Policies and practices of L.G.B.T. friendly institutions to support students who are attracted to more than one gender

Within the United States, the number of "out" Lesbian, Gay, and Bisexual (LGB) individuals attending a college or university is on the rise (Rosario, Schrimshaw, Hunter & Braun, 2006). With this increase, the new and/or different ways that lesbian and gay individuals can present and express their sexual orientation has also risen. For example, many college students now identify as pansexual, sapiosexual, and other identities that are not bound within the gender binary and preconceived sexual orientations. These individuals often experience marginalization, not only from the heterosexual majority, but from their homosexual counterparts as well. Forms of institutionalized support for lesbian and gay students have also continued to rise, but evidence of support for emergent LGB identities is not as evident in the literature (Fine, 2012; Sanlo, 2000). This study examined U.S. colleges and universities that have been identified as leaders in the LGB student support field and investigated how they develop policy and provide services and support for those individuals who identify on the LGB spectrum, but not as lesbian or gay. The research questions that framed this research were as follows: (a) What policies have the administrations at these institutions enacted to support students who are attracted to more than one gender? (b) What practices have the administrations at these institutions employed to support students who are attracted to more than one gender? and (c) How do the physical, aggregate, organizational, and constructed dimensions of involvement impact the ways in which institutions are able to support students who are attracted to more than one gender? This research used a case-study tradition with the researcher gathering data from eight US colleges/universities via interviews with institutional professionals and examination of existing institutional documents such as the website, meeting agendas and minutes. Three key findings emerged. First, inclusive LGB programming is favored by university programs serving the LGB population over targeted programming for students who are attracted to more than one gender. Second, generalizable LGBT policies are chosen more often than policies designed for specific identities. Finally, physical location of institutions, layout and flexibility of LGBT centers, availability and visibility of professional staff members, and the ability for a student to become involved with institution/LGBT center are important components to supporting individuals who are attracted to more than one gender. In considering these findings, the researcher offers three main implications. First, assessment of programs and policies designed to support individuals who are attracted to more than one gender should occur on a regular basis. Second, institutions may want to examine the language used within programs and policies to ensure that constituents are truly represented. Third, practitioners may want to use a critical eye when developing programming to ensure that it is supported by institutional policy. If such programming is not motivated by policy, then practitioners should be able to show a need for the programming thereby providing insight into possible gaps in student support

Behavioral effects of perinatal opioid exposure

Opioids are among the world's oldest known drugs used mostly for pain relief, but recreational use is also widespread. A particularly important problem is opioid exposure in females, as their offspring can also be affected. Adverse intrauterine and postnatal environments can affect offspring development and may lead to various disabilities later in life. It is clear that repetitive painful experiences, such as randomly occurring invasive procedures during neonatal intensive care, can permanently alter neuronal and synaptic organization and therefore later behavior. At the same time, analgesic drugs can also be harmful, inducing neuronal apoptosis or withdrawal symptoms in the neonate and behavioral alterations in adulthood. Hence, risk–benefit ratios should be taken into consideration when pain relief is required during pregnancy or in neonates. Recreational use of opioids can also alter many aspects of life. Intrauterine opioid exposure has many toxic effects, inducing poor pregnancy outcomes due to underdevelopment, but it is believed that later negative consequences are more related to environmental factors such as a chaotic lifestyle and inadequate prenatal care. One of the crucial components is maternal care, which changes profoundly in addicted mothers. In substance-dependent mothers, pre- and postnatal care has special importance, and controlled treatment with a synthetic opioid (e.g., methadone) could be beneficial. We aimed to summarize and compare human and rodent data, as it is important to close the gap between scientific knowledge and societal policies. Special emphasis is given to gender differences in the sensitivity of offspring to perinatal opioid exposure

Hepatic Adenomatosis May Mimic Metastatic Lesions of Liver With 18F-FDG PET/CT

Hepatic adenomatosis is an uncommon benign neoplasm, with the presence of multiple adenomas (generally more than 4) within the liver. A 52-yearold woman presented with multiple (>10) solid liver lesions detected with abdominal ultrasonography and verified with magnetic resonance imaging (MRI). Subsequently, F-18 FDG PET/CT demonstrated increased uptake in these lesions. Histology revealed hepatic adenomatosis. F-18 FDG PET/CT cannot reliably differentiate hepatic adenomas from malignant processes on the basis of uptake

Contrast-enhanced CT quantification of the hepatic fractional extracellular space: correlation with diffuse liver disease severity.

ObjectiveThe purpose of this study was to determine whether contrast-enhanced CT quantification of the hepatic fractional extracellular space (ECS) correlates with the severity of diffuse liver disease.Materials and methodsThe cases of 70 patients without (46 men, 24 women; mean age, 59.1 years) and 36 patients with (23 men, 13 women; mean age, 63.1 years) cirrhosis who had undergone unenhanced and 10-minute delayed phase contrast-enhanced CT were retrospectively identified. By consensus one experienced radiologist and one trainee measured the CT attenuation of the liver and aorta to estimate the fractional ECS, defined as the ratio of the difference between the attenuation of the liver on 10-minute and unenhanced images to the difference between the attenuation of the aorta on 10-minute and unenhanced images multiplied by 1 minus the hematocrit. Findings were correlated with each patient's Model of End-Stage Liver Disease (MELD) score.ResultsThe mean MELD score was higher in patients with than in those without cirrhosis (14.3 ± 7.3 versus 7.20 ± 2.4, p < 0.0001). The mean fractional ECS was significantly greater in patients with cirrhosis than in those without cirrhosis (41.0% ± 9.0% versus 23.8% ± 6.3%, p < 0.0001). The fractional ECS correlated with the MELD score (r = 0.572, p < 0.0001) and was predictive of cirrhosis with an area under the receiver operating characteristic curve of 0.953 (p < 0.0001). The sensitivity and specificity of an expanded fractional ECS greater than 30% for the prediction of cirrhosis were 92% and 83%. Multivariate linear regression revealed that the fractional ECS is complementary to the MELD score as a predictor of cirrhosis (p < 0.0001).ConclusionNoninvasive contrast-enhanced CT quantification of the fractional ECS correlates with the MELD score, an indicator of the severity of liver disease, and merits further study

Fully Automated Deep Learning System for Bone Age Assessment

Skeletal maturity progresses through discrete phases, a fact that is used routinely in pediatrics where bone age assessments (BAAs) are compared to chronological age in the evaluation of endocrine and metabolic disorders. While central to many disease evaluations, little has changed to improve the tedious process since its introduction in 1950. In this study, we propose a fully automated deep learning pipeline to segment a region of interest, standardize and preprocess input radiographs, and perform BAA. Our models use an ImageNet pretrained, fine-tuned convolutional neural network (CNN) to achieve 57.32 and 61.40% accuracies for the female and male cohorts on our held-out test images. Female test radiographs were assigned a BAA within 1 year 90.39% and within 2 years 98.11% of the time. Male test radiographs were assigned 94.18% within 1 year and 99.00% within 2 years. Using the input occlusion method, attention maps were created which reveal what features the trained model uses to perform BAA. These correspond to what human experts look at when manually performing BAA. Finally, the fully automated BAA system was deployed in the clinical environment as a decision supporting system for more accurate and efficient BAAs at much faster interpretation time (<2 s) than the conventional method