appropriate and less demanding energy forecast and planning in distributed generation systems.     

A simple Hessian-based 3D mesh adaptation technique with applications to the multigroup diffusion equations

A simple error estimation and mesh adaptation procedure is proposed for the multigroup multi-dimensional diffusion equations. The procedure estimates the values of the second-order derivatives of the current numerical solution to drive the mesh refinement. Different spatial meshes are obtained for each component of the multigroup flux in order to follow the physics appropriately. This requires the proper handling of the group coupling terms arising in the multigroup diffusion equations. Results are presented in 2D and 3D.     

Solution structure of nickel-peptide deformylase

In the accompanying paper, we report that zinc is unlikely to be the co-factor supporting peptide deformylase activity in vivo. In contrast, nickel binding promotes full enzyme activity. The three-dimensional structure of the resulting nickel-containing peptide deformylase (catalytic domain, residues 1 to 147) was solved by NMR using a 13C-15N-doubly labelled protein sample. A set of 2261 restraints could be collected, with an average of 15.4 per amino acid. The resolution, which shows a good definition for the position of most side-chains, is greatly improved compared to that previously reported for the zinc-containing, inactive form. A comparison of the two stuctures indicates however that both share the same 3D organization. This shows that the nature of the bound metal is the primary determinant of the hydrolytic activity of this enzyme. Site-directed mutagenesis enabled us to determine the conserved residues of PDF involved in the structure of the active site. In particular, a buried arginine appears to be critical for the positioning of Cys90, one of the metal ligands. Furthermore, the 3D structure of peptide deformylase was compared to thermolysin and metzincins. Although the structural folds are very different, they all display a common structural motif involving an alpha-helix and a three-stranded beta-sheet. These conserved structural elements build a common scaffold which includes the active site, suggesting a common hydrolytic mechanism for these proteases. Finally, an invariant glycine shared by both PDF and metzincins enables us to extend the conserved motif from HEXXH to HEXXHXXG.