The reactivity of metallic nanotubes toward the catalysis of water dissociation, a key step in the water gas shift reaction (WGSR), was analyzed through density functional theory (DFT) calculations. Water dissociation was studied on surfaces of nanotubes based on copper, gold and platinum, and also on platinum doped copper and gold nanotubes. Gold and copper nanotubes present activities that are similar to those of their corresponding extended surfaces but, in the case of the Pt(5,3) nanotube, a significant improvement in the activity is found when compared with the extended surfaces. In fact, the calculations predict the water dissociation to be spontaneous on Pt(5,3) with a low activation energy barrier. The platinum doping of gold and copper nanotubes leads to contrasting effects, i.e., with a slight increase of activity found on gold and a slight decrease of activity in the case of copper. The consideration of a Bronsted-Evans-Polanyi (BEP) relationship to estimate the activation energy barriers for the O-H bond break leads to a satisfactory agreement between estimated and explicitly calculated values which suggests the validity of the BEP relationship for qualitative predictions of the activities of metal nanotubes towards the water dissociation reaction.

Background: Satisfaction is an important outcome variable in surgical success. The purpose of this study is to evaluate predictors of satisfaction in women submitted to silicone textured breast implant surgery. Methods: A retrospective evaluation of women receiving textured silicone breast implants was performed. Patients were divided in four groups: cosmetic cohort (n = 104), reconstructive cohort (n = 120), general population control cohort (n = 120) and aesthetic control cohort (n = 54). Data were collected based on information retrieved from patient records, a planned consultation and a self-administered structured questionnaire. Results: Patient satisfaction was influenced by preoperative information (p = .007), cohort (p <. 001), and occurrence of postoperative complications (p <. 001). The degree of satisfaction was also related with drug intake habits: women using psychotropic drugs were 3-fold more likely to report poor satisfaction than those that never used these drugs (p <. 001). Conclusion: The purpose of the surgery, preoperative information and the occurrence of postoperative complications have an impact on the degree of satisfaction of women submitted to silicone breast implant surgery. Women using psychotropic drugs are more likely to report poor satisfaction.

Nanoparticles (NPs) are part of our daily life, having a wide range of applications in engineering, physics, chemistry, and biomedicine. However, there are serious concerns regarding the harmful effects that NPs can cause to the different biological systems and their ecosystems. Toxicity testing is an essential step for assessing the potential risks of the NPs, but the experimental assays are often very expensive and usually too slow to flag the number of NPs that may cause adverse effects. In silico models centered on quantitative structure-activity/toxicity relationships (QSAR/QSTR) are alternative tools that have become valuable supports to risk assessment, rationalizing the search for safer NPs. In this work, we develop a unified QSTR-perturbation model based on artificial neural networks, aimed at simultaneously predicting general toxicity profiles of NPs under diverse experimental conditions. The model is derived from 54,371NP-NP pair cases generated by applying the perturbation theory to a set of 260 unique NPs, and showed an accuracy higher than 97% in both training and validation sets. Physicochemical interpretation of the different descriptors in the model are additionally provided. The QSTR-perturbation model is then employed to predict the toxic effects of several NPs not included in the original dataset. The theoretical results obtained for this independent set are strongly consistent with the experimental evidence found in the literature, suggesting that the present QSTR-perturbation model can be viewed as a promising and reliable computational tool for probing the toxicity of NPs.

Nanotechnology is a newly emerging field, posing substantial impacts on society, economy, and the environment. In recent years, the development of nanotechnology has led to the design and large-scale production of many new materials and devices with a vast range of applications. However, along with the benefits, the use of nanomaterials raises many questions and generates concerns due to the possible health-risks and environmental impacts. This chapter provides an overview of the Quantitative Structure-Activity Relationships (QSAR) studies performed so far towards predicting nanoparticles' environmental toxicity. Recent progresses on the application of these modeling studies are additionally pointed out. Special emphasis is given to the setup of a QSAR perturbation-based model for the assessment of ecotoxic effects of nanoparticles in diverse conditions. Finally, ongoing challenges that may lead to new and exciting directions for QSAR modeling are discussed.

