The framing of options for retirement: Experimental tests for policy. ESRI WP604, December 2018

We hypothesise and confirm a substantial framing effect in relation to whether people opt for an annuity on retirement. Two laboratory experiments were conducted in collaboration with a national pensions regulator. Individuals demanded a higher annuity rate when pensions were initially conceived of as an accumulated lump sum – a “nest egg” or “pension pot” – than when they were initially conceived of as retirement income. The effect was recorded using both a matching and a choice procedure. Effect sizes implied more than a doubling of demand for annuities at market rates. While mindful of the need for caution in generalising from hypothetical laboratory studies, the findings have potentially strong policy implications. The framing of pension products in marketing materials and disclosures may have substantial effects on financial risks borne in later life

Second-generation p-values: improved rigor, reproducibility, & transparency in statistical analyses

Verifying that a statistically significant result is scientifically meaningful is not only good scientific practice, it is a natural way to control the Type I error rate. Here we introduce a novel extension of the p-value - a second-generation p-value - that formally accounts for scientific relevance and leverages this natural Type I Error control. The approach relies on a pre-specified interval null hypothesis that represents the collection of effect sizes that are scientifically uninteresting or are practically null. The second-generation p-value is the proportion of data-supported hypotheses that are also null hypotheses. As such, second-generation p-values indicate when the data are compatible with null hypotheses, or with alternative hypotheses, or when the data are inconclusive. Moreover, second-generation p-values provide a proper scientific adjustment for multiple comparisons and reduce false discovery rates. This is an advance for environments rich in data, where traditional p-value adjustments are needlessly punitive. Second-generation p-values promote transparency, rigor and reproducibility of scientific results by a priori specifying which candidate hypotheses are practically meaningful and by providing a more reliable statistical summary of when the data are compatible with alternative or null hypotheses.Comment: 29 pages, 29 page Supplemen

Recent advances in the use of metformin: Can treating diabetes prevent breast cancer?

© 2015 Diana Hatoum and Eileen M. McGowan. There is substantial epidemiological evidence pointing to an increased incidence of breast cancer and morbidity in obese, prediabetic, and diabetic patients. In vitro studies strongly support metformin, a diabetic medication, in breast cancer therapy. Although metformin has been heralded as an exciting new breast cancer treatment, the principal consideration is whether metformin can be used as a generic treatment for all breast cancer types. Importantly, will metformin be useful as an inexpensive therapy for patients with comorbidity of diabetes and breast cancer? In general, meta-analyses of clinical trial data from retrospective studies in which metformin treatment has been used for patients with diabetes and breast cancer have a positive trend; nevertheless, the supporting clinical data outcomes remain inconclusive. The heterogeneity of breast cancer, confounded by comorbidity of disease in the elderly population, makes it difficult to determine the actual benefits of metformin therapy. Despite the questionable evidence available from observational clinical studies and meta-analyses, randomized phases I-III clinical trials are ongoing to test the efficacy of metformin for breast cancer. This special issue review will focus on recent research, highlighting in vitro research and retrospective observational clinical studies and current clinical trials on metformin action in breast cancer

Utilization of the Building-Block Approach in Structural Mechanics Research

In the last 20 years NASA has worked in collaboration with industry to develop enabling technologies needed to make aircraft safer and more affordable, extend their lifetime, improve their reliability, better understand their behavior, and reduce their weight. To support these efforts, research programs starting with ideas and culminating in full-scale structural testing were conducted at the NASA Langley Research Center. Each program contained development efforts that (a) started with selecting the material system and manufacturing approach; (b) moved on to experimentation and analysis of small samples to characterize the system and quantify behavior in the presence of defects like damage and imperfections; (c) progressed on to examining larger structures to examine buckling behavior, combined loadings, and built-up structures; and (d) finally moved to complicated subcomponents and full-scale components. Each step along the way was supported by detailed analysis, including tool development, to prove that the behavior of these structures was well-understood and predictable. This approach for developing technology became known as the "building-block" approach. In the Advanced Composites Technology Program and the High Speed Research Program the building-block approach was used to develop a true understanding of the response of the structures involved through experimentation and analysis. The philosophy that if the structural response couldn't be accurately predicted, it wasn't really understood, was critical to the progression of these programs. To this end, analytical techniques including closed-form and finite elements were employed and experimentation used to verify assumptions at each step along the way. This paper presents a discussion of the utilization of the building-block approach described previously in structural mechanics research and development programs at NASA Langley Research Center. Specific examples that illustrate the use of this approach are included from recent research and development programs for both subsonic and supersonic transports

Good guy or bad guy? The duality of wild-type p53 in hormone-dependent breast cancer origin, treatment, and recurrence

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. “Lactation is at one point perilously near becoming a cancerous process if it is at all arrested”, Beatson, 1896. Most breast cancers arise from the milk-producing cells that are characterized by aberrant cellular, molecular, and epigenetic translation. By understanding the underlying molecular disruptions leading to the origin of cancer, we might be able to design novel strategies for more efficacious treatments or, ambitiously, divert the cancerous process. It is an established reality that full-term pregnancy in a young woman provides a lifetime reduction in breast cancer risk, whereas delay in full-term pregnancy increases short-term breast cancer risk and the probability of latent breast cancer development. Hormonal activation of the p53 protein (encode by the TP53 gene) in the mammary gland at a critical time in pregnancy has been identified as one of the most important determinants of whether the mammary gland develops latent breast cancer. This review discusses what is known about the protective influence of female hormones in young parous women, with a specific focus on the opportune role of wild-type p53 reprogramming in mammary cell differentiation. The importance of p53 as a protector or perpetrator in hormone-dependent breast cancer, resistance to treatment, and recurrence is also explored

Annexin/S100A protein family regulation through p14ARF-p53 activation: A role in cell survival and predicting treatment outcomes in breast cancer

© 2017 Hatoum et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The annexin family and S100A associated proteins are important regulators of diverse calcium- dependent cellular processes including cell division, growth regulation and apoptosis. Dysfunction of individual annexin and S100A proteins is associated with cancer progression, metastasis and cancer drug resistance. This manuscript describes the novel finding of differential regulation of the annexin and S100A family of proteins by activation of p53 in breast cancer cells. Additionally, the observed differential regulation is found to be beneficial to the survival of breast cancer cells and to influence treatment efficacy. We have used unbiased, quantitative proteomics to determine the proteomic changes occurring post p14ARF-p53 activation in estrogen receptor (ER) breast cancer cells. In this report we identified differential regulation of the annexin/S100A family, through unique peptide recognition at the N-terminal regions, demonstrating p14ARF-p53 is a central orchestrator of the annexin/S100A family of calcium regulators in favor of pro-survival functions in the breast cancer cell. This regulation was found to be cell-type specific. Retrospective human breast cancer studies have demonstrated that tumors with functional wild type p53 (p53wt) respond poorly to some chemotherapy agents compared to tumors with a non-functional p53. Given that modulation of calcium signaling has been demonstrated to change sensitivity of chemotherapeutic agents to apoptotic signals, in principle, we explored the paradigm of how p53 modulation of calcium regulators in ER+ breast cancer patients impacts and influences therapeutic outcomes

Applying economic principles to health care.

Applying economic thinking to an understanding of resource use in patient care is challenging given the complexities of delivering health care in a hospital. Health-care markets lack the characteristics needed to determine a "market" price that reflects the economic value of resources used. However, resource allocation in a hospital can be analyzed by using production theory to determine efficient resource use. The information provided by hospital epidemiologists is critical to understanding health-care production processes used by a hospital and developing economic incentives to promote antibiotic effectiveness and infection control