Computational design of a new multi-epitope vaccine using immunoinformatics approach against mastitis disease.

Mastitis disease causes significant economic losses in dairy farms by reducing milk production, increasing production costs, and reducing milk quality. Streptococcus agalactiae continues to be a major cause of mastitis in dairy cattle. To date, there has been no approved multi-epitope vaccine against this pathogen in the market. In the present study, an efficient multi-epitope vaccine against S. agalactiae, the causative agent of mastitis, was designed using various immonoinformtics approaches. Potential epitopes were selected from Sip protein to improve vaccine immunogenicity. The designed vaccine is more antigenic in nature. Then, linkers and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, Toxicity, and allergenicity. Prediction of three-dimensional (3 D) structure of multi-epitope vaccine, followed by refinement and validation, was conducted to obtain a high-quality 3 D structure of the designed multi-epitope vaccine. The designed vaccine was then subjected to molecular docking with Toll-like receptor 11 (TLR11) receptor to evaluate its binding efficiency followed by dynamic simulation for stable interaction. In silico cloning approach was carried out to improve the expression of the vaccine construct. These analyses indicate that the designed multi-epitope vaccine may produce particular immune responses against S. agalactiae and may be further helpful to control mastitis after in vitro and in vivo immunological assays.

Fullerene C60 containing porphyrin-like metal center as drug delivery system for ibuprofen drug.

Today, drug delivery systems based on nanostructures have become the most efficient to be studied. Recent studies revealed that the fullerenes can be used as drug carriers and transport drugs in a target cell. The aim of the present work is to study the interaction of C60 fullerene containing porphyrin-like transition metal-N4 clusters (TMN4C55, TM = Fe, Co, and Ni) with a non-steroidal anti-inflammatory drug (ibuprofen (Ibp)) by employing the method of the density functional theory. Results showed that the C60 fullerene with TMN4 clusters could significantly enhance the tendency of C60 for adsorption of ibuprofen drug. Also, our ultraviolet-visible results show that the electronic spectra of Ibp/TMN4C55 complexes exhibit a blue shift toward lower wavelengths (higher energies). It was found that the NiN4C55 fullerene had high chemical reactivity, which was important for binding of the drug onto the carrier surface. In order to gain insight into the binding features of Ibp/TMN4C55 complexes, the atoms in molecules analysis was also performed. Our results exhibit the electrostatic features of the Ibp/TMN4C55 bonding. Consequently, this study demonstrated that the TMN4C55 fullerenes could be used as potential carriers for delivery of Ibp drug in the nanomedicine domain. Graphical Abstract The TMN4C55 (TM=Fe, Co, and Ni) fullerenes could be used as potential carriers for delivery of ibuprofen drug in the nanomedicine domain.

Data on multicultural education and diagnostic information profiling: Culture, learning styles and creativity.

This article contains data related to multicultural education and diagnostic information profiling preliminary findings. It includes the responses of 253 students. The data consists of six sections, i) culture: race, ethnicity, language and identity; ii) learning preferences: physiological and perceptual; iii) cognitive learning styles: physical, emotional and mental; iv) creativity skills and problem solving skills; v) motivation; and vi) students' background knowledge. The data may be used as part of data analytics for specific personalized e-learning platform.