Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers.

Applying state-of-the-art machine learning techniques to medical images requires a thorough selection and normalization of input data. One of such steps in digital mammography screening for breast cancer is the labeling and removal of special diagnostic views, in which diagnostic tools or magnification are applied to assist in assessment of suspicious initial findings. As a common task in medical informatics is prediction of disease and its stage, these special diagnostic views, which are only enriched among the cohort of diseased cases, will bias machine learning disease predictions. In order to automate this process, here, we develop a machine learning pipeline that utilizes both DICOM headers and images to predict such views in an automatic manner, allowing for their removal and the generation of unbiased datasets. We achieve AUC of 99.72% in predicting special mammogram views when combining both types of models. Finally, we apply these models to clean up a dataset of about 772,000 images with expected sensitivity of 99.0%. The pipeline presented in this paper can be applied to other datasets to obtain high-quality image sets suitable to train algorithms for disease detection

The AT(N) framework for Alzheimer\u27s disease in adults with Down syndrome

The National Institute on Aging in conjunction with the Alzheimer\u27s Association (NIA-AA) recently proposed a biological framework for defining the Alzheimer\u27s disease (AD) continuum. This new framework is based upon the key AD biomarkers (amyloid, tau, neurodegeneration, AT[N]) instead of clinical symptoms and represents the latest understanding that the pathological processes underlying AD begin decades before the manifestation of symptoms. By using these same biomarkers, individuals with Down syndrome (DS), who are genetically predisposed to developing AD, can also be placed more precisely along the AD continuum. The A/T(N) framework is therefore thought to provide an objective manner by which to select and enrich samples for clinical trials. This new framework is highly flexible and allows the addition of newly confirmed AD biomarkers into the existing AT(N) groups. As biomarkers for other pathological processes are validated, they can also be added to the AT(N) classification scheme, which will allow for better characterization and staging of AD in DS. These biological classifications can then be merged with clinical staging for an examination of factors that impact the biological and clinical progression of the disease. Here, we leverage previously published guidelines for the AT(N) framework to generate such a plan for AD among adults with DS

Lessons Learned from Conducting Volunteer-Based Urban Forest Inventories on the Gulf Coast

Volunteer-based urban forest inventories are a common activity among Extension professionals; however, project facilitators often end up duplicating mistakes experienced previously by others. This article shares lessons learned from conducting several volunteer-based urban forest inventories. The lessons revolve around the themes of volunteer recruitment, communication with the public, private property access, project scope and time line, volunteer management, and efforts to increase efficiency. Through awareness of these lessons, Extension professionals can implement and adapt our successful strategies yet not repeat our mistakes. In turn, readers will increase the likelihood of successfully developing baseline measures while engaging the public in urban forest management

Intérêt des laits fermentés chez l'enfant diarrhéique malnutri

L'objectif de cette étude était de comparer, chez des enfants diarrhéiques malnutris, l'effet thérapeutique d'un yaourt manufacturé à flore vivante et d'un lait fermenté enrichi préparé de façon artisanale (soow). De novembre 1988 à juillet 1989, 50 enfants non sevrés présentant une diarrhée aigüe associée à une malnutrition (indice poids/taille < 80 % des références NCHS) ont été admis dans l'étude; la répartition entre les groupes (soow contre yaourt) a été faite par tirage au sort et les deux groupes étaient comparables pour la réhabilitation nutritionnelle de ces enfants; le gain de poids moyen a été de 16 g/kg/j et le protocole n'a jamais dû être interrompu du fait d'une aggravation de la diarrhée ou d'une perte de poids. Sur le plan biologique, les résultats confirment l'intérêt du dosage de la transthyrétine associé à celui des protéines inflammatoires pour l'évaluation et le suivi du déficit nutritionnel. L'ensemble de ces résultats suggère que la réalimentation précoce à l'aide de laits fermentés enrichis, associée à la réhydratation orale, apparaît comme bénéfique en cas de diarrhée aiguë associée à une malnutrition. (Résumé d'auteur

Registered nurses' perceptions of factors causing stress in the intensive care environment in state hospitals

The complex environment of an intensive care unit is associated with a considerable amount of stress. Intensive care nurses are confronted daily with increasing work demands, emanating from the growing numbers of critically-ill patients; the introduction of highly sophisticated technologies in the intensive care environment; increasing competition between health care institutions; increased work loads; and limited career opportunities caused by, among other things, budget cuts by the government (Janssen, De Jonge & Bakker, 1999:1360). Research has shown that such stressors can result in mental, physical and behavioural stress reactions among nurses (Demerouti, Bakker, Nachreiner and Schaufeli, 2000:454). The objective of this study is to explore and describe registered nurses’ perceptions of factors causing stress in intensive care environments of state hospitals. The main purpose of the study is to develop guidelines for a stress management programme, to assist registered nurses to cope with the stressors in an intensive care environment. The research design is placed within a quantitative, explorative and descriptive contextual framework. Validity and reliability in testing and evaluating the research questionnaire are discussed, as well as the ethical and legal considerations relating to this research study. Findings of the research study will be utilized to assist the researcher in developing guidelines for a stress management programme to assist registered nurses in coping with stress in an intensive care environmen

Gender and the energy transition in the North: light on dark area

Energy policies assume that women and men have the same values, experiences and aspirations towards energy production and use. In other words, energy policies are gender blind – neglecting gender-based differences in perception, socialization and values. There are arguments that ignoring these differences can act as a barrier to the sustainable energy transition. How can energy policies be influenced to reflect the reality of differences? Gender budgeting has been the dominant methodology for engendering policy however in the energy sector gender audits have been tried and tested. One of the arguments for using audits is that represent a more inclusive – less technocratic – approach. This paper evaluates experiences with engendering energy policy at the level of government and organisations

Neuroinflammation and white matter alterations in obesity assessed by Diffusion Basis Spectrum Imaging

Human obesity is associated with low-grade chronic systemic inflammation, alterations in brain structure and function, and cognitive impairment. Rodent models of obesity show that high-calorie diets cause brain inflammation (neuroinflammation) in multiple regions, including the hippocampus, and impairments in hippocampal-dependent memory tasks. To determine if similar effects exist in humans with obesity, we applied Diffusion Basis Spectrum Imaging (DBSI) to evaluate neuroinflammation and axonal integrity. We examined diffusion-weighted magnetic resonance imaging (MRI) data in two independent cohorts of obese and non-obese individuals (Cohort 1: 25 obese/21 non-obese; Cohort 2: 18 obese/41 non-obese). We applied Tract-based Spatial Statistics (TBSS) to allow whole-brain white matter (WM) analyses and compare DBSI-derived isotropic and anisotropic diffusion measures between the obese and non-obese groups. In both cohorts, the obese group had significantly greater DBSI-derived restricted fraction (DBSI-RF; an indicator of neuroinflammation-related cellularity), and significantly lower DBSI-derived fiber fraction (DBSI-FF; an indicator of apparent axonal density) in several WM tracts (all correcte