Playing in the dark with online games for girls

Pregnant Rapunzel Emergency is part of a series of online free games aimed at young girls (forhergames.com or babygirlgames.com), where dozens of characters from fairy tales, children’s toys and media feature in recovery settings, such as ‘Barbie flu’. The range of games available to choose from includes not only dressing, varnishing nails or tidying messy rooms, but also rather more troubling options such as extreme makeovers, losing weight, or a plethora of baby showers, cravings, hospital pregnancy checks, births (including caesarean), postnatal ironing, washing and baby care. Taking the online game Pregnant Rapunzel Emergency as an exemplar of a current digital trend, the authors explore the workings of ‘dark digital play’ from a number of perspectives – one by each named author. The game selected has (what may appear to adults) several disturbing features in that the player is invited to treat wounds of the kind of harm that might usually be associated with domestic violence towards women

Increase in mammography detected breast cancer over time at a community based regional cancer center: a longitudinal cohort study 1990–2005

Background: Coincident with the advent of mammography screening, breast carcinoma in situ has increased in the US population. Methods: We conducted a prospective cohort study of all women presenting with primary breast cancer, aged 21-94, and biopsy confirmed Stage 0-IV from 1990-2005 identified and tracked by our registry. Clinical presentation characteristics including age, race, TNM stage, family and pregnancy history, histologic type and method of detection by patient (PtD), physician (PhysD) or mammography (MgD) were chart abstracted at time of diagnosis. Cases with unknown or other method of detection (n = 84), or unusual cell types (n = 26) were removed (n = 6074). Results: From 1990 to 1998 the percentage of PtD and MgD cases was roughly equivalent. In 1999 the percentage of MgD cases increased to 56% and PtD dropped to 37%, a significant 20% differential, constant to 2005 (Pearson chi square = 120.99, p less than .001). Overall, percent TNM stage 0 (breast carcinoma in situ) cases increased after 1990, percent stage I and III cases declined, and stage II and IV cases remained constant (Pearson chi square = 218.36, p less than .001). Increase in MgD over time differed by age group with an 8.5% increase among women age 40-49 and 12% increase among women age 50-95. Women age 21-39 rarely had MgD BC. In forward stepwise logistic regression modeling, significant predictors of MgD BC by order of entry were TNM stage, age at diagnosis, diagnosis year, and race (chi square = 1867.56, p less than .001). Conclusion: In our cohort the relative proportion of mammography detected breast cancer increased over time with a higher increase among women age 50+ and an increase of breast carcinoma in situ exclusively among MgD cases. The increase among women currently targeted by mammography screening programs (age = 50) combined with an increase of breast carcinoma in situ most often detected by mammography screening indicates a possible incidence shift to lower stage breast cancer as a result of mammographic detection.Kaplan Research Fun

Objective quantification of nanoscale protein distributions

Nanoscale distribution of molecules within small subcellular compartments of neurons critically influences their functional roles. Although, numerous ways of analyzing the spatial arrangement of proteins have been described, a thorough comparison of their effectiveness is missing. Here we present an open source software, GoldExt, with a plethora of measures for quantification of the nanoscale distribution of proteins in subcellular compartments (e.g. synapses) of nerve cells. First, we compared the ability of five different measures to distinguish artificial uniform and clustered patterns from random point patterns. Then, the performance of a set of clustering algorithms was evaluated on simulated datasets with predefined number of clusters. Finally, we applied the best performing methods to experimental data, and analyzed the nanoscale distribution of different pre- and postsynaptic proteins, revealing random, uniform and clustered sub-synaptic distribution patterns. Our results reveal that application of a single measure is sufficient to distinguish between different distributions

Trapping virtual pores by crystal retro-engineering

Stable guest-free porous molecular crystals are uncommon. By contrast, organic molecular crystals with guest-occupied cavities are frequently observed, but these cavities tend to be unstable and collapse on removal of the guests—this feature has been referred to as ‘virtual porosity’. Here, we show how we have trapped the virtual porosity in an unstable low-density organic molecular crystal by introducing a second molecule that matches the size and shape of the unstable voids. We call this strategy ‘retro-engineering’ because it parallels organic retrosynthetic analysis, and it allows the metastable two-dimensional hexagonal pore structure in an organic solvate to be trapped in a binary cocrystal. Unlike the crystal with virtual porosity, the cocrystal material remains single crystalline and porous after removal of guests by heating

Experimental Microbial Evolution of Extremophiles

Experimental microbial evolutions (EME) involves studying closely a microbial population after it has been through a large number of generations under controlled conditions (Kussell 2013). Adaptive laboratory evolution (ALE) selects for fitness under experimentally imposed conditions (Bennett and Hughes 2009; Dragosits and Mattanovich 2013). However, experimental evolution studies focusing on the contributions of genetic drift and natural mutation rates to evolution are conducted under non-selective conditions to avoid changes imposed by selection (Hindré et al. 2012). To understand the application of experimental evolutionary methods to extremophiles it is essential to consider the recent growth in this field over the last decade using model non-extremophilic microorganisms. This growth reflects both a greater appreciation of the power of experimental evolution for testing evolutionary hypotheses and, especially recently, the new power of genomic methods for analyzing changes in experimentally evolved lineages. Since many crucial processes are driven by microorganisms in nature, it is essential to understand and appreciate how microbial communities function, particularly with relevance to selection. However, many theories developed to understand microbial ecological patterns focus on the distribution and the structure of diversity within a microbial population comprised of single species (Prosser et al. 2007). Therefore an understanding of the concept of species is needed. A common definition of species using a genetic concept is a group of interbreeding individuals that is isolated from other such groups by barriers of recombination (Prosser et al. 2007). An alternative ecological species concept defines a species as set of individuals that can be considered identical in all relevant ecological traits (Cohan 2001). This is particularly important because of the abundance and deep phylogenetic complexity of microbial communities. Cohan postulated that “bacteria occupy discrete niches and that periodic selection will purge genetic variation within each niche without preventing divergence between the inhabitants of different niches”. The importance of gene exchange mechanisms likely in bacteria and archaea and therefore extremophiles, arises from the fact that their genomes are divided into two distinct parts, the core genome and the accessory genome (Cohan 2001). The core genome consists of genes that are crucial for the functioning of an organism and the accessory genome consists of genes that are capable of adapting to the changing ecosystem through gain and loss of function. Strains that belong to the same species can differ in the composition of accessory genes and therefore their capability to adapt to changing ecosystems (Cohan 2001; Tettelin et al. 2005; Gill et al. 2005). Additional ecological diversity exists in plasmids, transposons and pathogenicity islands as they can be easily shared in a favorable environment but still be absent in the same species found elsewhere (Wertz et al. 2003). This poses a major challenge for studying ALE and community microbial ecology indicating a continued need to develop a fitting theory that connects the fluid nature of microbial communities to their ecology (Wertz et al. 2003; Coleman et al. 2006). Understanding the nature and contribution of different processes that determine the frequencies of genes in any population is the biggest concern in population and evolutionary genetics (Prosser et al. 2007) and it is critical for an understanding of experimental evolution

Mesoscale Eddies Are Oases for Higher Trophic Marine Life

Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur

A statistical framework for cross-tissue transcriptome-wide association analysis

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene–trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies