This chapter reviews the literature applying health behavior theories to indoor tanning. Few studies have tried to fit full versions of health behavior models to indoor tanning. Theoretical models from the family of theories referred to as the reasoned action approach (e.g., theory of planned behavior, behavioral alternative model, prototype willingness model, etc.) have been most commonly used to study indoor tanning. Results indicate that these models fit indoor tanning data moderately to extremely well. Two lesser known models, problem behavior theory and the terror management health model, have also demonstrated a reasonable fit. Two other common models, the health belief model and social cognitive theory, have never been fully tested with indoor tanning. However, key constructs from these models (e.g., perceived susceptibility and threat, modeling) have been used to understand indoor tanning. Empirical research conducted represents a solid start toward developing strong, comprehensive models of indoor tanning that can guide intervention efforts. This initial work needs to be expanded by conducting longitudinal studies and by including a broader age range in studies because the majority of existing work has focused on young adults. Incorporating findings related to tanning dependency, peer group affiliation, media influences and other constructs into these foundational models will also improve our understanding and ability to develop efficacious interventions to reduce engagement in this health risk behavior.

This chapter reviews the literature examining interventions to reduce indoor tanning (IT). The first objective was to highlight programs that show promise for large scale dissemination. The second objective was to promote criteria and standards for future intervention research efforts. The scope of interest for this review includes universal (for everyone in the population), selective (for those in the population who are at a greater risk), and indicated (for those who already are experiencing conditions that identify them as at risk) programs. The evaluation of the interventions resulted in three levels of evidence: (1) most promising, (2) emerging, and (3) mixed. For an intervention to be considered “most promising”, it was required that ten criteria be met through examination of research findings in published reports consistent with Flay and colleagues (Prev Sci 6(3):151–175, 2005). Interventions that were classified as “emerging” met most of the criteria. Finally, interventions classified as “mixed” did not reach threshold on more than two criteria that were deemed critical. The results revealed that there was very limited research on IT interventions that meet all the evaluation criteria. Only one intervention approach met all of the criteria (Appearance Booklet) (Hillhouse and Turrisi, Behav Med 25(4):395–409, 2002; Hillhouse et al., Cancer 113(11):3257–3266, 2008). Although the number of published papers in the IT area has increased dramatically over the past decade, these efforts have yet to translate into rigorously conducted intervention trials. The review points to important issues that need to be addressed in future research on the prevention of IT. Keywords

Proton therapy is a relatively new treatment modality for cancer, having recently been incorporated into hospitals in the last two decades. Although proton therapy has much higher start up and treatment costs than traditional methods of radiotherapy, it continues to expand in use today. One reason for this is that proton therapy has the advantage of a more precise localization of dose compared to traditional radiotherapy. Other proposed advantages of proton therapy in the treatment of cancer may lead to a faster expanse in its use if proven to be more effective than traditional radiotherapy. Therefore, much research must be done to investigate the possible negative and positive effects of using proton therapy as a treatment modality. In proton therapy, protons do account for the vast majority of dose. However, when protons travel through matter, secondary particles are created by the interactions of protons and matter en route to and within the patient. It is believed that secondary dose can lead to secondary cancer, especially in pediatric cases. Therefore, the focus of this work is determining both primary and secondary dose. In order to develop relevant simulations, the specifications of the treatment room and beam were based off of real-world facilities as closely as possible. Using available data from proton accelerators and clinical facilities, an accurate proton therapy nozzle was designed. Dose calculations were performed by MCNPX using a simple water phantom, and then beam characteristics were investigated to ensure the accuracy of the model. After validation of the beam nozzle, primary and secondary dose values were tabulated and discussed. By demonstrating the method of these calculations, the purpose of this work is to serve as a guide into the relatively recent field of Monte Carlo methods in proton therapy.

