Thermodynamic characterization of the prevailing molecular interactions in mixed floating monolayers of phospholipids and usnic acid

The investigation of the characteristics of mixed floating monolayers of phospholipids and usnic acid (UA), an active metabolite from lichens, can provide valuable information on how to prepare stable liposomes that could serve as carriers of UA for therapeutic proposes. The present paper is concerned with the thermodynamic analysis of the behavior of Langmuir monolayers formed by mixing different phospholipids (dibehenoylphosphatidylcholine, DBPC, dipalmitoylphosphatidylcholine, DPPC, and dioleoylphosphatidylcholine, DOPC) and UA at varied molar fractions. Relevant thermodynamic parameters such as excess areas, excess free energies and free energy of mixing were derived from the surface pressure data obtained from compression measurements performed in a Langmuir trough. For the largest lateral pressure examined (25 mN/m), negative values of the excess free energy were found only for the DOPC/UA monolayer, which should be the most stable of them. Based on the calculated values of the free energy of mixing, we note that the DBPC/UA and DPPC/UA systems present the best mixed character at low pressures and when the molar fraction of the UA is 0.5; at that relative concentration and at low values of the external pressure, the UA molecules can better mix and interact with the phospholipid molecules. The compression isotherms for mixed monolayers show no visible transitions, exhibiting a more organized phase that corresponds to a negative free energy of mixing. We have established that the most stable monolayers were those corresponding to DOPC/UA mixtures with a UA molar fraction of 0.75.     

Spectrofotometric determination of copper in sugar cane spirit using biquinoline in the presence of ethanol and Triton X-100

The present paper proposes a method for molecular spectrophotometric determination of copper in sugar cane spirits. The copper(I) reacts with biquinoline forming a pink complex with maximum absorption at 545 nm. The reaction occurs in the presence of hydroxylamine, ethanol and Triton X-100 tensioative. Determination of copper is possible in a linear range 0.2-20.0 mgL(-1) with a detection limit 0.05 mgL(-1). The great advantages of the proposed methodology are the elimination of liquid-liquid extraction step and the use of toxic organics solvents, like dioxane, to dissolve the reagent.     

Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.     

The modified electronic mass approach for the adiabatic corrections in H2

A theory of the modified (distance dependent) electronic mass effect for two-electron diatomic molecules is presented. The modified electronic mass correction is compared with the diagonal Born-Oppenheimer correction to the potential energy curves of H₂, suggesting that the adiabatic correction is almost exactly accounted for by this effect.     

Ureasil–polyether hybrid blend with tuneable hydrophilic/hydrophobic features based on U-PEO1900 and U-PPO400 mixtures

Urea-cross-linked polyether-siloxane hybrid blends with tuneable hydrophilic/hydrophobic features were prepared from a mixture of poly(ethylene oxide) (PEO1900) and poly(propylene oxide) (PPO400), hybridized by end-chain functionalization with (3-isocyanatopropyl)triethoxysilane. The aim of this study was to demonstrate that the combination of the different polyether phases produces materials with hydrophilic and hydrophobic properties. An anti-fog coating and a transparent monolithic swellable hydrogel were produced from the PEO1900 hybrid. Swellability and drug release profiles could be easily tuned by varying the ureasil–PEO/ureasil–PPO ratio in the hybrid matrix. Differential scanning calorimetry (DSC) and small angle X-ray scattering (SAXS) analyses indicated that the nanostructure of the hybrid blends could be described by the existence of a biphasic mixture of PEO1900-rich and PPO400-rich phases, with a fraction of the lamellar domains being derived from the PEO1900 crystallinity. A correlation between the nanoscopic features and the kinetics of the swelling mechanism is proposed, based on the results of in situ SAXS analyses. In vitro monitoring using UV–Vis spectroscopy indicated that the kinetics of drug release from the PEO1900:PPO400 hybrid blends could be controlled by varying the proportions of the hydrophilic (PEO1900) and hydrophobic (PPO400) hybrids. The response to pH change and to application of a magnetic field to the PEO1900-magnetite nanocomposite indicated that the production of stimuli-responsive delivery devices based on ureasil–PE should be feasible in the near future.     

Hyperbolic 0–1 programming and query optimization in information retrieval

Unconstrained hyperbolic 0–1 programming can be solved in linear time when the numerator and the denominator are linear and the latter is always positive. It is NP-hard, and finding an approximate solution with a value equal to a positive multiple of the optimal one is also NP-hard, if this last hypothesis does not hold. Determining the optimal logical form of a query in information retrieval, given the attributes to be used, can be expressed as a parametric hyperbolic 0–1 program and solved in O(n logn) time, wheren is the number of elementary logical conjunctions of the attributes. This allows to characterize the optimal queries for the Van Rijsbergen synthetic criterion.This research was done in part during a visit of the first author to the Pontifical Catholic University of Rio de Janeiro in July and August 1987, sponsored by CNPq. It was also supported in part by grants 0271 and 0066 of the AFOSR to Rutgers University. The second author was with Centro de Análise de Sistemas Navais, Rio de Janeiro.     

Multilayer brain network combined with deep convolutional neural network for detecting major depressive disorder

As a global and grievous mental disease, major depressive disorder (MDD) has received much attention. Accurate detection of MDD via physiological signals represents an urgent research topic. Here, a frequency-dependent multilayer brain network, combined with deep convolutional neural network (CNN), is developed to detect the MDD. Multivariate pseudo Wigner distribution is firstly introduced to extract the time-frequency characteristics from the multi-channel EEG signals. Then multilayer brain network is constructed, with each layer corresponding to a specific frequency band. Such multilayer framework is in line with the nature of the workings of the brain, and can effectively characterize the brain state. Further, a multilayer deep CNN architecture is designed to study the brain network topology features, which is finally used to accurately detect MDD. The experimental results on a publicly available MDD dataset show that the proposed approach is able to detect MDD with state-of-the-art accuracy of 97.27%. Our approach, combining multilayer brain network and deep CNN, enriches the multivariate time series analysis theory and helps to better characterize and recognize the complex brain states.