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

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

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

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Is Productivity Diverging in the EU? Evidence from 11 Member States

An argument that received a lot of attention in the political and economic discussion surrounding the recent crisis in the EU is that diverging trends in productivity across member countries will undermine the viability of the common currency. This article examines the issue of convergence in multifactor productivity using sector-level data from 11 EU Member States. A state-space model is developed and formal Bayesian model comparisons are performed to infer whether productivity is diverging, both at the aggregate level and at a sector-by-sector basis. The data point towards diverging productivity at the aggregate level, but suggest the opposite for many individual sectors

Emerging pharmacotherapy for cancer patients with cognitive dysfunction

Advances in the diagnosis and multi-modality treatment of cancer have increased survival rates for many cancer types leading to an increasing load of long-term sequelae of therapy, including that of cognitive dysfunction. The cytotoxic nature of chemotherapeutic agents may also reduce neurogenesis, a key component of the physiology of memory and cognition, with ramifications for the patient's mood and other cognition disorders. Similarly radiotherapy employed as a therapeutic or prophylactic tool in the treatment of primary or metastatic disease may significantly affect cognition. A number of emerging pharmacotherapies are under investigation for the treatment of cognitive dysfunction experienced by cancer patients. Recent data from clinical trials is reviewed involving the stimulants modafinil and methylphenidate, mood stabiliser lithium, anti-Alzheimer's drugs memantine and donepezil, as well as other agents which are currently being explored within dementia, animal, and cell culture models to evaluate their use in treating cognitive dysfunction