Privileged Pedagogy, Vulnerable Voice: Opening Feminist Doors in the Communication Classroom

This interview study analyzes 22 communication scholars’ experiences of teaching about feminism. Beyond questioning understandings of feminism in the communication classroom, a theory of privileged vulnerability emerged regarding the privilege of teaching about feminism and the vulnerability we--as self-identified feminist educators--embody via this privilege. Implications include recognizing our privileges and vulnerabilities, as well as how they relate to student interactions, to enact a reflexive, embodied pedagogical praxis

Air pollution modelling for birth cohorts: a time-space regression model

To investigate air pollution effects during pregnancy or in the first weeks of life, models are needed that capture both the spatial and temporal variability of air pollution exposures.; We developed a time-space exposure model for ambient NO2 concentrations in Bern, Switzerland. We used NO2 data from passive monitoring conducted between 1998 and 2009: 101 rural sites (24,499 biweekly measurements) and 45 urban sites (4350 monthly measurements). We evaluated spatial predictors (land use; roads; traffic; population; annual NO2 from a dispersion model) and temporal predictors (meteorological conditions; NO2 from continuous monitoring station). Separate rural and urban models were developed by multivariable regression techniques. We performed ten-fold internal cross-validation, and an external validation using 57 NO2 passive measurements obtained at study participant's homes.; Traffic related explanatory variables and fixed site NO2 measurements were the most relevant predictors in both models. The coefficient of determination (R(2)) for the log transformed models were 0.63 (rural) and 0.54 (urban); cross-validation R(2)s were unchanged indicating robust coefficient estimates. External validation showed R(2)s of 0.54 (rural) and 0.67 (urban).; This approach is suitable for air pollution exposure prediction in epidemiologic research with time-vulnerable health effects such as those occurring during pregnancy or in the first weeks of life

Striatal Dopamine and Norepinephrine Levels in Conjunction with OCD-like Behaviors in a Novel Animal Model of Obsessive-Compulsive Disorder

This study evaluated behaviors and monoamine levels of the neonatal clomipramine (neoCLOM) model of Obsessive Compulsive Disorder (OCD) in male and female rats (36 of each). Subjects were injected with 15 mg/kg of the serotonin-norepinephrine uptake inhibitor clomipramine during a developmentally sensitive period. A unique combination of Hole Board (HB) and Elevated Plus Maze (EPM) apparatuses was used to evaluate compulsiveness and anxiety. There was a significant effect of Treatment in the HB. Male neoCLOMs had increased hole poke and repeats versus control male neoSALs. In contrast, there was a significant effect of Sex in the EPM. Female neoCLOMs spent more time in open arms than male neoCLOMs. HB and EPM behaviors did not correlate for any group. Serotonin (5-HT), dopamine (DA), and norepinephrine (NE) levels in post mortem tissue homogenates from the hypothalamus and amygdala were analyzed using High Performance Liquid Chromatography. There were significant effects of Treatment and Sex. Neurochemical abnormalities reflect monoamine dysfunction in OCD patients. Results support some aspects of the face and construct validity of the model. Further research is needed to evaluate the model\u27s predictive validity, sensitivity to sex differences, and potential usefulness in identification of new treatment methods for OCD patients.https://orb.binghamton.edu/research_days_posters_spring2020/1004/thumbnail.jp

Blood and alveolar lymphocyte subsets in pulmonary cytomegalovirus infection after lung transplantation

