THE EFFECTS OF STREPTOZOTOCIN DIABETES AND DIETARY IRON INTAKE ON CATALASE, GLUTATHIONE PEROXIDASE, SUPEROXIDE DISMUTASE AND LIPID PEROXIDATION IN CARDIAC AND SKELETAL MUSCLES OF RATS

Catalase, glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD) prevent oxygen free radical mediated tissue damage. Diabetes increases and a low dietary intake of iron decreases catalase activity in muscle. Therefore, the combined effects of diabetes and iron deficiency on the free radical scavenging enzyme system and lipid peroxidation were studied. Male, weanling rats were injected with streptozotocin (65 mg/kg, IV) and fed diets containing either 35 ppm iron (Db + Fe) or 8 ppm iron (Db $-$ Fe). Sham injected animals served as iron adequate (C + Fe) or iron deficient (C $-$ Fe) controls. Heart, gastrocnemius (GT), soleus and tibialis anterior (TA) muscles were dissected, weighted and analyzed for catalase, GSH-Px and SOD activities after 3, 6 or 9 weeks on the respective diets. The TBA assay was used to assess lipid peroxidation in the GT muscle. Diabetes elevated catalase activity in all muscles while it had a slight lowering effect on SOD and GSH-Px activities in the GT and TA muscles. In the C $-$ Fe rats, catalase activity declined and remained depressed in all muscles except the heart. There was an elevation in GSH-Px and SOD in the GT muscles of these animals after 6 weeks but not after 9 weeks of consuming the low iron diet. The Db $-$ Fe animals were unable to respond to the diabetic state with catalase activity as high as observed in the Db + Fe rats. Treatment with insulin or iron returned catalase to control levels. The C $-$ Fe animals had significantly lower levels of lipid peroxidation than the other groups at 6 and 9 weeks. Refeeding an iron adequate diet resulted in an increase in lipid peroxidation levels. These studies indicate that skeletal muscle free radical scavenging enzymes are sensitive to metabolic states and that dietary iron influences lipid peroxidation in this tissue. ^

Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data

The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^