In Judgment of Victims: The Social Context of Rape

This study examines some of the linkages between the rape victims\u27 experience and community attitudes about rape, focusing on differences among three racial-ethnic groups. Public attitude data were collected from a stratified sample of 1,011 respondents; personal interviews were conducted with 335 Anglos, 336 Blacks and 340 Mexican Americans. Victim data were collected from in depth interviews with 61 female rape victims: 32 Anglos, 11 Blacks and 18 Mexican Americans. While the victim data suggest some degree of negative impact resulting from the rape experience for all victims, significant differences were found among the three racial-ethnic groups. Public attitude data suggest that public responses to rape are differentiated by certain age, sex and race-related categoric risks as well as certain attitudinal variations about sex roles. These findings are discussed in terms of how public attitudes may work to mitigate or exacerbate the negative effects of the rape experience for victims. Subsequently, an attempt is made to reconceptualize rape as an integrated composite of the public (extrinsic) and personal (intrinsic) experience of the victim

Current utility of the ankle-brachial index (ABI) in general practice: implications for its use in cardiovascular disease screening

Peripheral arterial disease (PAD) is a marker of systemic atherosclerosis and associated with a three to six fold increased risk of death from cardiovascular causes. Furthermore, it is typically asymptomatic and under-diagnosed; this has resulted in escalating calls for the instigation of Primary Care PAD screening via Ankle Brachial Index (ABI) measurement. However, there is limited evidence regarding the feasibility of this and if the requisite core skills and knowledge for such a task already exist within primary care. This study aimed to determine the current utility of ABI measurement in general practices across Wales, with consideration of the implications for its use as a cardiovascular risk screening tool

Interpersonal Hardiness as a Critical Contributing Factor to Persistence among International Women in Doctoral Programs: A Trioethnographic Study

Women in PhD programs, in particular minority and international women, are especially at risk for drop-out (Castro, Garcia, Cavazos, & Castro, 2011; Haynes et al., 2012). This initial part of a longitudinal trioethnography captures the experiences of three international women in a doctoral program, highlighting the challenges, support systems, and coping mechanisms they engage with in the process of completing their degrees. Discoveries include the identification of “Interpersonal Hardiness” as the potential vehicle which could ensure our success

Safety assessment of drotrecogin alfa (activated) in the treatment of adult patients with severe sepsis

INTRODUCTION: Drotrecogin alfa (activated; recombinant activated protein C) was shown to reduce 28-day all-cause mortality in patients with severe sepsis and to have an acceptable safety profile in 1690 patients studied in the F1K-MC-EVAD (PROWESS) trial. We analyzed all available data on the safety of treatment with drotrecogin alfa (activated) in 2786 adult patients with severe sepsis enrolled in all phase 2 and 3 clinical trials, and in an estimated 3991 patients receiving the drug in commercial use. PATIENTS AND METHOD: Mortality and safety analyses were performed on all available data from adult severe sepsis patients enrolled in seven clinical trials as of 12 April 2002. Trial-specific safety data and spontaneously reported serious adverse events from commercial use were extracted from a pharmacovigilance database. RESULTS: The 28-day mortality rate for all adult patients who received active treatment in all clinical trials was 25.3% (704/2786). Serious bleeding events during the infusion period and 28-day study period occurred in 2.8% (79/2786) and 5.3% (148/2786) of patients, respectively. Of bleeding events during the infusion period, 43% (34/79) were procedure-related. Fatal serious bleeding events during the infusion period occurred in 0.4% (12/2786) of cases. Intracranial hemorrhage (ICH) events during the infusion period and 28-day study period occurred in 0.6% (16/2786) and 1.1% (32/2786) of patients, respectively. Ten out of the 16 ICH events occurring during the study drug infusion period were associated with severe thrombocytopenia (≤ 30,000/mm(3)) and/or meningitis. Serious bleeding and ICH events spontaneously reported from commercial use (n = 3991) occurred in 0.9% and 0.2% of patients, respectively. CONCLUSION: Drotrecogin alfa (activated) significantly reduces mortality in severe sepsis. The efficacy and safety profiles of drotrecogin alfa (activated) have remained consistent over the conduct of multiple clinical trials. The most important serious adverse event associated with drotrecogin alfa (activated) treatment is bleeding. Additional clinical experience indicates that invasive procedures are associated with a substantial percentage of serious bleeding events, particularly those occurring at the start of infusion of the drug. Severe thrombocytopenia (for all serious bleeding events, including ICH) and meningitis (for ICH only) may be risk factors for serious bleeding. However, patients with severe thrombocytopenia and/or meningitis may be at greater risk for bleeding or ICH in the absence of drug therapy

