Background: Madurella. mycetomatis is most common causative agent of mycetoma in Sudan and worldwide. No vaccines are available till now so design of effective vaccine is essential as protection tool. Peptide vaccine can overcome the common side effects of the conventional vaccines. The aim of this study was to design peptide based vaccine for M.Mycetomatis Translationally Controlled Tumor Protein (TCTP) using immunoinformatics tools. Materials and methods:TCTP sequences were retrieved from NCBI and then processed using BioEdit program to determine conserved regions and different immunoinformatics tools from IEDB. Population coverage analysis was performed for the most promising epitopes. Homology modelling was performed to show their structural positions in TCTP. Protein analysis was done using Expasy (ProtParamsotware). Results and conclusion:Four epitopes passed the Bepipred, Emini, Kolaskar and Tongaonkar tools. 111 epitopes were predicted to interact with MHCI alleles with IC50 < 500 nM, three of them were most promising. 274 predicted epitopes were interacted with MHCII alleles with IC50 < 100 nM, four of them were most promising. The epitope (YMKSVKKAL) was the most promising one concerning its binding with MHCI alleles, while (FRLQSTSFD) was the most promising for MHC II. The epitope (YLKAYMKSV) is shared betweenMHC I and II. For the population coverage of M. Mycetomatis TCTP vaccine Sudan (90.39%) had the highest percentage for MHC I. This is the first computational vaccinology study conducted in mycetoma caused by M. Mycetomatis using TCTP.
Heavy crude oils contain considerable amounts of contaminants (e.g., sulfur, nitrogen, and heavy metals) and asphaltenes. The high contents of such contaminants in crude oil would decrease the efficiency of the refining process at the distillation column and lead to various problems such as air pollution, corrosion, and catalyst poisoning. Viewing such difficulties, the objective of this paper is to study the effect and performance of the hydrotreating process of heavy crude oil before atmospheric distillation. Such a process is expected to improve the properties of heavy crude oil and consequently increase the efficiency of the refining process. Process simulation of such process was performed via ASPEN HYSYS V.9., based on an existing Egyptian refinery plant with a feedstock of (50/50% mixture of light and heavy Arabian crudes). The process simulation results showed that a significant improvement had been achieved in the characteristics of crude oil after the hydrotreating process (e.g., lower contaminants content, lower density, and higher yield of middle distillates).
Since the last few decades, global energy demand has steadily increased, creating a critical issue, particularly in the industrial sector. Energy conservation is an important issue in process design. Heat exchanger networks (HENs) synthesis have been the most studied in recent decades as its effect on energy recovery between process streams is significantly important. Pinch analysis and mathematical programming have been used for the synthesis of HENs. The proposed approaches can achieve the target of minimum utility consumption and develop networks to obtain a minimum number of heat exchange units. This paper presents a study to compare the performance of the heat exchanger network synthesized via pinch technology and mathematical programming for a crude oil plant. In addition, an application of a ready program like THEN is utilized to solve the problem. Based on the extracted data, the HEN is designed via the above-mentioned techniques, then, the results are analyzed and discussed in detail.
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