Calcium phosphates grown on bacterial cellulose template

Bacterial cellulose membranes were employed as templates for calcium phosphates deposition by successive immersion in solutions of Ca(NO₃)₂·4H₂O and (NH₄)₂HPO₄, under ultrasonication. During the wet chemical reaction, mineral phases were loaded on bacterial cellulose fibrils, leading to precursor hybrid composites. These were subjected to a lyophilisation procedure in order to preserve the 3D porous aspect and afterwards to a thermal treatment with the aim of removing the polymeric phase and generating well crystallized structures. Different types of morphologies were achieved by varying the heating rate, as well as the calcination temperature and period. The as-prepared samples and the final ones were investigated from compositional and structural point of view through X-ray diffraction and Fourier-transform infrared spectroscopy and morphologically concerning by scanning electron microscopy. The magnetic properties were also evaluated in order to demonstrate the suitability of the obtained materials for the development of magnetic scaffolds dedicated to hard tissue applications.     

Sol-Gel Preparation and Spectroscopic Properties of Modified Sodium Silicate /Tartrazine Dye Nanocomposite

Silicon - Thin film nanocomposites of sodium silicate (80 SiO2 –20 Na2O)/ tartrazine dye (E102) prepared using sol gel process in acidic system. The change in the physicochemical properties...     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Preparation of Pure Uranium,Thorium, and Yttrium Oxides from El-Garra El-Hamra Sulfate Leach Liquor

Radiochemistry - The study deals with separation of uranium, thorium, and yttrium with highest possible purity from El-Garaa El-Hamara sulfate leach liquor. From the latter, almost complete...     

Fatal Attraction: How Bacterial Adhesins Affect Host Signaling and What We Can Learn from Them

The ability of bacterial species to colonize and infect host organisms is critically dependent upon their capacity to adhere to cellular surfaces of the host. Adherence to cell surfaces is known to be essential for the activation and delivery of certain virulence factors, but can also directly affect host cell signaling to aid bacterial spread and survival. In this review we will discuss the recent advances in the field of bacterial adhesion, how we are beginning to unravel the effects adhesins have on host cell signaling, and how these changes aid the bacteria in terms of their survival and evasion of immune responses. Finally, we will highlight how the exploitation of bacterial adhesins may provide new therapeutic avenues for the treatment of a wide range of bacterial infections.