Young women's use of a microbicide surrogate: The complex influence of relationship characteristics and perceived male partners' evaluations

This is the post-print version of the article. The official published version can be found at the link below.Currently in clinical trials, vaginal microbicides are proposed as a female-initiated method of sexually transmitted infection prevention. Much of microbicide acceptability research has been conducted outside of the United States and frequently without consideration of the social interaction between sex partners, ignoring the complex gender and power structures often inherent in young women’s (heterosexual) relationships. Accordingly, the purpose of this study was to build on existing microbicide research by exploring the role of male partners and relationship characteristics on young women’s use of a microbicide surrogate, an inert vaginal moisturizer (VM), in a large city in the United States. Individual semi-structured interviews were conducted with 40 young women (18–23 years old; 85% African American; 47.5% mothers) following use of the VM during coital events for a 4 week period. Overall, the results indicated that relationship dynamics and perceptions of male partners influenced VM evaluation. These two factors suggest that relationship context will need to be considered in the promotion of vaginal microbicides. The findings offer insights into how future acceptability and use of microbicides will be influenced by gendered power dynamics. The results also underscore the importance of incorporating men into microbicide promotion efforts while encouraging a dialogue that focuses attention on power inequities that can exist in heterosexual relationships. Detailed understanding of these issues is essential for successful microbicide acceptability, social marketing, education, and use.This study was funded by a grant from National Institutes of Health (NIHU19AI 31494) as well as research awards to the first author: Friends of the Kinsey Institute Research Grant Award, Indiana University’s School of HPER Graduate Student Grant-in-Aid of Research Award, William L. Yarber Sexual Health Fellowship, and the Indiana University Graduate and Professional Student Organization Research Grant

Health Status of Sand Flathead (Platycephalus bassensis), Inhabiting an Industrialised and Urbanised Embayment, Port Phillip Bay, Victoria as Measured by Biomarkers of Exposure and Effects

Port Phillip Bay, Australia, is a large semi-closed bay with over four million people living in its catchment basin. The Bay receives waters from the Yarra River which drains the city of Melbourne, as well as receiving the discharges of sewage treatment plants and petrochemical and agricultural chemicals. A 1999 study demonstrated that fish inhabiting Port Phillip Bay showed signs of effects related to pollutant exposure despite pollution management practices having been implemented for over a decade. To assess the current health status of the fish inhabiting the Bay, a follow up survey was conducted in 2015. A suite of biomarkers of exposure and effects were measured to determine the health status of Port Phillip Bay sand flathead (Platycephalus bassensis), namely ethoxyresorufin-O-deethylase (EROD) activity, polycyclic aromatic hydrocarbons (PAH) biliary metabolites, carboxylesterase activity (CbE) and DNA damage (8-oxo-dG). The reduction in EROD activity in the present study suggests a decline in the presence of EROD activity-inducing chemicals within the Bay since the 1990s. Fish collected in the most industrialised/urbanised sites did not display higher PAH metabolite levels than those in less developed areas of the Bay. Ratios of PAH biliary metabolite types were used to indicate PAH contaminant origin. Ratios indicated fish collected at Corio Bay and Hobsons Bay were subjected to increased low molecular weight hydrocarbons of petrogenic origin, likely attributed to the close proximity of these sites to oil refineries, compared to PAH biliary metabolites in fish from Geelong Arm and Mordialloc.Quantification of DNA damage indicated a localised effect of exposure to pollutants, with a 10-fold higher DNA damage level in fish sampled from the industrial site of Corio Bay relative to the less developed site of Sorrento. Overall, integration of biomarkers by multivariate analysis indicated that the health of fish collected in industrialised areas was compromised, with biologically significant biomarkers of effects (LSI, CF and DNA damage) discriminating between individuals collected in industrialised areas from observations made in fish collected in less developed areas of the Bay

Lessons Learned from Creating a Mobile Version of an Educational Board Game to Increase Situational Awareness

This paper reports on an iterative design process for a serious game, which aims to raise situational awareness among different stakeholders in a logistics value chain by introducing multi-user role-playing games. It does so in several phases: After introducing the field of logistics as a problem domain for an educational challenge, it firstly describes the design of an educational board game for the field of disruption handling in logistics processes. Secondly, it de-scribes how the board game can be realized in an open-source mobile serious games platform and identifies lessons learned based on advantages and issues found. Thirdly, it derives requirements for a re-design of the mobile game and finally draws conclusions.SALOM

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data