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Ovarian cancer remains a deadly disease and its recurrence disease is due in part to the presence of disseminating ovarian cancer aggregates not removed by debulking surgery. During dissemination in a dynamic ascitic environment, the spheroid cells’ metabolism is characterized by low respiration and fragmented mitochondria, a metabolic phenotype that may not support secondary outgrowth after adhesion. Here, we investigated how adhesion affects cellular respiration and substrate utilization of spheroids mimicking early stages of secondary metastasis. Using different glucose and oxygen levels, we investigated cellular metabolism at early time points of adherence (24 h and less) comparing slow and fast-developing disease models. We found that adhesion over time showed changes in cellular energy metabolism and substrate utilization, with a switch in the utilization of mostly glutamine to glucose but no changes in fatty acid oxidation. Interestingly, low glucose levels had less of an impact on cellular metabolism than hypoxia. A resilience to culture conditions and the capacity to utilize a broader spectrum of substrates more efficiently distinguished the highly aggressive cells from the cells representing slow-developing disease, suggesting a flexible metabolism contributes to the stem-like properties. These results indicate that adhesion to secondary sites initiates a metabolic switch in the oxidation of substrates that could support outgrowth and successful metastasis.

Accelerated destructive degradation tests (ADDT) are often used to collect necessary data for assessing the long-term properties of polymeric materials. Based on the data, a thermal index (TI) is estimated. The TI can be useful for material rating and comparisons. The R package ADDT provides the functionalities of performing the traditional method based on the least-squares method, the parametric method based on maximum likelihood estimation, and the semiparametric method based on spline methods for analyzing ADDT data, and then estimating the TI for polymeric materials. In this chapter, we provide a detailed introduction to the ADDT package. We provide a step-by-step illustration for the use of functions in the package. Publicly available datasets are used for illustrations.

Accelerated destructive degradation test (ADDT) is a technique that is commonly used by industries to access material's long-term properties. In many applications, the accelerating variable is usually the temperature. In such cases, a thermal index (TI) is used to indicate the strength of the material. For example, a TI of 200 • C may be interpreted as the material can be expected to maintain a specific property at a temperature of 200 • C for 100,000 hours. A material with a higher TI possesses a stronger resistance to thermal damage. In literature, there are three methods available to estimate the TI based on ADDT data, which are the traditional method based on the least-squares approach, the parametric method, and the semiparametric method. In this chapter, we provide a comprehensive review of the three methods and illustrate how the TI can be estimated based on different models. We also conduct comprehensive simulation studies to show the properties of different methods. We provide thorough discussions on the pros and cons of each method. The comparisons and discussion in this chapter can be useful for practitioners and future industrial standards.

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