Preimplantation genetic diagnosis: Analysis of gene expression, nuclear DNA and cytoplasmic DNA

Preimplantation genetic diagnosis (PGD) following in vitro fertilization (IVF) offers couples at risk for transmitting genetic disorders the opportunity to identify affected embryos prior to replacement. In particular, embryo gender determination permits screening for X-linked diseases of unknown etiology. Analysis of embryos can be performed by polymerase chain reaction (PCR) amplification of material obtained by micromanipulation. This approach provides an alternative to the termination of an established pregnancy following chorionic villi sampling or amniocentesis. ^ Lately, the focus of preimplantation diagnosis and intervention has been shifting toward an attempt to correct cytoplasmic deficiencies. Accordingly, it is the aim of this investigation to develop methods to permit the examination of single cells or components thereof for clinical evaluation. In an attempt to lay the groundwork for precise therapeutic intervention for age related aneuploidy, transcripts encoding proteins believed to be involved in the proper segregation of chromosomes during human oocyte maturation were examined and quantified. Following fluorescent rapid cycle RT-PCR analysis it was determined that the concentration of cell cycle checkpoint gene transcripts decreases significantly as maternal age increases. Given the well established link between increasing maternal age and the incidence of aneuploidy, these results suggest that the degradation of these messages in aging oocytes may be involved with inappropriate chromosome separation during meiosis. ^ In order to investigate the cause of embryonic rescue observed following clinical cytoplasmic transfer procedures and with the objective of developing a diagnostic tool, mtDNA concentrations in polar bodies and subcellular components were evaluated. First, the typical concentration of mtDNA in human and mouse oocytes was determined by fluorescent rapid cycle PCR. Some disparity was noted between the copy numbers of individual cytoplasmic samples which may limit the use of the current methodology for the clinical assessment of the corresponding oocyte. ^

Minimizing makespan for hybrid flowshops with batch, discrete processing machines and arbitrary job sizes

This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.