Indiana University-Purdue University Indianapolis (IUPUI) / Sequestration at the aggresome and degradation through autophagy are two approaches by which a cell can counteract the toxic effect of misfolded proteins. Tuberous sclerosis (TS) and cancer cells can become dependent on autophagy for survival due to the high demand for protein synthesis, thus making protein clearance a potential therapeutic target. Because of its histone deacetylase (HDAC) inhibitory activity, we hypothesized that 4-phenylbutyrate (4-PBA) inhibits HDAC6 and aggresome formation to induce TS cell death. We found that 4-PBA treatment increases cell death and reduces bortezomib-induced aggresome formation. To link these results with HDAC inhibition we used two other HDAC inhibitors, trichostatin A (TSA) and tubastatin, and found that they also reduce bortezomib-induced protein aggregation. Because tubulin is a target of HDAC6, we next measured the effect of the HDAC inhibitors and 4-PBA treatment on tubulin acetylation. As expected, tubastatin increased tubulin acetylation but surprisingly TSA and 4-PBA did not. Because 4-PBA did not significantly inhibit HDAC6, we next hypothesized that 4-PBA was alternatively inducing autophagy and increasing aggresome clearance. Surprisingly, autophagy inhibition did not prevent the 4-PBA-induced reduction in protein aggregation. In conclusion, we found 4-PBA to induce cell death and reduce aggresome levels in TS cells, but we found no link between these phenomena. We next hypothesized that loss of the Ral guanine nucleotide exchange factor Rgl2 induces cell death via autophagy inhibition in pancreatic adenocarcinoma (PDAC) cells. KRas is mutationally activated in over 90% of PDACs and directly activates Rgl2. Rgl2 activates RalB, a known regulator of autophagy, and Rgl2 has been shown to promote PDAC cell survival. We first confirmed that loss of Rgl2 does increase cell death in PDAC cells. Initial experiments using doubly tagged fluorescent p62 and LC3 (autophagy markers) suggested that loss of Rgl2 inhibited autophagosome accumulation, but after developing a more sophisticated quantitation method we found loss of Rgl2 to have no effect. We also measured endogenous LC3 levels, and these experiments confirmed loss of Rgl2 to have no effect on autophagy levels. Therefore, loss of Rgl2 increases cell death in PDAC cells, but does not have a significant effect on autophagy.

Indiana University-Purdue University Indianapolis (IUPUI) / Fanconi anemia (FA) is a heterogenous genetic syndrome characterized by progressive bone marrow failure, aneuploidy, and cancer predisposition. It is incompletely understood why FA-deficient cells develop gross aneuploidy leading to cancer. Since the mitotic spindle assembly checkpoint (SAC) prevents aneuploidy by ensuring proper chromosome segregation during mitosis, we hypothesized that the FA signaling network regulates the mitotic SAC. A genome-wide RNAi screen and studies in primary cells were performed to systematically evaluate SAC activity in FA-deficient cells. In these experiments, taxol was used to activate the mitotic SAC. Following taxol challenge, negative control siRNA-transfected cells appropriately arrested at the SAC. However, knockdown of fourteen FA gene products resulted in a weakened SAC, evidenced by increased formation of multinucleated, aneuploid cells. The screen was independently validated utilizing primary fibroblasts from patients with characterized mutations in twelve different FA genes. When treated with taxol, fibroblasts from healthy controls arrested at the mitotic SAC, while all FA patient fibroblasts tested exhibited weakened SAC activity, evidenced by increased multinucleated cells. Rescue of the SAC was achieved in FANCA patient fibroblasts by genetic correction. Importantly, SAC activity of FANCA was confirmed in primary CD34+ hematopoietic cells. Furthermore, analysis of untreated primary fibroblasts from FA patients revealed micronuclei and multinuclei, reflecting abnormal chromosome segregation. Next, microscopy-based studies revealed that many FA proteins localize to the mitotic spindle and centrosomes, and that disruption of the FA pathway results in supernumerary centrosomes, establishing a role for the FA signaling network in centrosome maintenance. A mass spectrometry-based screen quantifying the proteome and phospho-proteome was performed to identify candidates which may functionally interact with FANCA in the regulation of mitosis. Finally, video microscopy-based experiments were performed to further characterize the mitotic defects in FANCA-deficient cells, confirming weakened SAC activity in FANCA-deficient cells and revealing accelerated mitosis and abnormal spindle orientation in the absence of FANCA. These findings conclusively demonstrate that the FA signaling network regulates the mitotic SAC, providing a mechanistic explanation for the development of aneuploidy and cancer in FA patients. Thus, our study establishes a novel role for the FA signaling network as a guardian of genomic integrity.

Indiana University-Purdue University Indianapolis (IUPUI) / All platinum (Pt)-based chemotherapeutics exert their efficacy primarily via the formation of DNA adducts which interfere with DNA replication, transcription and cell division and ultimately induce cell death. Repair and tolerance of Pt-DNA lesions by nucleotide excision repair and homologous recombination (HR) can substantially reduce the effectiveness of the Pt therapy. Inhibition of these repair pathways, therefore, holds the potential to sensitize cancer cells to Pt treatment and increase clinical efficacy. Replication Protein A (RPA) plays essential roles in both NER and HR, along with its role in DNA replication and DNA damage checkpoint activation. Each of these functions requires RPA binding to single-stranded DNA (ssDNA). We synthesized structural analogs of our previously reported RPA inhibitor TDRL-505, determined the structure activity relationships and evaluated their efficacy in tissue culture models of epithelial ovarian cancer (EOC) and non-small cell lung cancer (NSCLC). These data led us to the identification of TDRL-551, which exhibited a greater than 2-fold increase in in vitro and cellular activity. TDRL-551 showed synergy with Pt in tissue culture models of EOC and in vivo efficacy, as a single agent and in combination with platinum, in a NSCLC xenograft model. These data demonstrate the utility of RPA inhibition in EOC and NSCLC and the potential in developing novel anticancer therapeutics that target RPA-DNA interactions.

