217 research outputs found

    The Places We Called Home

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    An excerpt from a novel-in-progress following the lives of three related women, told via interconnected chapters. This thesis represents the stories of two women: Esther and Robin. Borrowing the technique of memoir to tell an account of their lives in the genre of fictional autobiography, these stories are finally being shared in effort to recast societal narratives and reveal empowerment in the unlikeliest places

    Investing in Rural Mental Health: An Approach to Increasing Access to Mental Health Professionals and Services

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    Farmers and rural residents in greater Minnesota are often overlooked relating to mental health services. Minnesota needs to focus on an approach to increase accessible mental health services in rural communities. The model for delivering mental health services has often been a one-size-fits-all approach without understanding the unique barriers, cultures, and strengths rural communities offer

    Age-Related Changes in Perirhinal Cortex Sensitivity to Configuration and Part Familiarity and Connectivity to Visual Cortex

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    The perirhinal cortex (PRC) is a medial temporal lobe (MTL) structure known to be involved in assessing whether an object is familiar (i.e., meaningful) or novel. Recent evidence shows that the PRC is sensitive to the familiarity of both whole object configurations and their parts, and suggests the PRC may modulate part familiarity responses in V2. Here, using functional magnetic resonance imaging (fMRI), we investigated age-related decline in the PRC’s sensitivity to part/configuration familiarity and assessed its functional connectivity to visual cortex in young and older adults. Participants categorized peripherally presented silhouettes as familiar (“real-world”) or novel. Part/configuration familiarity was manipulated via three silhouette configurations: Familiar (parts/configurations familiar), Control Novel (parts/configurations novel), and Part-Rearranged Novel (parts familiar, configurations novel). “Real-world” judgments were less accurate than “novel” judgments, although accuracy did not differ between age groups. The fMRI data revealed differential neural activity, however: In young adults, a linear pattern of activation was observed in left hemisphere (LH) PRC, with Familiar > Control Novel > Part-Rearranged Novel. Older adults did not show this pattern, indicating age-related decline in the PRC’s sensitivity to part/configuration familiarity. A functional connectivity analysis revealed a significant coupling between the PRC and V2 in the LH in young adults only. Older adults showed a linear pattern of activation in the temporopolar cortex (TPC), but no evidence of TPC-V2 connectivity. This is the first study to demonstrate age-related decline in the PRC’s representations of part/configuration familiarity and its covariance with visual cortex

    Evaluating PSU\u27s Community Forests: Langdon Woods and Fox Park

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    Langdon Woods and Fox Park are two community forests located on the Plymouth State University campus which provide numerous ecosystem services for students and residents. The goal of this project is to evaluate these services and propose future courses of action which will improve and protect these areas. We are also working with the ES&P Seminar class to achieve Tree Campus USA status for PSU. Langdon Woods borders the Baker River and is located on its floodplain. This area has walking and biking trails and is used by a variety of PSU’s ES&P and Adventure Education classes. We will examine the possibility of putting Langdon Woods into a conservation easement. We will also work with Angel Ekstrom, who has proposed a cluster project to further develop mountain biking trails in Langdon Woods and Fox Park. Our group will utilize both iTree canopy and iTree design to get an idea of the tree species composition, canopy cover, potential economic value, etc. Also, we will work in GIS to develop analyze these areas and produce maps. We have access to the wildlife management plan and will use this to evaluate the animal species present and their conservation status

    Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

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    <div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div

    Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.

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    It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.We thank the two anonymous reviewers for their constructive comments. This research was supported by the National Institutes of Health (NIH) grant R01CA169122; P.W. was supported by NIH grants R01HL116720 and R21HL126032. S.H.O. was supported by NIH grant P30CA008748. R.E.N. and the Queensland Pancreatic Cancer Study were funded by the Australian National Health and Medical Research Council. The authors thank Ms. Jessica Swann and the National Institute of Statistical Sciences writing workshop for editorial assistance and suggestions. The authors acknowledge the Texas Advanced Computing Center at The University of Texas at Austin for providing computing resources. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. The authors declare that there is no conflict of interest
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