PURPOSE: To investigate the void parameters within the resin cements used for fiber post cementation by micro-CT (µCT) and regional push-out bonding strength. MATERIALS AND METHODS: Twenty-one, single and round shaped roots were enlarged with a low-speed drill following by endodontic treatment. The roots were divided into three groups (n=7) and fiber posts were cemented with Maxcem Elite, Multilink N and Superbond C&B resin cements. Specimens were scanned using µCT scanner at resolution of 13.7 µm. The number, area, and volume of voids between dentin and post were evaluated. A method of analysis based on the post segmentation was used, and coronal, middle and apical thirds considered separately. After the µCT analysis, roots were embedded in epoxy resin and sectioned into 2 mm thick slices (63 sections in total). Push-out testing was performed with universal testing device at 0.5 mm/min cross-head speed. Data were analyzed with Kruskal–Wallis and Mann–Whitney U tests (α=.05). RESULTS: Overall, significant differences between the resin cements and the post level were observed in the void number, area, and volume (P<.05). Super-Bond C&B showed the most void formation (44.86 ± 22.71). Multilink N showed the least void surface (3.51 ± 2.24 mm2) and volume (0.01 ± 0.01 mm3). Regional push-out bond strength of the cements was not different (P>.05). CONCLUSION: µCT proved to be a powerful non-destructive 3D analysis tool for visualizing the void parameters. Multilink N had the lowest void parameters. When efficiency of all cements was evaluated, direct relationship between the post region and push-out bonding strength was not observed.
Cementation* ; Dentin ; Resin Cements*

Objective: This study investigated the relationship of anthropometric and metabolic risk factors with seminal and sex steroidal hormone parameters in a screened population of healthy males. Methods: The participants were healthy young men without chronic or congenital diseases. The body composition parameters that we investigated were measured weight, height, and waist circumference (WC), as well as bioelectrical impedance analysis. Semen samples were analyzed for semen volume, sperm concentration, sperm motility and morphology, seminal pH, and liquefaction time. Biochemistry analysis, including glucose and lipid metabolism parameters, was conducted on fasting blood samples. Testicular volume was calculated separately for each testis using ultrasonography. Results: Body mass index exhibited an inverse association with total sperm count. WC showed negative correlations with numerous seminal parameters, including sperm concentration, total sperm count, sperm morphology, and follicle-stimulating hormone levels. The basal metabolic rate was associated with seminal pH, liquefaction time, and sperm motility. WC, fat mass percentage, and triglyceride levels exhibited negative correlations with sex hormone binding globulin. The measures of glucose metabolism were associated with a greater number of seminal parameters than the measures of cholesterol metabolism. C-reactive protein levels were inversely associated with sperm concentration and total sperm count. Conclusion Anthropometric and metabolic risk factors were found to predict semen quality and alterations in sex steroidal hormone levels.