Indiana University-Purdue University Indianapolis (IUPUI) / In this study, a novel model for manipulating cancer blood cells based on multi-stage micro channels under varied low field concepts is proposed. Steering Device approach was followed to manipulate the cancer cells based on their various differential potentials across their membranes. The proposed approach considers the size and the surface potential as well as the iso electronic structure of the cells. These research objectives emphasize the separation of the cells in the blood stream, and differentiates various blood cells and tumors for further analysis within the microfluidic channels. The dimensions of the channel sets the required electric field for manipulating the cancer cells within the channels using low electrode voltage function. The outcomes of this research may introduce a new diagnostic approach of finding the minimum residual disease (MRD) scans, early detection and analysis scans. This thesis provides a mathematical model, detailing the theory of the cell sorting device, manipulating the blood cancer cells and design of the device structure are also detailed, leading to the optimum research parameters and process. A Computer Aided Design (CAD) was used to model the multi-cell sorting lab-on-chip device, details of hardware and software were used in the simulation of the device various stages. Reverse engineering to configure the potentials for sorting mechanism needs is discussed. The thesis work also presents a comparative study of this sorting mechanism and the other commercially available devices. The practical model of the proposed research is laid out for future consideration.

Indiana University-Purdue University Indianapolis (IUPUI) / Loneliness is a known risk factor for poor mental and physical health outcomes in the general population, and preliminary research suggests that loneliness is linked to poorer health in cancer patients as well. Various aspects of the cancer experience (e.g., heightened existential concerns) lend themselves to making patients feel alone and misunderstood. Furthermore, loneliness theory suggests that negative social expectations, which may specifically relate to the cancer experience, precipitate and sustain loneliness. Thus, loneliness interventions in cancer should be tailored to address illness-related social conditions and negative social expectations. Prior to the development of loneliness interventions for cancer populations, cancer-specific tools are needed to assess: (1) loneliness attributed to cancer (i.e., cancer-related loneliness), and (2) negative social expectations related to cancer. In the current project I developed measures of cancer-related loneliness and cancer-related negative social expectations for use in future theory-based loneliness research. A mixed-methods study design was employed. First, I developed items for the measure of cancer-related loneliness (i.e., the Cancer Loneliness Scale) based on theory, prior research, and expert feedback. Second, I conducted a clinic-based qualitative study (n=15) to: (1) obtain cancer patient feedback on the Cancer Loneliness Scale items, and (2) inform development of the item pool for the measure of negative social expectations (i.e., the Cancer-related Negative Social Expectations Scale). Interviews were audiotaped, transcribed verbatim, and then transferred to Atlas.ti for analysis. Content analysis was used to analyze data regarding patient feedback and theoretical thematic analysis was used to analyze data regarding negative social expectations. Overall, patients said they liked the Cancer Loneliness Scale and no changes were made to the items based on patient feedback. Based on results, I also created five content domains of negative social expectations that were represented in the item pool for the Cancer-related Negative Social Expectations Scale. Third, I conducted a telephone and mail-based quantitative study (n=186) to assess psychometric properties of the two new measures. Dimensionality was determined using confirmatory factor analysis. Reliability was assessed by examining internal consistency coefficients and construct validity was assessed by examining theoretical relationships between the Cancer Loneliness Scale, the Cancer-related Negative Social Expectations Scale, and existing reliable and valid measures of health and social well-being. The final products of the project included a 7-item unidimensional Cancer Loneliness Scale and 5-item unidimensional Cancer-related Negative Social Expectations Scale. Excellent evidence for reliability and validity was found for both measures. The resulting measures have both clinical and research utility.

The text-guided diffusion model GLIDE (Guided Language to Image Diffusion for Generation and Editing) is the state of the art in text-to-image generative artificial intelligence (AI). GLIDE has rich representations, but medical applications of this model have not been systematically explored. If GLIDE had useful medical knowledge, it could be used for medical image analysis tasks, a domain in which AI systems are still highly engineered towards a single use-case. Here we show that the publicly available GLIDE model has reasonably strong representations of key topics in cancer research and oncology, in particular the general style of histopathology images and multiple facets of diseases, pathological processes and laboratory assays. However, GLIDE seems to lack useful representations of the style and content of radiology data. Our findings demonstrate that domain-agnostic generative AI models can learn relevant medical concepts without explicit training. Thus, GLIDE and similar models might be useful for medical image processing tasks in the future - particularly with additional domain-specific fine-tuning.