Characterization of Murine Breast Cancer Cell Lines for Anti-Cancer Vaccine

Breast cancer is the most commonly diagnosed cancer in women and the second leading cause of cancer death among women in the United States (1). While treatments involving radiation and chemotherapy currently exist, disease must be detected early in order for the treatments to be somewhat effective, and there is no effective treatment after metastasis occurs (2). Additionally, current therapies do not mitigate tumor immunosuppression. Decreasing the tumor-associated immunosuppressive conditions while activating antitumor immunity could prevent recurrence and metastasis, possibly leading to an effective treatment for cancer (3). Tumor cell vaccines could possibly address this issue and have become a recent topic of research. They have the potential to generate tumor regression and antitumor immune responses, but they have had low clinical response rates and poor immunogenicity so far (3, 4). We suspect the failure of cancer vaccines to be due to the immunosuppression and heterogeneity of breast cancers. Thus, to determine how and why different breast cancers induce different levels of immunosuppression, we studied different cancer cell lines of varying levels of immunogenicity. The study included five murine breast cancer cell lines, 4T1, 4T07, 66cl4, 168FARN, and 67NR. These are sister cell lines that were isolated from a Balb/cfC3H mouse and that differ in aggressiveness and metastatic capability. The production of immunosuppressive cytokines GM-CSF, G-CSF, M-CSF, IL-6, MCP-1, TGF-β, and VEGF was quantified for each of these cell lines. We also studied the effect these cytokines have on the expansion of myeloid-derived suppressor cells (MDSCs), which are known to suppress the immune response, and found that high levels of G-CSF are correlated with high numbers of MDSCs. A correlation between G-CSF levels and MDSC accumulation in these breast cancer cell lines could lead to future studies in which the effects of G-CSF are blocked in order to develop effective autologous breast cancer vaccines

An earnings-return model for strategic market planning / BEBR No. 869

Includes bibliographical references (p. 38-39).Few models currently exist which aid managers in their strategic market planning. The models or frameworks which do exist have a variety of shortcomings, a major one being an inadequate linkage to a business organization's dominant goals for existence -- earnings and return on investment. This paper develops a planning model based on a firm's present levels of earnings and return designed to provide a partial foundation on which its managers can base their strategic market planning. Depending upon the firm's placement in the model, different organizational objectives and strategies exist for improving future performance

Exploring the Role of Insulin Receptor Signaling in Hippocampal Learning and Memory, Neuronal Calcium Dysregulation, and Glucose Metabolism

In the late 90’s, emerging evidence revealed that the brain is insulin-sensitive, highlighted by broad expression of brain-specific insulin receptors and reports of circulating brain insulin. Contemporary literature robustly supports the role of insulin signaling in normal brain function and suggests that insulin-related processes diminish with aging, evidenced by decreased signaling markers, reduced insulin receptor density, and lower levels of insulin transport across the blood-brain barrier. In the context of pathological cognitive decline, clinical trials using intranasal insulin delivery have reported positive outcomes on memory and learning in patients with mild cognitive decline or early-stage Alzheimer’s disease. However, while the importance of insulin and its related actions in the brain are robustly supported, the distinct mechanisms and pathways that mediate these effects remain unclear. To address this, I conducted a series of experiments exploring the impact of insulin on memory and learning in two models: primary hippocampal cell cultures and the Fisher 344 animal model of aging. These studies attempted to identify relationships between insulin receptor signaling, neuronal gene expression, glucose metabolism, and calcium homeostasis in the hippocampus using either expression of a constitutively active human insulin receptor or administration of intranasal insulin. The following dissertation summarizes this work and provides valuable insights into the potential pathways mediating these relationships. Of note, intranasal studies reported that insulin is able to significantly alter gene expression patterns in the hippocampus of both young and aged rats following chronic, repeated exposure to the ligand. In cell culture, constitutive insulin signaling correlated with significantly elevated neuronal glucose uptake and utilization, as well as with significant alterations in the overall expression and localization of the neuron-specific glucose transporter 3. Interestingly, continued activity of the insulin receptor did not appear to alter voltage-gated calcium channels in hippocampal neurons despite prior evidence of the ligand’s role in other calcium-related processes. The results reported in this manuscript suggest that in the brain, insulin may be involved in a myriad of complex and dynamic events dependent on numerous variables, such as age, length of the exposure, and/or the insulin formulation used. Nevertheless, this work highlights the validity of using insulin to ameliorate age-related cognitive decline and supports the need for further studies exploring alternative approaches to enhance insulin receptor signaling in the brain

Data analysis of the LPSP experiment on OSO-8

The first and statistically most reliable step in the data analysis - the computation of the vertical phase lag between photospheric and chromospheric oscillations - was completed. Unfortunately, the error associated with this calculated phase lag is so great that the result has no physical significance. Since the subsequent data analysis that was originally planned would have much larger associated errors, it was concluded that the data available is insufficient to allow any meaningful results to be derived. Accordingly, the project was terminated. The reasons for the failure of the data are discussed. There are two basic reasons for this failure; (1) the very low signal to noise ratio of the raw data, and (1) the small statistical sample that resulted from the very small number of usable orbits. The final phase of data analysis is described. Finally, some comments and recommendations of a general nature are made concerning this entire contract effort. It is hoped that at least some lessons can be learned from this particular Guest Investigator project, so that future Guest Investigator programs can be pursued more effectively, and with less risk

The role of collider bias in understanding statistics on racially biased policing

7 pages, 5 figuresContradictory conclusions have been made about whether unarmed blacks are more likely to be shot by police than unarmed whites using the same data. The problem is that, by relying only on data of 'police encounters', there is the possibility that genuine bias can be hidden. We provide a causal Bayesian network model to explain this bias, which is called collider bias or Berkson's paradox, and show how the different conclusions arise from the same model and data. We also show that causal Bayesian networks provide the ideal formalism for considering alternative hypotheses and explanations of bias