Disentangled representation learning in cardiac image analysis

Typically, a medical image offers spatial information on the anatomy (and pathology) modulated by imaging specific characteristics. Many imaging modalities including Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) can be interpreted in this way. We can venture further and consider that a medical image naturally factors into some spatial factors depicting anatomy and factors that denote the imaging characteristics. Here, we explicitly learn this decomposed (disentangled) representation of imaging data, focusing in particular on cardiac images. We propose Spatial Decomposition Network (SDNet), which factorises 2D medical images into spatial anatomical factors and non-spatial modality factors. We demonstrate that this high-level representation is ideally suited for several medical image analysis tasks, such as semi-supervised segmentation, multi-task segmentation and regression, and image-to-image synthesis. Specifically, we show that our model can match the performance of fully supervised segmentation models, using only a fraction of the labelled images. Critically, we show that our factorised representation also benefits from supervision obtained either when we use auxiliary tasks to train the model in a multi-task setting (e.g. regressing to known cardiac indices), or when aggregating multimodal data from different sources (e.g. pooling together MRI and CT data). To explore the properties of the learned factorisation, we perform latent-space arithmetic and show that we can synthesise CT from MR and vice versa, by swapping the modality factors. We also demonstrate that the factor holding image specific information can be used to predict the input modality with high accuracy. Code will be made available at https://github.com/agis85/anatomy_modality_decomposition

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

The impact of beliefs about face recognition ability on memory retrieval processes in young and older adults

This study examined whether beliefs about face recognition ability differentially influence memory retrieval in older compared to young adults. Participants evaluated their ability to recognise faces and were also given information about their ability to perceive and recognise faces. The information was ostensibly based on an objective measure of their ability, but in actuality, participants had been randomly assigned the information they received (high ability, low ability or no information control). Following this information, face recognition accuracy for a set of previously studied faces was measured using a remember– know memory paradigm. Older adults rated their ability to recognise faces as poorer compared to young adults. Additionally, negative information about face recognition ability improved only older adults’ ability to recognise a previously seen face. Older adults were also found to engage in more familiarity than item-specific processing than young adults, but information about their face recognition ability did not affect face processing style. The role that older adults’ memory beliefs have in the meta-cognitive strategies they employ is discussed

In Vivo Optical Metabolic Imaging of Long-Chain Fatty Acid Uptake in Orthotopic Models of Triple-Negative Breast Cancer

Targeting a tumor’s metabolic dependencies is a clinically actionable therapeutic approach; however, identifying subtypes of tumors likely to respond remains difficult. The use of lipids as a nutrient source is of particular importance, especially in breast cancer. Imaging techniques offer the opportunity to quantify nutrient use in preclinical tumor models to guide development of new drugs that restrict uptake or utilization of these nutrients. We describe a fast and dynamic approach to image fatty acid uptake in vivo and demonstrate its relevance to study both tumor metabolic reprogramming directly, as well as the effectiveness of drugs targeting lipid metabolism. Specifically, we developed a quantitative optical approach to spatially and longitudinally map the kinetics of long-chain fatty acid uptake in in vivo murine models of breast cancer using a fluorescently labeled palmitate molecule, Bodipy FL c16. We chose intra-vital microscopy of mammary tumor windows to validate our approach in two orthotopic breast cancer models: a MYC-overexpressing, transgenic, triple-negative breast cancer (TNBC) model and a murine model of the 4T1 family. Following injection, Bodipy FL c16 fluorescence increased and reached its maximum after approximately 30 min, with the signal remaining stable during the 30–80 min post-injection period. We used the fluorescence at 60 min (Bodipy60), the mid-point in the plateau region, as a summary parameter to quantify Bodipy FL c16 fluorescence in subsequent experiments. Using our imaging platform, we observed a two- to four-fold decrease in fatty acid uptake in response to the downregulation of the MYC oncogene, consistent with findings from in vitro metabolic assays. In contrast, our imaging studies report an increase in fatty acid uptake with tumor aggressiveness (6NR, 4T07, and 4T1), and uptake was significantly decreased after treatment with a fatty acid transport inhibitor, perphenazine, in both normal mammary pads and in the most aggressive 4T1 tumor model. Our approach fills an important gap between in vitro assays providing rich metabolic information at static time points and imaging approaches visualizing metabolism in whole organs at a reduced resolution