CuI‐Catalyzed Multicomponent Synthesis of Aminoindolizines from Aldehydes,Amines, and Alkynes under Solvent‐Free Conditions

A direct and efficient approach to 1‐aminoindolizines through three‐component one‐pot reaction of heteroaryl aldehydes, secondary amines and terminal alkynes catalyzed by CuI under solvent‐free conditions has been developed. This methodology provides a rapid access to substituted aminoindolizines with good yields (up to 97%).     

膦酰肽和膦酰酯肽的汇聚式合成

本文首先介绍了膦酰肽的分类、结构特征以及膦酰肽的主要合成方法,然后详细介绍了类Mannich反应在合成氨基膦酸衍生物中的应用,并介绍了以类Mannich反应为关键步骤通过汇聚式的方法合成膦酰肽、膦酰酯肽、次膦酰肽、次膦酰酯肽、磺酰膦酰杂交肽的研究进展.汇聚式的合成方法具有原料简单、合成步骤少、原子经济性好等优点.     

Determination of phenolic compounds and authentication of PDO Lambrusco wines by HPLC-DAD and chemometric techniques

This work proposes a fast and simple method for detection and quantification of phenolic compounds in PDO Lambrusco wines using HPLC-DAD and chemometric techniques. Samples belonging to three different varieties of Lambrusco (Grasparossa, Salamino and Sorbara) were analyzed to provide a methodology appropriate for routine analysis. Given the high complexity of the sample and the coelution among chromatographic peaks, the use of chemometric techniques to extract the information of the individual eluting compounds was needed. Multivariate curve resolution-alternating least squares (MCR-ALS) allowed the resolution of the chromatographic peaks obtained and the use of this information for the quantification of the phenolic analytes in the presence of interferences. Use of multiset analysis and local rank/selectivity information was proven to be crucial for the correct resolution and quantification of compounds. The quantitative data provided by MCR-ALS about the phenolic targets and additional compounds present in the samples analyzed provided wine composition profiles, which were afterwards used to distinguish among wine varieties. Principal component analysis applied to the wine profiles allowed characterizing the wines according to their varieties.     

Fe(NO3)3·9H2O as Efficient Catalyst for One‐pot Synthesis of Highly Functionalized Piperidines

Fe(NO₃)₃·9H₂O is used as an efficient and effective catalyst for the one‐pot three‐component synthesis of highly functionalized piperidines from aromatic aldehydes, anilines and b–ketoesters in ethanol at ambient temperature. This procedure includes some important aspects like the easy work‐up, no need to column chromatography, simple and readily available precursors, and good to high yields.     

Acetylcholinesterase inhibitors: Modeling potential candidates

Alzheimer's disease is the leading cause of dementia for elderly people. The main active therapeutic is supported on the increased levels of acetylcholine in the synaptic cleft, based on reversible inhibition of the acetylcholinesterase (AChE) enzyme. This article aims to propose possible inhibitor candidates for AChE, designed from nonisoprenoid lipids of cashew (Anacardium occidentale), and based on several electronic properties. These electronic properties were obtained through B3LYP/6‐311+G(2d,p) calculation level. Principal component analysis reveals that from the set of studied molecular structures a small group is correlated with donepezil, a drug with known biological activity. © 2012 Wiley Periodicals, Inc.     

Three‐Component One‐Pot Synthesis of 1,4‐Dihydropyrano[2,3‐c]pyrazole Derivatives in Aqueous Media

Abstract

6‐Amino‐5‐cyano‐4‐aryl‐1,4‐dihydropyrano[2,3‐c]pyrazoles were synthesized by three‐component reaction of aromatic aldehydes, malononitrile, and 3‐methyl‐1‐phenyl‐2‐pyrazolin‐5‐one using triethylbenzylammonium chloride (TEBA) as catalyst in aqueous media. The reaction has the advantages of good yield, less pollution, ease of separation, and of being environment friendly.     

Risk evaluation of diabetes mellitus by relation of chaotic globals to HRV

This study's aim is to analyze heart rate dynamics in subjects with diabetes by measures of heart rate variability (HRV). The correlation of chaotic global parameters in the two cohorts is able to assess the probability of cardiac failure and other dynamical diseases. Adults (46) were divided into two equal groups. The autonomic evaluation consisted of measuring HRV for 30 min in supine position in absence of any physical, sensory, or pharmacological stimuli. Chaotic global parameters are able to statistically determine which series of electrocardiograph interpeak intervals in short time‐series are diabetic and which are not. The chaotic forward parameter that applies all three parameters is suggested to be the most appropriate and robust algorithm. This was decided after tests for normality; followed by one‐way analysis of variance (ANOVA1); (P < 0.09) and Kruskal–Wallis technique (P < 0.03). Principal component analysis implied two components represent 99.8% of total variance. Therefore, diabetes is a disease which reduces the chaotic response and, as such may be termed a dynamical condition such as are cardiac arrest, asthma, and epilepsy. © 2014 Wiley Periodicals, Inc. Complexity 20: 84–92, 2015     

Quality by Design Approach for Development of W/O Type Microemulsion-Based Transdermal Systems for Atenolol

The objective of the present investigation was to develop microemulsion-based transdermal systems of highly water soluble drug, Atenolol, by quality by design technique. Atenolol-loaded W/O microemulsions were optimized using D-optimal design with concentrations of oil, surfactants mixture, and water as independent variables, which was converted into microemulsion-based gel (MBG). The results of in vitro permeation of the optimized batch of Atenolol-loaded MBG revealed significant increase in permeability parameters as compared to its convention gel. All results suggested suitability of W/O type MEs as carriers for transdermal delivery of highly water soluble drug, Atenolol.     

CORSICA: correction of structured noise in fMRI by automatic identification of ICA components

When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR data sets (typically acquired with TR >1 s), such spatial priors can be applied to fMRI data, regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR data sets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.