Effect of Ag Adatoms on High-Coverage Alkanethiolate Adsorption on Au(111)

Alkanethiol adsorption on Ag-adatom-modified Au(111) surfaces is studied by means of electrochemical techniques combined with Auger electron spectroscopy and periodic density functional (DF) calculations. The bimetallic surfaces are prepared by Ag underpotential deposition, and only the alkanethiolate high-coverage regime is considered. Alkanethiolate electrodesorption from Ag-modified Au(111) surfaces requires potentials shifted 0.3 eV in the negative direction with respect to the value corresponding to desorption from Au(111) surfaces. In agreement with this experimental result, DF calculations show that alkanethiolates prefer to be laterally adsorbed to Ag adatoms, the interaction energy being 0.3 eV larger than that corresponding to the same thiolate on Au(111). Therefore, it is concluded that alkanethiolates adsorbed on Au are likely to be observed only when the Ag adatom surface density is small enough or all Ag sites are occupied. The preference for alkanethiolate adsorption on adatoms is also found for a model surface containing Au adatoms on Au-(111). This indicates that no significant differences in electrodesorption potentials should be expected between Ag-adatom- and Au-adatom-rich surfaces. These findings and the analysis of experimental results strongly suggest that, under experimental conditions, the Au(111) surface does not exhibit a significant amount of Au adatoms, thus casting reasonable doubts on the adatom reconstruction models proposed for thiolates on Au-(111).Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

Computational classifiers for predicting the short-term course of Multiple sclerosis

The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). METHODS: We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. RESULTS: We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. CONCLUSIONS: The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability

Megalin/LRP2 Expression Is Induced by Peroxisome Proliferator-Activated Receptor -Alpha and -Gamma: Implications for PPARs' Roles in Renal Function

BACKGROUND: Megalin is a large endocytic receptor with relevant functions during development and adult life. It is expressed at the apical surface of several epithelial cell types, including proximal tubule cells (PTCs) in the kidney, where it internalizes apolipoproteins, vitamins and hormones with their corresponding carrier proteins and signaling molecules. Despite the important physiological roles of megalin little is known about the regulation of its expression. By analyzing the human megalin promoter, we found three response elements for the peroxisomal proliferator-activated receptor (PPAR). The objective of this study was to test whether megalin expression is regulated by the PPARs. METHODOLOGY/PRINCIPAL FINDINGS: Treatment of epithelial cell lines with PPARα or PPARγ ligands increased megalin mRNA and protein expression. The stimulation of megalin mRNA expression was blocked by the addition of specific PPARα or PPARγ antagonists. Furthermore, PPAR bound to three PPAR response elements located in the megalin promoter, as shown by EMSA, and PPARα and its agonist activated a luciferase construct containing a portion of the megalin promoter and the first response element. Accordingly, the activation of PPARα and PPARγ enhanced megalin expression in mouse kidney. As previously observed, high concentrations of bovine serum albumin (BSA) decreased megalin in PTCs in vitro; however, PTCs pretreated with PPARα and PPARγ agonists avoided this BSA-mediated reduction of megalin expression. Finally, we found that megalin expression was significantly inhibited in the PTCs of rats that were injected with BSA to induce tubulointerstitial damage and proteinuria. Treatment of these rats with PPARγ agonists counteracted the reduction in megalin expression and the proteinuria induced by BSA. CONCLUSIONS: PPARα/γ and their agonists positively control megalin expression. This regulation could have an important impact on several megalin-mediated physiological processes and on pathophysiologies such as chronic kidney disease associated with diabetes and hypertension, in which megalin expression is impaired

A giant exoplanet orbiting a very-low-mass star challenges planet formation models

Surveys have shown that super-Earth and Neptune-mass exoplanets are more frequent than gas giants around low-mass stars, as predicted by the core accretion theory of planet formation. We report the discovery of a giant planet around the very-low-mass star GJ 3512, as determined by optical and near-infrared radial-velocity observations. The planet has a minimum mass of 0.46 Jupiter masses, very high for such a small host star, and an eccentric 204-day orbit. Dynamical models show that the high eccentricity is most likely due to planet-planet interactions. We use simulations to demonstrate that the GJ 3512 planetary system challenges generally accepted formation theories, and that it puts constraints on the planet accretion and migration rates. Disk instabilities may be more efficient in forming planets than previously thought

CARMENES: high-resolution spectra and precise radial velocities in the red and infrared

SPIE Astronomical Telescopes + Instrumentation (2018, Austin, Texas, United States

Chemical Defect-Driven Response on Graphene-Based Chemiresistors for Sub-ppm Ammonia Detection

Gas sensors are essential in several fields and, in general, features such as high sensitivity, quick response, and fast recovery are required, along with low power consumption and low cost. Graphene is considered a promising material for gas sensing applications, its functionalization often being a requisite. In the present study, we developed competitive and promising gas sensors for ammonia detection. Interestingly, we present an easy and efficient method to functionalize graphene by using diazonium chemistry with different functional groups. Moreover, we prove the superior sensing capability of our covalently modified graphene layers. These experimental data have been consistently interpreted by theoretical calculations, which reveal a defect-driven sensor's response to ammonia. These results open the possibility of a comprehensive design and use of these graphene-based sensors in real applications