BACKGROUND: Cytomegalovirus (CMV) pneumonitis has been shown to be associated with lymphocytic alveolitis after lung transplantation. In the present study, we investigated a series of bronchoalveolar (BAL) and blood samples, collected in the absence of rejection or acute infectious episodes. in order -1: to evaluate intra-alveolar cell population changes concomitant with CMV replication and -2: to reappraise the value of cell population analysis in the management of patients after lung transplantation. METHODS: We used flow cytometry to investigate modifications of lymphocyte subpopulations related to pulmonary cytomegalovirus infections in blood and BAL samples from a series of 13 lung transplant recipients. After exclusion of samples obtained during pulmonary rejection, bronchiolitis obliterans or acute bacterial infection, 48 blood and BAL samples were retained for analysis: 17 were CMV positive by shell-vial assay and 31 were CMV negative in blood and BAL. RESULTS: Our results demonstrate that pulmonary CMV infection is associated with a significant increase in the total lymphocyte population in BAL samples, but with minor modifications of the various lymphocyte subpopulations and a significantly higher absolute number of B lymphocytes in blood samples. CONCLUSIONS: Cytomegalovirus pulmonary infection is accompanied by only minor changes in BAL lymphocyte subpopulations. The study of BAL lymphocyte subpopulations therefore appears to be of limited clinical value in the diagnosis of pulmonary CMV infection. However, increased blood B-lymphocytes seems to be a clinical feature associated with CMV infection

The Reference Ability Neural Network Study: Motivation, Design, and Initial Feasibility Analyses

We introduce and describe the Reference Ability Neural Network Study and provide initial feasibility data. Based on analyses of large test batteries administered to individuals ranging from young to old, four latent variables, or reference abilities (RAs) that capture the majority of the variance in age-related cognitive change have been identified: episodic memory, fluid reasoning, perceptual speed, and vocabulary. We aim to determine whether spatial fMRI networks can be derived that are uniquely associated with the performance of each reference ability. We plan to image 375 healthy adults (50 per decade from age 20 to 50; 75 per decade from age 50 to 80) while performing a set of 12 cognitive tasks. Data on 174 participants are reported here. Three tasks were grouped a priori into each of the four reference ability domains. We first assessed to what extent both cognitive task scores and activation patterns readily show convergent and discriminant validity, i.e. increased similarity between tasks within the same domain and decreased similarity between tasks between domains, respectively. Block-based time-series analysis of each individual task was conducted for each participant via general linear modeling. We partialled activation common to all tasks out of the imaging data. For both test scores and activation topographies, we then calculated correlations for each of 66 possible pairings of tasks, and compared the magnitude of correlation of tasks within reference ability domains to that of tasks between domains. For the behavioral data, globally there were significantly stronger inter-task correlations within than between domains. When examining individual abilities, 3 of the domains also met these criteria but memory reached only borderline significance. Overall there was greater topographic similarity within reference abilities than between them (p<0.0001), but when examined individually, statistical significance was reached only for episodic memory and perceptual speed. We then turned to a multivariate technique, linear indicator regression analysis, to derive four unique linear combinations of Principal Components (PC) of imaging data that were associated with each RA. We investigated the ability of the identified PCs to predict the reference domain associated with the activation of individual subjects for individual tasks. Median accuracy rates for associating component task activation with a particular reference ability were quite good: memory: 82%; reasoning: 87%; speed: 84%; vocabulary: 77%. These results demonstrate that even using basic GLM analysis, the topography of activation of tasks within a domain is more similar than tasks between domains. The follow-up regression analyses suggest that all tasks with each RA rely on a common network, unique to that RA. Our ultimate goal is to better characterize these RA neural networks and then study how their expression changes across the age span. Our hope is that by focusing on these networks associated with key features of cognitive aging, as opposed to task-related activation associated with individual tasks, we will be able to advance our knowledge regarding the key brain changes that underlie cognitive aging

Anatomy-Aware Inference of the 3D Standing Spine Posture from 2D Radiographs

An important factor for the development of spinal degeneration, pain and the outcome of spinal surgery is known to be the balance of the spine. It must be analyzed in an upright, standing position to ensure physiological loading conditions and visualize load-dependent deformations. Despite the complex 3D shape of the spine, this analysis is currently performed using 2D radiographs, as all frequently used 3D imaging techniques require the patient to be scanned in a prone position. To overcome this limitation, we propose a deep neural network to reconstruct the 3D spinal pose in an upright standing position, loaded naturally. Specifically, we propose a novel neural network architecture, which takes orthogonal 2D radiographs and infers the spine’s 3D posture using vertebral shape priors. In this work, we define vertebral shape priors using an atlas and a spine shape prior, incorporating both into our proposed network architecture. We validate our architecture on digitally reconstructed radiographs, achieving a 3D reconstruction Dice of 0.95, indicating an almost perfect 2D-to-3D domain translation. Validating the reconstruction accuracy of a 3D standing spine on real data is infeasible due to the lack of a valid ground truth. Hence, we design a novel experiment for this purpose, using an orientation invariant distance metric, to evaluate our model’s ability to synthesize full-3D, upright, and patient-specific spine models. We compare the synthesized spine shapes from clinical upright standing radiographs to the same patient’s 3D spinal posture in the prone position from CT

