Effects of semen storage and separation techniques on sperm DNA fragmentation

Objective: To determine the effect of semen storage and separation techniques on sperm DNA fragmentation. Design: Controlled clinical study. Setting: An assisted reproductive technology laboratory. Patient(s): Thirty normoozospermic semen samples obtained from patients undergoing infertility evaluation. Intervention(s): One aliquot from each sample was immediately prepared (control) for the sperm chromatin dispersion assay (SCD). Aliquots used to assess storage techniques were treated in the following ways: snap frozen by liquid nitrogen immersion, slow frozen with Tris-yolk buffer and glycerol, kept on ice for 24 hours or maintained at room temperature for 4 and 24 hours. Aliquots used to assess separation techniques were processed by the following methods: washed and centrifuged in media, swim-up from washed sperm pellet, density gradient separation, density gradient followed by swim-up. DNA integrity was then measured by SCD. Main Outcome Measure(s): DNA fragmentation as measured by SCD. Result(s): There was no significant difference in fragmentation among the snap frozen, slow frozen, and wet-ice groups. Compared to other storage methods short-term storage at room temperature did not impact DNA fragmentation yet 24 hours storage significantly increased fragmentation. Swim-up, density gradient and density gradient/swim-up had significantly reduced DNA fragmentation levels compared with washed semen. Postincubation, density gradient/swim-up showed the lowest fragmentation levels. Conclusion(s): The effect of sperm processing methods on DNA fragmentation should be considered when selecting storage or separation techniques for clinical use. (Fertil Steril (R) 2010;94:2626-30. (C) 2010 by American Society for Reproductive Medicine.)

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.