In the present study, different in vitro and electrochemical protocols were employed to determine the mitoprotective properties of carbon nanotubes family (pristine-CNT, oxidized-CNT) based on free radical scavenging ability against the most aggressive reactive oxygen species (ROS) as hydroxyl radical (·OH) formed by Fenton-Haber-Weiss reaction, which was experimentally induced on isolated rat-liver mitochondria through Fe2+ ions overload. The results suggest that the mitochondrial Fenton-inhibition response involves a significant reduction of (·OH) concentration linked to iron-complexing ability of CNT-family, following the order: carboxylated-CNT &gt; pristine-CNT ∼ hydroxylated-CNT, without affecting the electrochemical mitochondrial membrane potential in Fe2+-overloaded mitochondria. Besides, a new in silico dose-response QSPR-model was applied suggesting reliability for the CNT-dose-effect series predictions towards the mitochondrial Fenton ROS-inhibition with excellent linear behavior on the training set (R2 = 0.901; R2(adj.) = 0.901; Q2(LOO-CV) = 0.901) and test set (Q2F1 = 0.9008; Q2F2 = 0.9008; Q2F3 = 0.9009; MAE = 21.213) for internal and external validation respectively, with p &lt; 0.05 for all regression coefficient for &gt; 70,000 data points. Lastly, these experimental and theoretical evidences open a gate to the rational design of novel carbon nanomaterials toward mitochondrial nanomedicine based redox-targeting as an alternative of treatment of several chronic diseases where pathological Fenton-reaction mechanisms have been directly involved. © 2017 Elsevier Ltd

Estrogens play a crucial role in the growth, development, and homeostasis of various target tissues, their biological effects being mediated by the estrogen receptor (ER). In order to get a better understanding of the structural features of the modulators associated with the binding to ER, this paper provides an overview of the Quantitative Structure-Activity (QSAR) studies performed so far for estimating or predicting the activity of different ligands towards its two known subtypes (ER alpha and ER beta). Recent progresses in the application of these modeling studies are additionally pointed out. Finally, ongoing challenges that may lead to new and exciting directions for QSAR modeling studies in this field are discussed.

The dendrimer polyamidoamine (PAMAM) has been widely applied in environmental applications as adsorbents for wastewater treatment. In this work, molecular dynamics simulations are conducted to understand the effect of dendrimer grafted graphene and graphene oxide on the structural and dynamical properties of the Pb2+ ion. The adsorption capacity of the metal ion is improved significantly, over 60%, using carboxyl terminal groups of a dendrimer molecule grafted on a graphene oxide surface. We examine the self-diffusion coefficient and residence time of Pb2+ ion near graphene and graphene oxide surfaces grafted with PAMAM dendrimers using terminal groups, -COO- and -OH. Further, the potential of mean force is analyzed to understand the role of different surface groups in enhancing the adsorption of the metal ion.

The increasing miniaturization of devices creates the need for adequate power sources and direct methanol fuel cells (DMFC) are a strong option in the various possibilities under current development. DMFC catalysts are mostly based on platinum, for its outperformance in three key areas (activity, selectivity and stability) within methanol oxidation framework. However, platinum poisoning with products of methanol oxidation led to the use of alloys. Ruthenium-platinum alloys are preferred catalysts active phases for methanol oxidation from an industrial point of view and, indeed, ruthenium itself is a viable catalyst for this reaction. In addition, the route of methanol decomposition is crucial in the goal of producing H-2 from water reaction with methanol. However, the reaction pathway remains elusive and new approaches, namely in computational methods, have been ensued to determine it. This article reviews the various recent theoretical approaches for determining the pathway of methanol decomposition, and systematizes their validation with experimental data, within methodological context.