The Omega-6 and Omega-3 Polyunsaturated Fatty Acids and Modifiable Breast Cancer Risk Factors

Experimental evidence suggests that omega-6 (n-6) fatty acids have mammary tumor promoting effects whereas omega-3 (n-3) fatty acids inhibit tumor growth. These two families of fatty acids may influence breast cancer development by impacting prostaglandin E2 (PGE2) formation and consequently estradiol synthesis. Whether this effect on estrogen production can be observed in the circulation or in breast tissue, as reflected on a mammogram, is unknown. Therefore, using fatty acids in erythrocytes as a biomarker of recent dietary intake, we sought to establish the relationship between the n-6 and n-3 fatty acids with both serum estradiol and mammographic breast density, two well-established modifiable breast cancer risk factors. We hypothesized that n-6 fatty acids are positively related and n-3 fatty acids negatively related to both risk factors. Nonsteroidal anti-inflammatory drugs (NSAIDs) also inhibit PGE2 formation, therefore we further hypothesized that estradiol levels would be lower among NSAID users. NSAID data was not available at the time of mammogram; hence the relationship between NSAID use and mammographic density could not accurately be assessed. To test our hypotheses we conducted several investigations ancillary to the Mammograms and Masses Study (MAMS), a case control study of the determinants of mammographic breast density. Participants were eligible for this compilation of studies if they were breast cancer-free, postmenopausal and not taking exogenous hormones. We observed significantly lower levels of serum estradiol among current users of NSAIDs as compared to non-users of NSAIDs. Further, as hypothesized, estradiol concentration decreased with increasing erythrocyte composition of total n-3 fatty acids and rose with increasing erythrocyte composition of total n-6 fatty acids. However, these findings were noted only among non-users of NSAIDs and not among NSAID users. No relationship was observed between any of the n-6 or n-3 fatty acids measures and mammographic breast density. In summary, lowering consumption of n-6 fatty acids, increasing n-3 intake, or taking a NSAID may result in reduced estradiol synthesis and potentially breast cancer risk. Further research is needed to validate our results. If confirmed, these findings could have a substantial impact on public health as it could lead to the development of chemopreventive guidelines, and ultimately prevent the development of estrogen-dependent breast cancer

A Bayesian Analysis of the Correlations Among Sunspot Cycles

Sunspot numbers form a comprehensive, long-duration proxy of solar activity and have been used numerous times to empirically investigate the properties of the solar cycle. A number of correlations have been discovered over the 24 cycles for which observational records are available. Here we carry out a sophisticated statistical analysis of the sunspot record that reaffirms these correlations, and sets up an empirical predictive framework for future cycles. An advantage of our approach is that it allows for rigorous assessment of both the statistical significance of various cycle features and the uncertainty associated with predictions. We summarize the data into three sequential relations that estimate the amplitude, duration, and time of rise to maximum for any cycle, given the values from the previous cycle. We find that there is no indication of a persistence in predictive power beyond one cycle, and conclude that the dynamo does not retain memory beyond one cycle. Based on sunspot records up to October 2011, we obtain, for Cycle 24, an estimated maximum smoothed monthly sunspot number of 97 +- 15, to occur in January--February 2014 +- 6 months.Comment: Accepted for publication in Solar Physic

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research

Soil Cd, Cu, Pb and Zn contaminants around Mount Isa city, Queensland, Australia: Potential sources and risks to human health

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A framework for the implementation of new radiation therapy technologies and treatment techniques in low-income countries.

We present a practical, generic, easy-to-use framework for the implementation of new radiation therapy technologies and treatment techniques in low-income countries. The framework is intended to standardize the implementation process, reduce the effort involved in generating an implementation strategy, and provide improved patient safety by reducing the likelihood that steps are missed during the implementation process. The 10 steps in the framework provide a practical approach to implementation. The steps are, 1) Site and resource assessment, 2) Evaluation of equipment and funding, 3) Establishing timelines, 4) Defining the treatment process, 5) Equipment commissioning, 6) Training and competency assessment, 7) Prospective risk analysis, 8) System testing, 9) External dosimetric audit and incident learning, and 10) Support and follow-up. For each step, practical advice for completing the step is provided, as well as links to helpful supplementary material. An associated checklist is provided that can be used to track progress through the steps in the framework. While the emphasis of this paper is on addressing the needs of low-income countries, the concepts also apply in high-income countries