Ataei, Afrouz

The ultimate challenge for assisted reproductive technologies (ARTs) is to select the most competent sperm population from a semen sample in an efficient way. In this thesis, we report on an effective sperm sorting microfluidic device that exploits the rheotaxis of sperm and investigates the sperm quality sorted under various flow conditions. Rheotaxis is the ability of a sperm cell to orient itself in the direction of the flow and swim against it. We developed a novel passively driven pumping system that provides a steady flow rate while it requires no external power source. We have also developed another rheotaxis-based microfluidic device that washes out the raw semen sample from any dead or less motile sperm. The device consists of a collection and waste chamber. To evaluate the effect of the shape and height of the collection chamber, we measured the sperm motility and velocity parameters after sorting using varying the shape and height of the collection chamber. We demonstrated that sperm selected with all devices have higher motility, normal morphology, and a fewer degree of DNA fragmentation compared to a control group.

Liver cancer is the sixth most common type of cancer worldwide and is the third leading cause of cancer related mortality. Several types of cancer can form in the liver. Hepatocellular carcinoma (HCC) makes up 75%-85% of all primary liver cancers and it is a malignant disease with limited therapeutic options due to its aggressive progression. While the exact cause of liver cancer may not be known, habits/lifestyle may increase the risk of developing the disease. Several risk prediction models for HCC are available for individuals with hepatitis B and C virus infections who are at high risk but not for general population. To address this challenge, an artificial neural network (ANN) was developed, trained, and tested using the health data to predict liver cancer risk. Our results indicate that our ANN can be used to predict liver cancer risk with changes with lifestyle and may provide a novel approach to identify patients at higher risk and can be bene ted from early diagnosis.