MANAGING VARIANT DISCREPANCY IN HEREDITARY CANCER: CLINICAL PRACTICE, BARRIERS, AND DESIRED RESOURCES

Variants are changes in the DNA whose phenotypic effects may or may not be definitively understood. Because variant interpretation is a complex process, sources sometimes disagree on the classification of a variant, which is called a variant discrepancy. This study aimed to determine the practice of genetic counselors regarding variant discrepancies and to identify the barriers to counseling a variant discrepancy in hereditary cancer genetic testing. This investigation was unique because it was the first to address variant discrepancies from a clinical point of view. An electronic survey was sent to genetic counselors in the NSGC Cancer Special Interest Group. The vast majority of counselors (93%) had seen a variant discrepancy in practice. The most commonly selected barriers to counseling a variant discrepancy were lack of data sharing (90%) and lack of a central database (76%). Most counselors responded that the ideal database would be owned by a non-profit (59%) and obtain information directly from laboratories (91%). When asked how they approached counseling sessions involving variant discrepancies, the free responses emphasized that counselors consider family history and psychosocial concerns, showing that genetic counselors tailored the session to each individual. Variant discrepancies are an ongoing concern for clinical cancer genetic counselors, as demonstrated by the fact that counselors desired further resources to aid in addressing variant discrepancies, including a centralized database (89%), guidelines from a major organization (88%), continuing education about the issue (74%) and functional studies (58%)

Body Satisfaction and Sex Differences in Exercise Motivations

In this study we investigated body satisfaction and sex differences in exercise motivations. We used a questionnaire that assessed the exercise motivations: stress/anxiety, health/fitness level, mood/enjoyment, and appearance/body shape. We had 198 undergraduate participants, 114 females and 84 males between the ages of 18-23 from the University of New Hampshire, Durham campus. Self-objectification is relevant in this topic because males and females feel pressures from society to obtain the “ideal body type”. We found that health/fitness goals are the primary motivators for both males and females. There were statistically significant differences between male and female exercisers desire to lose, gain weight, and be stronger. The majority of both males and females, regardless of exercise behavior, desire to have thinner bodies. The majority of exercising males report no discrepancy in their ideal and actual body types and the majority of exercising females report an ideal body type thinner than their own body

Effective affinities in microarray data

In the past couple of years several studies have shown that hybridization in Affymetrix DNA microarrays can be rather well understood on the basis of simple models of physical chemistry. In the majority of the cases a Langmuir isotherm was used to fit experimental data. Although there is a general consensus about this approach, some discrepancies between different studies are evident. For instance, some authors have fitted the hybridization affinities from the microarray fluorescent intensities, while others used affinities obtained from melting experiments in solution. The former approach yields fitted affinities that at first sight are only partially consistent with solution values. In this paper we show that this discrepancy exists only superficially: a sufficiently complete model provides effective affinities which are fully consistent with those fitted to experimental data. This link provides new insight on the relevant processes underlying the functioning of DNA microarrays.Comment: 8 pages, 6 figure

Tupleware: Redefining Modern Analytics

There is a fundamental discrepancy between the targeted and actual users of current analytics frameworks. Most systems are designed for the data and infrastructure of the Googles and Facebooks of the world---petabytes of data distributed across large cloud deployments consisting of thousands of cheap commodity machines. Yet, the vast majority of users operate clusters ranging from a few to a few dozen nodes, analyze relatively small datasets of up to a few terabytes, and perform primarily compute-intensive operations. Targeting these users fundamentally changes the way we should build analytics systems. This paper describes the design of Tupleware, a new system specifically aimed at the challenges faced by the typical user. Tupleware's architecture brings together ideas from the database, compiler, and programming languages communities to create a powerful end-to-end solution for data analysis. We propose novel techniques that consider the data, computations, and hardware together to achieve maximum performance on a case-by-case basis. Our experimental evaluation quantifies the impact of our novel techniques and shows orders of magnitude performance improvement over alternative systems

The impact of transport across the polar vortex edge on Match ozone loss estimates

The Match method for the quantification of polar chemical ozone loss is investigated mainly with respect to the impact of the transport of air masses across the vortex edge. For the winter 2002/03, we show that significant transport across the vortex edge occurred and was simulated by the Chemical Lagrangian Model of the Stratosphere. In-situ observations of inert tracers and ozone from HAGAR on the Geophysica aircraft and balloon-borne sondes, and remote observations from MIPAS on the ENVISAT satellite were reproduced well by CLaMS. The model even reproduced a small vortex remnant that remained a distinct feature until June 2003 and was also observed in-situ by a balloon-borne whole air sampler. We use this CLaMS simulation to quantify the impact of transport across the vortex edge on ozone loss estimates from the Match method. We show that a time integration of the determined vortex average ozone loss rates, as performed in Match, results in a larger ozone loss than the polar vortex average ozone loss in CLaMS. The determination of the Match ozone loss rates is also influenced by the transport of air across the vortex edge. We use the model to investigate how the sampling of the ozone sondes on which Match is based represents the vortex average ozone loss rate. Both the time integration of ozone loss and the determination of ozone loss rates for Match are evaluated using the winter 2002/2003 CLaMS simulation. These impacts can explain the majority of the differences between CLaMS and Match column ozone loss. While the investigated effects somewhat reduce the apparent discrepancy in January ozone loss rates reported earlier, a distinct discrepancy between simulations and Match remains. However, its contribution to the accumulated ozone loss over the winter is not large

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms

The $L_{\infty}$ star discrepancy is a measure for the regularity of a finite set of points taken from $[0,1)^d$. Low discrepancy point sets are highly relevant for Quasi-Monte Carlo methods in numerical integration and several other applications. Unfortunately, computing the $L_{\infty}$ star discrepancy of a given point set is known to be a hard problem, with the best exact algorithms falling short for even moderate dimensions around 8. However, despite the difficulty of finding the global maximum that defines the $L_{\infty}$ star discrepancy of the set, local evaluations at selected points are inexpensive. This makes the problem tractable by black-box optimization approaches. In this work we compare 8 popular numerical black-box optimization algorithms on the $L_{\infty}$ star discrepancy computation problem, using a wide set of instances in dimensions 2 to 15. We show that all used optimizers perform very badly on a large majority of the instances and that in many cases random search outperforms even the more sophisticated solvers. We suspect that state-of-the-art numerical black-box optimization techniques fail to capture the global structure of the problem, an important shortcoming that may guide their future development. We also provide a parallel implementation of the best-known algorithm to compute the discrepancy.Comment: To appear in the Proceedings of GECCO 202