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Abstract Biologists represent data in visual forms, such as graphs, to aid data analysis and communication. However, students struggle to construct effective graphs. Although some studies explore these difficulties, we lack a comprehensive framework of the knowledge and skills needed to construct graphs in biology. In the present article, we describe the development of the Graph Construction Competency Model for Biology (GCCM-Bio), a framework of the components and activities associated with graph construction. We identified four broad knowledge areas for graph construction in biology: data selection, data exploration, graph assembly, and graph reflection. Under each area, we identified activities undertaken when constructing graphs of biological data and refined the GCCM-Bio through focus groups with experts in biology and statistics education. We also ran a scoping literature review to verify that these activities were represented in the graphing literature. The GCCM-Bio could support instructors, curriculum developers, and researchers when designing instruction and assessment of biology graph construction. 

There has been a growing interest in reproductive health and intimate wellbeing in Human-Computer Interaction, increasingly from an ecological perspective. Much of this work is centered around women’s experiences across diverse settings, emphasizing men’s limited engagement and need for greater participation on these topics. Our research responds to this gap by investigating cisgender men’s experiences of cultivating sexual health literacies in an urban Indian context. We leverage media probes to stimulate focus group discussions, using popular media references on men’s fertility to elicit shared reflection. Our findings uncover the role that humor and masculinity play in shaping men’s perceptions of their sexual health and how this influences their sense of agency and participation in heterosexual intimate relationships. We further discuss how technologies might be designed to support men’s participation in these relationships as supportive partners and allies. 

Interface between two immiscible electrolyte solutions (ITIES) is a powerful platform for chemical sensing and studying electron/ion transfer reactions and is typically formed between the interface of two immiscible solutions such as an oil phase and an aqueous phase. Micro/nano ITIES interface are generally formed at the tip of a borosilicate/quartz pipette, inner surface of which can be rendered hydrophobic to be filled with an organic solvent by a method called silanization. Nano/micrometer-sized electrodes are typically silanized by vapor silanization methods in which silanizing agent in vapor phase is exposed to nanopipettes. Micrometer-sized pipettes have been also silanized by directly filling liquid silanization agent, one type of liquid silanization methods, but this method has not been used at the nanoscale. Liquid silanization method allows to selectively silanize a single channel in a dual-channel pipette platform. Here, we developed the liquid silanization method for nanoscale ITIES and demonstrated that a stable cyclic voltammogram for tetrabutylammonium ion transfer across water/dichloroethane interface can be accomplished. We also presented challenges for liquid silanization at the nanoscale and strategies to overcome them. The liquid silanization methods presented here lay the foundation for future development of dual channel multi-functional probe where one channel is nanoITIES. 

Abstract Graphing is an important practice for scientists and in K-16 science curricula. Graphs can be constructed using an array of software packages as well as by hand, with pen-and-paper. However, we have an incomplete understanding of how students’ graphing practice vary by graphing environment; differences could affect how best to teach and assess graphing. Here we explore the role of two graphing environments in students’ graphing practice. We studied 43 undergraduate biology students’ graphing practice using either pen-and-paper (PP) ( n  = 21 students) or a digital graphing tool GraphSmarts (GS) ( n  = 22 students). Participants’ graphs and verbal justifications were analyzed to identify features such as the variables plotted, number of graphs created, raw data versus summarized data plotted, and graph types (e.g., scatter plot, line graph, or bar graph) as well as participants’ reasoning for their graphing choices. Several aspects of participant graphs were similar regardless of graphing environment, including plotting raw vs. summarized data, graph type, and overall graph quality, while GS participants were more likely to plot the most relevant variables. In GS, participants could easily make more graphs than in PP and this may have helped some participants show latent features of their graphing practice. Those students using PP tended to focus more on ease of constructing the graph than GS. This study illuminates how the different characteristics of the graphing environment have implications for instruction and interpretation of assessments of student graphing practices. 

ABSTRACT Many ant species grow fungus gardens that predigest food as an essential step of the ants’ nutrient uptake. These symbiotic fungus gardens have long been studied and feature a gradient of increasing substrate degradation from top to bottom. To further facilitate the study of fungus gardens and enable the understanding of the predigestion process in more detail than currently known, we applied recent mass spectrometry-based approaches and generated a three-dimensional (3D) molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments to compare with lab-maintained ecosystems. IMPORTANCE The study of complex ecosystems requires an understanding of the chemical processes involving molecules from several sources. Some of the molecules present in fungus-growing ants’ symbiotic system originate from plants. To facilitate the study of fungus gardens from a chemical perspective, we provide a molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments. 

ABSTRACT The central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance. IMPORTANCE By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE ; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/q2-deicode .