Early and Delayed Impact of Nanosilver on the Glutamatergic NMDA Receptor Complex in Immature Rat Brain

Silver nanoparticles (AgNPs) are the one of the most extensively used nanomaterials. The strong antimicrobial properties of AgNPs have led to their use in a wide range of medical and consumer products. Although the neurotoxicity of AgNPs has been confirmed, the molecular mechanisms have not been extensively studied, particularly in immature organisms. Based on information gained from previous in vitro studies, in the present work, we examine whether ionotropic NMDA glutamate receptors contribute to AgNP-induced neurotoxicity in an animal model of exposure. In brains of immature rats subjected to a low dose of AgNPs, we identified ultrastructural and molecular alterations in the postsynaptic region of synapses where NMDA receptors are localized as a multiprotein complex. We revealed decreased expression of several NMDA receptor complex-related proteins, such as GluN1 and GluN2B subunits, scaffolding proteins PSD95 and SynGAP, as well as neuronal nitric oxide synthase (nNOS). Elucidating the changes in NMDA receptor-mediated molecular mechanisms induced by AgNPs, we also identified downregulation of the GluN2B-PSD95-nNOS-cGMP signaling pathway which maintains LTP/LTD processes underlying learning and memory formation during development. This observation is accompanied by decreased density of NMDA receptors, as assessed by a radioligand binding assay. The observed effects are reversible over the post-exposure time. This investigation reveals that NMDA receptors in immature rats are a target of AgNPs, thereby indicating the potential health hazard for children and infants resulting from the extensive use of products containing AgNPs.     

AUTOMAT[R]IX: learning simple matrix pipelines

Machine Learning - Matrices are a very common way of representing and working with data in data science and artificial intelligence. Writing a small snippet of code to make a simple matrix...     

The effects of laser patterning 10CeTZP-Al2O3 nanocomposite disc surfaces: Osseous differentiation and cellular arrangement in vitro

Customized square grid arrangements of different groove depths (1.0, 1.5 and 3.0?µm) and separations (10 and 30?µm) were successfully laser patterned, using a nanosecond pulsed fibre laser, on the surface of 10?mol% ceria-stabilized zirconia and alumina (10CeTZP-Al₂O₃) nanocomposite discs (diameter: 10?mm; thickness: 1.5?mm). The patterned surfaces and the in vitro biological response of osteoblasts (SAOS-2) towards them were thoroughly analysed. In terms of composition, the laser treatment was found to cause superficial monoclinic-tetragonal zirconia phase transformation and alumina evaporation. In vitro, the most effective grid configuration for osseous differentiation was found to be 1.5?µm groove depth and 10?µm groove separation, and confocal microscopy revealed that the cells show a tendency to be sorted as groove depth increases. It is thought that custom-made patterns could be produced to guide cell attachment in vivo, which could favour implant integration and reduce healing time.     

Cationic curing of diglycidyl ether of bisphenol A and 2,2,5,5‐tetramethyl‐4,6‐dioxo‐1,3‐dioxane and degradation of the thermosets obtained

Ytterbium and lanthanum triflates were used as cationic initiators to cure mixtures of diglycidyl ether of bisphenol A and 2,2,5,5‐tetramethyl‐4,6‐dioxo‐1,3‐dioxane in several proportions. The evolution of the epoxy and lactone during curing and the linear ester groups in the final materials were evaluated with Fourier transform infrared in the attenuated total reflection mode. The shrinkage after curing and the thermal degradability of the materials with variations in the comonomer ratios and initiator used were evaluated and related to the chemical structure of the final network. The expandable character of 2,2,5,5‐tetramethyl‐4,6‐dioxo‐1,3‐dioxane was confirmed. The obtained materials were more degradable than conventional epoxy resins because of the tertiary ester groups incorporated into the network by copolymerization. The kinetic parameters of the curing and degradation processes were calculated with differential scanning calorimetry and thermogravimetric analysis, respectively, with isoconversional procedures applied in both cases. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

A multiagent player system composed by expert agents in specific game stages operating in high performance environment

This paper proposes a new approach for the non-supervised learning process of multiagent player systems operating in a high performance environment, being that the cooperative agents are trained so as to be expert in specific stages of a game. This proposal is implemented by means of the Checkers automatic player denominated D-MA-Draughts, which is composed of 26 agents. The first is specialized in initial and intermediary game stages, whereas the remaining are specialists in endgame stages (defined by board-games containing, at most, 12 pieces). Each of these agents consists of a Multilayer Neural Network, trained without human supervision through Temporal Difference Methods. The best move is determined by the distributed search algorithm known as Young Brothers Wait Concept. Each endgame agent is able to choose a move from a determined profile of endgame board. These profiles are defined by a clustering process performed by a Kohonen-SOM network from a database containing endgame boards retrieved from real matches. Once trained, the D-MA-Draughts agents can actuate in a match according to two distinct game dynamics. In fact, the D-MA-Draughts architecture corresponds to an extension of two preliminary versions: MP-Draughts, which is a multiagent system with a serial search algorithm, and D-VisionDraughts, which is a single agent with a distributed search algorithm. The D-MA-Draughts gains are estimated through several tournaments against these preliminary versions. The results show that D-MA-Draughts improves upon its predecessors by significantly reducing training time and the endgame loops, thus beating them in several tournaments.     

Hydrodynamic effects on the performance of an electrochemical reactor for destruction of copper cyanide—Part 1: in situ formation of the electrocatalytic film

An electrochemical reactor with stainless-steel electrodes was used for cyanide destruction and copper electrodeposition from dilute wastewater. With mechanical stirring, pumping or gas sparging, in situ deposition of a Cu oxyhydroxide film occurred on the anode at potentials vs. AgCl/Ag and had electrocatalytic properties for oxidation of cyanides. The Cu^II/Cu^I ratio in the electrocatalytic film was found to vary with the hydrodynamic conditions. The minimum mechanical energy dissipation, ranging from 1.5 to , necessary to create sufficient turbulence for film formation, was of a similar order of magnitude for all three means of transport enhancement. However, shear rates and shear stresses at the anode resulted in shearing of the film from the stainless-steel support.     

Fractional convolution quadrature based on generalized Adams methods

In this paper we present a product quadrature rule for Volterra integral equations with weakly singular kernels based on the generalized Adams methods. The formulas represent numerical solvers for fractional differential equations, which inherit the linear stability properties already known for the integer order case. The numerical experiments confirm the valuable properties of this approach.     

Effect of melt annealing on the phase structure and rheological behavior of propylene–ethylene copolymers

The morphological and rheological properties of a commercial propylene‐ethylene copolymer (PEC) and a series of blends with different concentrations of poly (ethylene‐co‐propylene) are investigated. The blends are prepared mixing PEC with fractions obtained from it by solvent extraction. The phase structure of samples exposed to different thermal and mechanical histories was analyzed using scanning electron microscopy. The linear viscoelastic properties of the molten polymers were measured using different test sequences that include dynamic frequency and time sweeps. The phase structure of most blends changes dramatically with time when the polymers are kept in the molten state due to the coalescence of the domains. For example, the initial morphology of PEC which presents domains of ～1 μm diameter changes to regions of more than 10 μm of average diameter after 90 min at 178°C at rest. Coincidentally, the dynamic moduli of the blends change during annealing reaching values that depend on the mechanical history. For example, the elastic modulus of PEC increases ～32% during a dynamic time sweep of 45 min using a frequency of 0.1 s^?1, while it decreases ～18% when a frequency of 1 s^?1 is applied. Moreover, the modulus measured at 0.1 s^?1 of samples annealed at rest during 45 min is ～58% larger than that of the fresh material. POLYM. ENG. SCI., 47:912–921, 2007. © 2007 Society of Plastics Engineers     

Change point detection in time series data with random forests

A large class of monitoring problems can be cast as the detection of a change in the parameters of a static or dynamic system, based on the effects of these changes on one or more observed variables. In this paper, the use of random forest models to detect change points in dynamic systems is considered. The approach is based on the embedding of multivariate time series data associated with normal process conditions, followed by the extraction of features from the resulting lagged trajectory matrix. The features are extracted by recasting the data into a binary classification problem, which can be solved with a random forest model. A proximity matrix can be calculated from the model and from this matrix features can be extracted that represent the trajectory of the system in phase space. The results of the study suggest that the random forest approach may afford distinct advantages over a previously proposed linear equivalent, particularly when complex nonlinear systems need to be monitored.