Cancer in Sexual and Gender Minorities: Role of Oncology RNs in Health Equity.

Despite comprising almost 8% of the population of the United States, sexual and gender minority (SGM) patients with cancer experience health inequities with poorer outcomes than non-SGM patients. Although sex-based guidelines.

Electrical and Low Frequency Noise Characterization of Graphene Chemical Sensor Devices Having Different Geometries.

Chemiresistive graphene sensors are promising for chemical sensing applications due to their simple device structure, high sensitivity, potential for miniaturization, low-cost, and fast response. In this work, we investigate the effect of (1) ZnO nanoparticle functionalization and (2) engineered defects onto graphene sensing channel on device resistance and low frequency electrical noise. The engineered defects of interest include 2D patterns of squares, stars, and circles and 1D patterns of slots parallel and transverse to the applied electric potential. The goal of this work is to determine which devices are best suited for chemical sensing applications. We find that, relative to pristine graphene devices, nanoparticle functionalization leads to reduced contact resistance but increased sheet resistance. In addition, functionalization lowers 1/f current noise on all but the uniform mesa device and the two devices with graphene strips parallel to carrier transport. The strongest correlations between noise and engineering defects, where normalized noise amplitude as a function of frequency f is described by a model of AN/fγ, are that γ increases with graphene area and contact area but decreases with device total perimeter, including internal features. We did not find evidence of a correlation between the scalar amplitude, AN, and the device channel geometries. In general, for a given device area, the least noise was observed on the least-etched device. These results will lead to an understanding of what features are needed to obtain the optimal device resistance and how to reduce the 1/f noise which will lead to improved sensor performance.

Primary Central Nervous System Lymphoma: Treatment and Nursing Management of Immunocompetent Patients.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare primary brain tumor. Because of its rarity and the increasing incidence rates as the U.S. population ages, it is important for nurses to understand the unique needs of patients and their caregivers during the disease continuum. OBJECTIVES: This article provides an overview of the treatment and nursing management of immunocompetent patients with PCNSL. METHODS: An extensive examination of the current literature, including incidence, diagnosis, treatment, and implications for nursing, was performed. FINDINGS: Nurses play a vital role in caring for patients with PCNSL and addressing their unique needs. Nurses should concentrate on early recognition and comprehensive management of neurologic symptoms. This includes patient and caregiver education and diligent implementation of treatment strategies, as well as maximizing quality of life.

Prediction of asthma exacerbations among children through integrating air pollution, upper atmosphere, and school health surveillances.

Climatic factors and air pollution are important in predicting asthma exacerbations among children. This study was designed to determine if a relationship exists between asthma exacerbations among elementary school children and the combined effect of daily upper atmosphere observations (temperature, relative humidity, dew point, and mixing ratio) and daily air pollution (particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone) and, if so, to predict asthma exacerbations among children using a mathematical model. Using an ecological study design, school health records of 168,825 students in elementary schools enrolled in "Health eTools for Schools" within 49 Pennsylvania counties were analyzed. Data representing asthma exacerbations were originally recorded by school nurses as the type of treatment given to a student during a clinic visit on a particular day. Daily upper atmosphere measurements from ground level to the 850-mb pressure level and air pollution measurements were obtained. A generalized estimating equation model was used to predict the occurrence of >48 asthma exacerbations, the daily mean for 2008-2010. The greatest occurrence of asthma among school children was in the fall, followed by summer, spring, and winter. Upper atmosphere temperature, dew point, mixing ratio, and six air pollutants as well as their interactions predicted the probability of asthma exacerbations occurring among children. Monitoring of upper atmosphere observation data and air pollutants over time can be a reliable means for predicting increases of asthma exacerbations among elementary school children. Such predictions could help parents and school officials implement effective precautionary measures.