Papers by Keyword: Vaccine

Abstract: The worldwide society was devastated by the 2019 coronavirus illness (COVID19) epidemic in Wuhan, China, which overloaded advanced medical systems around the world. The World Health Organization (WHO) is constantly monitoring and responding to the pandemic. The current rapid and exponential development in patient numbers necessitates the use of AI technology to forecast possible outcomes of infected individuals in order to provide suitable therapy. The goal is to find the machine learning-based solution that best fits the Covid19 vaccination predictions with the highest accuracy. Variable identification, univariate analysis, bivariate and multivariate analysis, missing value handling and data validation analysis, data cleaning / preparation, and data validation analysis are all accomplished using supervised machine learning technology (SMLT). Various types of data, such as visualisation, are gathered. For the entire given dataset. Proposal of a machine learning-based method for accurately predicting the suitability of Covid19 vaccine prediction.

Abstract: Cancer is a serious threat to human health and is the most interesting research field at present. Compared to conventional treatments, tumor immunotherapy has a unique advantage in cancer treatment, favored by more and more outcomes from research or clinical trials of institutions and pharmaceutical companies, which is showing a booming trend recently. Due to the complexity of the immune system, tumor immunotherapy covers a variety of mechanisms and approaches, including immune checkpoint inhibition, vaccine-based therapies, adoptive T cell transfer, and therapeutic antibodies. Through the investigation of a large number of literature and database information, this paper focuses on the mechanisms and applications of current immunotherapies, aiming to explain the general trend and direction of tumor immunotherapy development.

Abstract: Recently, O-type foot and mouth disease epidemic situation has changed, there has been MYA98 epidemic strains, has caused many Asian countries for many kinds of animal damage. In January 2011, a new matching vaccine developed, namely Foot and mouth disease type O inactivated vaccine (O/MYA98/BY/2010 strain). In order to master this vaccine effectiveness in pig production, all the individual pigs in the ten farms had been immunized.A total of 97786 individuals or times immunized pigs were observed. All pigs were traced surveillance for foot and mouth clinical signs. A total of 295 serum samples were detected for antibody titers.The results show that although there adverse side effects, but other than the vaccine adverse reactions and extent has significantly decreased, pigs immunized were non-occurrence of type O foot and mouth disease, the antibody titer is eligible. So here we show , the vaccine is safe and effective, can be widely used.

Abstract: A pseudorabies virus (PRV) mutant with deletions in genes for glycoprotein I (gI) and glycoprotein E (gE) was constructed and evaluated as a candidate vaccine strain for its protective by virulent wildtype (wt) PRV Ea strain challenge in pigs. Transfer plasmid pIESE was constructed and co-transfected with PRV genome into IBRS-2 cells to generate a recombinant mutant PRV Ea gI^-/gE^- virus. The recombinant virus was confirmed by Southern blotting and indirect immunofluorescence assay (IFA). In animal experiments, the immunogenicity was tested by PRV-enzyme-linked immunosorbent assay (ELISA) and PRV neutralizing assay. PRV Ea gI^-/gE^- elicited significant humoral immune responses to wt PRV Ea, and PRV gI^-/gE^- immunization protected pigs against a lethal challenge by virulent PRV Ea strain. These results suggested that the recombinant PRV Ea gI^-/gE^- might be considered as a potential candidate vaccine against PRV.

Abstract: To facilitate the application of Bayesian network in engineering fields, learning proper structure from dataset is one of the most efficiency Bayesian network modeling technique. In this paper, the description and characteristics of Bayesian networks and immune algorithms are discussed at first. Then, the extraction method of root node vaccines is proposed to accelerate the model structure learning process. Thirdly, the immune algorithm based method is also applied to search the best Bayesian network structure. Finally, the simulation studies based on a car start BN model are carried out and the results verify that the proposed Bayesian network structure learning method can build the objective structure from dataset more effectively and more efficiently with the root node vaccines.

Abstract: Due to the increasing scale of scheduling problems, the study is to explore an effective optimize scheduling approach for the semiconductor wafer fab. Semiconductor manufacturing is widely regarded as one of the most complex manufacturing processes in the world. The particular complexity, characterized by reentrant flows, uncertainties, mixed processing styles, etc., leads to a great challenge in its scheduling. Without powerful scheduling techniques it becomes practically impossible to design a manufacturing system. So, by means of a new coding method, and the adaptive mechanism of crossover and mutation, an improved immune algorithm (IA) is presented to solve the scheduling problem. The algorithm is based on clonal selection and affinity maturation for finding optimal solutions. To demonstrate the efficiency of the IA, some numerical experiments are carried out. The results show that the IA will yield a more efficient solution than several other scheduler.

Abstract: Cancer cells synthesize abnormal proteins and peptides which are associated to heat shock proteins being overproduced by these cells due to the stress induced by the particular biology of cancer tissue. We have purified on hydroxylapatite powder heat shock proteins using the HAparticles as purification bed, vectors for the proteins and vaccination adjuvant. The powder make possible that the purified HSPs and their associated peptides are transfected to the antigen presenting cells and presented to the T cells for the destruction of the cancer cells bearing the antigens.