Dietary lutein modulates inducible nitric oxide synthase (iNOS) gene and protein expression in mouse macrophage cells (RAW 264.7)

Lutein is an oxycarotenoid primarily found in dark-green leafy vegetables such as spinach and kale. Other dietary sources which contain moderate amounts of lutein include corn, egg yolks, and fruits like oranges and kiwi. Although a number of in vivo studies have demonstrated the anti-inflammatory effect of lutein, its in vitro anti-inflammatory molecular mechanism of action is unknown. In this study, we have investigated the in vitro anti-inflammatory effect of lutein using LPS-stimulated mouse macrophage cell line (RAW 264.7). The inhibition of LPS-stimulated nitric oxide (NO) was measured and the expression of inducible NO synthase (iNOS) was assessed at the mRNA and protein levels in mouse macrophage cells after treatment with lutein. Lutein decreased the LPS-induced NO production by 50% compared to LPS alone. Real-time PCR analysis showed a 1.9-fold reduction in iNOS expression at the mRNA level. Western blotting revealed that lutein decreased LPS-induced iNOS expression at the protein level by 72.5%. The results of this study suggest the anti-inflammatory properties of lutein demonstrated by the decrease in the expression of iNOS at the mRNA and protein levels in RAW 264.7 mouse macrophage cells.     

A Cluster-based Stratified Hybrid Decision Support Model under Uncertainty: Sustainable Healthcare Landfill Location Selection

Applied Intelligence - Nowadays, healthcare waste management has become one of the significant environmental, health, and social problems. Due to population and urbanization growth and an increase...     

An Overview of Audio Event Detection Methods from Feature Extraction to Classification

Audio streams, such as news broadcasting, meeting rooms, and special video comprise sound from an extensive variety of sources. The detection of audio events including speech, coughing, gunshots, etc. leads to intelligent audio event detection (AED). With substantial attention geared to AED for various types of applications, such as security, speech recognition, speaker recognition, home care, and health monitoring, scientists are now more motivated to perform extensive research on AED. The deployment of AED is actually a more complicated task when going beyond exclusively highlighting audio events in terms of feature extraction and classification in order to select the best features with high detection accuracy. To date, a wide range of different detection systems based on intelligent techniques have been utilized to create machine learning-based audio event detection schemes. Nevertheless, the preview study does not encompass any state-of-the-art reviews of the proficiency and significances of such methods for resolving audio event detection matters. The major contribution of this work entails reviewing and categorizing existing AED schemes into preprocessing, feature extraction, and classification methods. The importance of the algorithms and methodologies and their proficiency and restriction are additionally analyzed in this study. This research is expanded by critically comparing audio detection methods and algorithms according to accuracy and false alarms using different types of datasets.     

A closed-loop supply chain configuration considering environmental impacts: a self-adaptive NSGA-II algorithm

Applied Intelligence - Configuration of a supply chain network is a critical issue that contributes to choose the best combination for a set of facilities in order to attain an effective and...     

Development of the Kansa method for solving seepage problems using a new algorithm for the shape parameter optimization

In this research, the Kansa or Multiquadric method (MQ) has been developed for solving the seepage problems in 2D and 3D arbitrary domains. This research is the first application of this method for seepage analysis in both confined and unconfined porous media. The domain decomposition approach has been employed for applying MQ method easily in inhomogeneous and irregular complex geometries and decreasing the computational costs. For determining the optimum shape parameter that affects strongly the accuracy of MQ and other RFB methods, a new scheme that decreases drastically the computational time is introduced. The efficiency of the proposed algorithm has been examined under various radial basis functions, variations of number of interpolating points and points distribution, through a numerical example with analytical solution. Eventually, three examples including different boundary conditions are presented. Comparing results of the examples with other numerical methods indicates that the present approach has high capability and accuracy in solving seepage problems.