Making Cognitive Latent Variables Manifest: Distinct Neural Networks for Fluid Reasoning and Processing Speed

Cognitive psychologists posit several specific cognitive abilities that are measured with sets of cognitive tasks. Tasks that purportedly tap a specific underlying cognitive ability are strongly correlated with one another, whereas performances on tasks that tap different cognitive abilities are less strongly correlated. For these reasons, latent variables are often considered optimal for describing individual differences in cognitive abilities. Although latent variables cannot be directly observed, all cognitive tasks representing a specific latent ability should have a common neural underpinning. Here, we show that cognitive tasks representing one ability (i.e., either perceptual speed or fluid reasoning) had a neural activation pattern distinct from that of tasks in the other ability. One hundred six participants between the ages of 20 and 77 years were imaged in an fMRI scanner while performing six cognitive tasks, three representing each cognitive ability. Consistent with prior research, behavioral performance on these six tasks clustered into the two abilities based on their patterns of individual differences and tasks postulated to represent one ability showed higher similarity across individuals than tasks postulated to represent a different ability. This finding was extended in the current report to the spatial resemblance of the task-related activation patterns: The topographic similarity of the mean activation maps for tasks postulated to reflect the same reference ability was higher than for tasks postulated to reflect a different reference ability. Furthermore, for any task pairing, behavioral and topographic similarities of underlying activation patterns are strongly linked. These findings suggest that differences in the strengths of correlations between various cognitive tasks may be because of the degree of overlap in the neural structures that are active when the tasks are being performed. Thus, the latent variable postulated to account for correlations at a behavioral level may reflect topographic similarities in the neural activation across different brain regions

Asthma Phenotypes in Childhood

INTRODUCTION: Asthma is no longer thought of as a single disease, but rather a collection of varying symptoms expressing different disease patterns. One of the ongoing challenges is understanding the underlying pathophysiological mechanisms that may be responsible for the varying responses to treatment. Areas Covered: This review provides an overview of our current understanding of the asthma phenotype concept in childhood and describes key findings from both conventional and data-driven methods. Expert Commentary: With the vast amounts of data generated from cohorts, there is hope that we can elucidate distinct pathophysiological mechanisms, or endotypes. In return, this would lead to better patient stratification and disease management, thereby providing true personalised medicine

Predatory journals and their practices present a conundrum for systematic reviewers and evidence synthesisers of health research: A qualitative descriptive study

Predatory journals are a blemish on scholarly publishing and academia and the studies published within them are more likely to contain data that is false. The inclusion of studies from predatory journals in evidence syntheses is potentially problematic due to this propensity for false data to be included. To date, there has been little exploration of the opinions and experiences of evidence synthesisers when dealing with predatory journals in the conduct of their evidence synthesis. In this paper, the thoughts, opinions, and attitudes of evidence synthesisers towards predatory journals and the inclusion of studies published within these journals in evidence syntheses were sought. Focus groups were held with participants who were experienced evidence synthesisers from JBI (previously the Joanna Briggs Institute) collaboration. Utilising qualitative content analysis, two generic categories were identified: predatory journals within evidence synthesis, and predatory journals within academia. Our findings suggest that evidence synthesisers believe predatory journals are hard to identify and that there is no current consensus on the management of these studies if they have been included in an evidence synthesis. There is a critical need for further research, education, guidance, and development of clear processes to assist evidence synthesisers in the management of studies from predatory journals.</p