• Korean Journal of Microbiology
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• v.52 no.1
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• pp.120-124
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• 2016

A certain size of DNA (28-29 kb long) to be packaged into P2-size head and the mutation in sid gene of bacteriophage P4 are the major factors to overcome "P2 sir-associated helper inefficiency". To clarify whether the presence of sid mutation is essential to overcome "P2 sir-associated helper inefficiency" or not, we tested the P4 derivative, P4 delRI::kmr, which is $sid^+$ and whose genome size supposed to be 28.5 kb long in the case of being packaged into $P2_{sir3}$-sized large head. As P4 delRI::kmr showed the low EOP with P2 sir3 lysogen, P4 delRI::kmr phage stock was prepared in P2 sir3 lysogen host to increase the EOP with P2 sir3 lysogen. Through this process, P4 delRI::kmr had been adapted for P2 sir3 lysogen. With a CsCl buoyant equilibrium density gradient experiment and gel electrophoresis of the isolated DNA, it was evident that the adaptation of P4 delRI::kmr for P2 sir3 lysogen was caused by the conformational change of DNA to be packaged into large head. The burst size determination experiments with P4 delRI::kmr phage stock adapted for P2 sir3 lysogen and normal P4 delRI::kmr phage stock showed that not the sid mutation but the size of DNA to be packaged (28-29 kb long) was essential to overcome "P2 sir-associated helper inefficiency".

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.80-96
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• 2022

Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1219-1224
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• 2015

Background: To date several common mutations in BRCA1 and BRCA2 associated with breast cancer have been reported in different populations. However, the common BRCA1 and BRCA2 mutations among breast cancer patients in Iran have not been described in detail. Materials and Methods: To comprehensively assess the frequency and distribution of the most common BRCA1 and BRCA2 mutations in Iranian breast cancer patients, we conducted this meta-analysis on 13 relevant published studies indentified in a literature search on PubMed and SID. Results: A total of 11 BRCA1 and BRCA2 distinct common mutations were identified, reported twice or more in the articles, of which 10 (c.2311T>C, c.3113A>G, c.4308T>C, c.4837A>G, c.2612C>T, c.3119G>A, c.3548A>G, c.5213G>A c.IVS16-92A/G, and c.IVS16-68A/G) mutations were in BRCA1, and 1 (c.4770A>G) was in BRCA2. The mutations were in exon 11, exon 13, intron 16, and exon 20 of BRCA1 and exon 11 of BRCA2. All have been previously reported in different populations. Conclusions: These meta analysis results should be helpful in understanding the possibility of any first true founder mutation of BRCA1/BRCA2 in the Iranian population. In addition, they will be of significance for diagnostic testing, genetic counseling and for epidemiological studies.