The use of quantitative polymerase chain reaction amplification method to determine sex ratio of human spermatozoa in semen and to determine maternal contamination of amniotic fluid samples

We have modified a technique which uses a single pair of primer sets directed against homologous but distinct genes on the X and Y chromosomes, all of which are coamplified in the same reaction tube with trace amounts of radioactivity. The resulting bands are equal in length, yet distinguishable by restriction enzyme sites generating two independent bands, a 364 bp X-specific band and a 280 bp Y-specific band. A standard curve was generated to show the linear relationship between X/Y ratio average vs. %Y or %X chromosomal content. Of the 51 purified amniocyte DNA samples analyzed, 16 samples showed evidence of high % X contamination while 2 samples demonstrated higher % Y than the expected 50% X and 50% Y chromosomal content. With regards to the 25 processed sperm samples analyzed, X-sperm enrichment was evident when compared to the primary sex ratio whereas Y-sperm was enriched when we compared before and after selection samples.

Modified continuous ant colony algorithm for function optimization

Many classical as well as modern optimization techniques exist. One such modern method belonging to the field of swarm intelligence is termed ant colony optimization. This relatively new concept in optimization involves the use of artificial ants and is based on real ant behavior inspired by the way ants search for food. In this thesis, a novel ant colony optimization technique for continuous domains was developed. The goal was to provide improvements in computing time and robustness when compared to other optimization algorithms. Optimization function spaces can have extreme topologies and are therefore difficult to optimize. The proposed method effectively searched the domain and solved difficult single-objective optimization problems. The developed algorithm was run for numerous classic test cases for both single and multi-objective problems. The results demonstrate that the method is robust, stable, and that the number of objective function evaluations is comparable to other optimization algorithms.