Clinical significance of sperm DNA damage in assisted reproduction outcome

Background: Sperm DNA damage shows great promise as a biomarker of infertility. The study aim is to determine the usefulness of DNA fragmentation (DF), including modified bases (MB), to predict assisted reproduction treatment (ART) outcomes. Methods: DF in 360 couples (230 IVF and 130 ICSI) was measured by the alkaline Comet assay in semen and in sperm following density gradient centrifugation (DGC) and compared with fertilization rate (FR), embryo cumulative scores (ECS1) for the total number of embryos/treatment, embryos transferred (ECS2), clinical pregnancy (CP) and spontaneous pregnancy loss. MB were also measured using formamidopyrimidine DNA glycosylase to convert them into strand breaks. Results: In IVF, FR and ECS decreased as DF increased in both semen and DGC sperm, and couples who failed to achieve a CP had higher DF than successful couples (+12.2 semen, P = 0.004; +9.9 DGC sperm, P = 0.010). When MB were added to existing strand breaks, total DF was markedly higher (+17.1 semen, P = 0.009 and +13.8 DGC sperm, P = 0.045). DF was not associated with FR, ECS or CP in either semen or DGC sperm following ISCI. In contrast, by including MB, there was significantly more DNA damage (+16.8 semen, P = 0.008 and +15.5 DGC sperm, P = 0.024) in the group who did not achieve CP. Conclusion: SDF can predict ART outcome for IVF. Converting MB into further DNA strand breaks increased the test sensitivity, giving negative correlations between DF and CP for ICSI as well as IVF. © 2010 The Author.

The Influence of COX-2 Single Nucleotide Polymorphisms on Abdominal Aortic Aneurysm Development and the Associated Inflammation

Introduction: Cyclooxygenase (COX)-2 influences cardiovascular disease and serum concentration of high-sensitivity C-reactive protein (hsCRP). The study purpose was to determine the influence of single nucleotide polymorphisms (SNPs) of the COX-2 gene on abdominal aortic aneurysm (AAA) development and serum hsCRP concentrations. Patients and Methods: Patients with AAA and disease-free controls were recruited. High-sensitivity C-reactive protein was measured by an enzyme-linked immunosorbent assay (ELISA) test. The distributions of COX-2 SNPs were investigated (rs20417 and rs4648307). The influence of the COX-2 SNPs on the hsCRP serum concentration was assessed.Results: A total of 230 patients with AAA and 279 controls were included. No difference was found in the genotype distribution of the COX-2 SNPs rs20417 (P = .26) and rs4648307 (P = .90). They did not influence the hsCRP concentration (P = .24 and P = .61, respectively). Haplotype analysis of COX-2 SNPs revealed no difference. Conclusion: These COX-2 SNPs do not play any role in AAA development and do not influence serum hsCRP. These results differentiate AAA development from atherosclerotic diseases.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.