Hiv-1 Specific Reverse Transcriptase Inhibitors: why are Tsao-Nucleosides so Unique?

1. INTRODUCTION

AIDS will still be one of the most important challenges for the Scientific Community in the approaching new century. Since the identification, in 1983-84,^1,2 of human immunodeficiency virus (HIV) as the etiological agent of AIDS, significant progress has been made in the treatment of HIV-infected patients. This has been in part due to the discovery and clinical use of an increasing number of anti-HIV drugs. However, while highly active antiretroviral therapy (HAART)³ approaches have reduced the morbidity and mortality, the intertwined problems of drug induced viral resistance, poor compliance with complex regimens and therapy failure continue. Therefore, there remains a pressing need for the development of new antiviral agents that can be used not only as first line therapeutic candidates, but also in the antiretroviral-experienced patient population.     

Multivariate optimization of the Kharasch–Sosnovsky allylic oxidation of olefins

The multivariate optimization method known as simplex is applied to the Kharasch–Sosnovsky allylic oxidation of double bonds. By applying this method, the amounts of three variables (copper source, oxidant, and additive) are optimized at the same time. Under the conditions thus obtained the reaction takes place in a considerable shorter time, being the alkene the limiting reagent. These conditions are applied to some monoterpenes and sesquiterpenes leading regioselectively to the corresponding benzoate esters, opening a route to the employment of this reaction in the synthesis of more complex molecules.     

On distributive modules and rings

In this paper we study ω-distributive modules, where ω is a cardinal number. We extend a characterization of distributive modules to ω-distributive modules. In particular, the case in which ω = n is a finite cardinal is considered. We apply the results to the case n = 2, obtaining new characterizations for distributive modules and rings. Special attention is given to saturated submodules and ideals.     

Methodological reflections on a three-step-design combining observation,stimulated recall and interview

In this paper a tripartite qualitative design combining abservation, stimulated recall and interview is presented and discussed. This three-step-design makes it possible to get insight into the interaction of internal and external processes when solving mathematical tasks. The data analysis depends on the research question and the methodological approach. In the light of two research projects in mathematics education two different methods of data analysis are presented and methodologically reflected.     

Randomised circular means of Fourier transforms of measures

We explore decay estimates for circular means of the Fourier transform of a measure on in terms of its -dimensional energy. We find new upper bounds for the decay exponent. We also prove sharp estimates for a certain family of randomised versions of this problem.

     

Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear

The increase in the proportion of elderly in Europe brings with it certain challenges that society needs to address, such as custodial care. We propose a scalable, easily modulated and live assistive technology system, based on a comfortable smart footwear capable of detecting walking behaviour, in order to prevent possible health problems in the elderly, facilitating their urban life as independently and safety as possible. This brings with it the challenge of handling the large amounts of data generated, transmitting and pre-processing that information and analysing it with the aim of obtaining useful information in real/near-real time. This is the basis of information theory. This work presents a complete system aiming at elderly people that can detect different user behaviours/events (sitting, standing without imbalance, standing with imbalance, walking, running, tripping) through information acquired from 20 types of sensor measurements (16 piezoelectric pressure sensors, one accelerometer returning reading for the 3 axis and one temperature sensor) and warn the relatives about possible risks in near-real time. For the detection of these events, a hierarchical structure of cascading binary models is designed and applied using artificial neural network (ANN) algorithms and deep learning techniques. The best models are achieved with convolutional layered ANN and multilayer perceptrons. The overall event detection performance achieves an average accuracy and area under the ROC curve of 0.84 and 0.96, respectively.     

Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images

Magnetic Resonance (MR) white matter hyperintensities have been shown to predict an increased risk of developing cognitive decline. However, their actual role in the conversion to dementia is still not fully understood. Automatic segmentation methods can help in the screening and monitoring of Mild Cognitive Impairment patients who take part in large population-based studies. Most existing segmentation approaches use multimodal MR images. However, multiple acquisitions represent a limitation in terms of both patient comfort and computational complexity of the algorithms. In this work, we propose an automatic lesion segmentation method that uses only three-dimensional fluid-attenuation inversion recovery (FLAIR) images. We use a modified context-sensitive Gaussian mixture model to determine voxel class probabilities, followed by correction of FLAIR artifacts. We evaluate the method against the manual segmentation performed by an experienced neuroradiologist and compare the results with other unimodal segmentation approaches. Finally, we apply our method to the segmentation of multiple sclerosis lesions by using a publicly available benchmark dataset. Results show a similar performance to other state-of-the-art multimodal methods, as well as to the human rater.     

Experimental NMR and MS study of benzoylguanidines. Investigation of E/Z isomerism

Molecules containing the guanidinic nuclei possess several pharmacological applications, and knowing the preferred isomers of a potential drug is important to understand the way it operates pharmacologically. Benzoylguanidines were synthesized in satisfactory to good yields and characterized by NMR, Electrospray Ionization Mass Spectrometry (ESI‐MS) and Fourrier Transform InfraRed Spectroscopy techniques (FTIR). E/Z isomerism of the guanidines was studied and confirmed by NMR analysis in solution (¹H‐¹³C Heteronuclear Single Quantum Coherence (HSQC) and Heteronuclear Multiple‐Bond Correlation (HMBC), ¹H‐¹⁵N HMBC, ¹H‐¹H Correlation Spectroscopy (COSY) and Nuclear Overhauser Effect Spectroscopy (NOESY) experiments) at low temperatures. Compounds with p‐Cl and p‐Br aniline moiety exist mainly as Z isomer with a small proportion of E isomer, whereas compounds with p‐NO2 moiety showed a decrease in proportion of isomer Z. The results are important for the application of these molecules as enzymatic inhibitors. Copyright © 2013 John Wiley & Sons, Ltd.