One might therefore expect that trabecular microarchitecture would not be well correlated with fatigue properties in this test protocol. However, it is possible that despite our normalized test,
some types of structure are more favorable over time in a fatigue test than others, which could result in a correlation between a structural parameter and a fatigue property. Additional studies need to be conducted to further delineate the possible relationship between bone microarchitecture and fatigue behavior. Notably, in human trabecular bone, bone volume fraction is weakly correlated with strain at failure, which agrees with our findings [30]. Rather than Bafilomycin A1 applying the same load, which will result in low bone mass samples failing earlier than high bone mass samples, we applied the same apparent strain in each test. By developing this normalized fatigue test, we aimed at determining changes in fatigue properties due to differences at the tissue rather than the structural level. The fact that no difference in fatigue behavior was found between both groups indicates that either no changes occurred in the bone tissue fatigue properties or that we were unable to detect them. Increased mineralization that may have taken place in the ZOL group
due to lower turnover rate apparently did not lead to detectable changes in fatigue properties of the bone tissue. It may be, however, that a longer treatment period would have led to noticeable Smoothened Agonist nmr changes. Also, no untreated OVX group was included in this study, and therefore, (-)-p-Bromotetramisole Oxalate the effects of OVX versus those associated with ZOL treatment cannot be distinguished. Theoretically, it could be that OVX would lead to altered fatigue properties, which could have then been reversed by ZOL resulting in no differences between SHAM-OVX- and ZOL-treated OVX rats. This will need to be tested by additional studies. In our study, several samples did not fail
during the test, which reduced the sample size. Also, between-subject variation was found to be high, which, combined with the small sample size, reduced the power to detect differences between the groups. A power analysis revealed that a scientifically relevant difference of 30% between the two groups in apparent strain at failure would have been detectable if the sample size would have been 22. Therefore, large sample sizes would have been needed to detect any scientifically relevant differences, which were not noted in this study. Also, after starting the test, all samples needed to “settle in”. Thus, strains sometimes decreased or increased slightly directly after starting the test, and this may have affected the time to failure. However, this phenomenon occurred in both groups and, therefore, would not be expected to contribute to group-related differences.