Measurement of an Excited Charmonium State and the Study of J/psi Polarization in p plus p Collisions at root s=200 GeV in PHENIX Experiment at RHIC

We report the J/psi -> e(+)e(-) and the psi` -> e(+)e(-) production cross sections in the PHENIX experiment at RHIC. The first measurements of the production cross sections of the psi` and the psi` over the J/psi, will contribute to the clarification of the theoretical understanding of the J/psi meson production. The inclusive J/psi polarization through the same decay channel is also presented, showing a trend of slightly longitudinal polarization for p(T) <5 GeV/c.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

New material for orthopedic implants: Electrochemical study of nickel free P558 stainless steel in minimum essential medium

Nickel, a component of stainless steels (SS) applied in orthopedic implants may cause allergic processes in human tissues P558 nickel free SS was studied to verify its viability as a substitute for stainless steel containing nickel Its performance is compared to ISO 5832-9 and F138 most used nowadays grades in implants fabrications, in minimum essential medium. MEM, at 37 degrees C. Potentiodynamic polarization curves, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and ""in vitro"" cytotoxicity were used as techniques. From the electrochemical point of view P558 SS is comparable to ISO 5832-9 SS in MEM It remains passivated until the transpassivation potential, above which generalized corrosion occurs F138 presents pitting corrosion at 370 mV/SCE. The cytotoxicity results showed that P558. ISO 5832-9 and F138 do not present cytotoxic character Therefore, these results suggest that P558 SS can be applied in orthopedic implants (C) 2010 Elsevier BV All rights reserved

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.