Association of Obesity with Periodontitis, Tooth Loss and Oral Hygiene in Non-smoking Adults

Background: Periodontitis was found to be significantly related to obesity as well as the number of missing teeth and oral hygiene. However, the studies addressing these relationships often included smokers and diabetics, and none was performed in Eastern European patients. The aim of this cross-sectional study was to investigate associations between obesity and periodontitis, oral hygiene, and tooth loss in a sample of non-smoking Croatian subjects aged 31-75 years. Methods: A total of 320 patients were recruited by convenient sampling at the Dental Clinic, Clinical Hospital Centre in Rijeka, Croatia. Periodontal examination and data on tooth loss were completed in 292 subjects and each participant completed a structured written questionnaire with questions regarding oral hygiene, education, height, and weight. Periodontitis was categorized as early, moderate and advanced. In multiple regression analysis, periodontitis was used as predictor variable, and BMI, oral hygiene, tooth loss, and education level were used as dependent variables. Results: Use of interdental brushes/flossing and number of missing teeth correlated significantly with BMI, but the same could not be proven for periodontitis and frequency of tooth brushing. However, logistic regression proved that the subset of obese, poorly educated women aged 36-55 years were 5-6 times more likely to develop severe forms of periodontal disease. Conclusions: Obesity was associated with tooth loss, oral hygiene, and education level in the investigated group. BMI could not be correlated with severity of periodontal disease, except in poorly educated women aged 36-55 year

IN SEARCH OF NEURAL MECHANISMS OF MIRROR NEURON DYSFUNCTION IN SCHIZOPHRENIA: RESTING STATE FUNCTIONAL CONNECTIVITY APPROACH

It has been repeatedly shown that schizophrenia patients have immense alterations in goal-directed behaviour, social cognition, and social interactions, cognitive abilities that are presumably driven by the mirror neurons system (MNS). However, the neural bases of these deficits still remain unclear. Along with the task-related fMRI and EEG research tapping into the mirror neuron system, the characteristics of the resting state activity in the particular areas that encompass mirror neurons might be of interest as they obviously determine the baseline of the neuronal activity. Using resting state fMRI, we investigated resting state functional connectivity (FC) in four predefined brain structures, ROIs (inferior frontal gyrus, superior parietal lobule, premotor cortex and superior temporal gyrus), known for their mirror neurons activity, in 12 patients with first psychotic episode and 12 matched healthy individuals. As a specific hypothesis, based on the knowledge of the anatomical inputs of thalamus to all preselected ROIs, we have investigated the FC between thalamus and the ROIs. Of all ROIs included, seed-to-voxel connectivity analysis revealed significantly decreased FC only in left posterior superior temporal gyrus (STG) and the areas in visual cortex and cerebellum in patients as compared to controls. Using ROI-to-ROI analysis (thalamus and selected ROIs), we have found an increased FC of STG and bilateral thalamus whereas the FC of these areas was decreased in controls. Our results suggest that: (1) schizophrenia patients exhibit FC of STG which corresponds to the previously reported changes of superior temporal gyrus in schizophrenia and might contribute to the disturbances of specific functions, such as emotional processing or spatial awareness; (2) as the thalamus plays a pivotal role in the sensory gating, providing the filtering of the redundant stimulation, the observed hyperconnectivity between the thalami and the STGs in patients with schizophrenia might explain the sequential overload with sensory inputs that leads to the abnormal cognitive processing

Cardiac displacement tracking with data assimilation combining a biomechanical model and an automatic contour detection

International audienceData assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively computing adequate data-fitting term for cardiac imaging such as cine MRI. We here provide a proof-of-concept study of data assimilation based on automatic contour detection. The tissue motion simulated by the data assimilation framework is then assessed with displacements extracted from tagged MRI in six subjects, and the results illustrate the performance of the proposed method, including for circumferential displacements, which are not well extracted from cine MRI alone

Deep Learning-based Method for Fully Automatic Quantification of Left Ventricle Function from Cine MR Images: A Multivendor, Multicenter Study

Purpose: To develop a deep learning–based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods: This retrospective study included cine MRI data sets obtained from three major MRI vendors in four medical centers from 2008 to 2016. Three convolutional neural networks (CNNs) with the U-NET architecture were trained on data sets of increasing variability: (a) a single-vendor, single-center, homogeneous cohort of 100 patients (CNN1); (b) a single-vendor, multicenter, heterogeneous cohort of 200 patients (CNN2); and (c) a multivendor, multicenter, heterogeneous cohort of 400 patients (CNN3). All CNNs were tested on an independent multivendor, multicenter data set of 196 patients. CNN performance was evaluated with respect to the manual annotations from three experienced observers in terms of (a) LV detection accuracy, (b) LV segmentation accuracy, and (c) LV functional parameter accuracy. Automatic and manual results were compared with the paired Wilcoxon test, Pearson correlation, and Bland-Altman analysis. Results: CNN3 achieved the highest performance on the independent testing data set. The average perpendicular distance compared with manual analysis was 1.1 mm ± 0.3 for CNN3, compared with 1.5 mm ± 1.0 for CNN1 (P < .05) and 1.3 mm ± 0.6 for CNN2 (P < .05). The LV function parameters derived from CNN3 showed a high correlation (r2 ≥ 0.98) and agreement with those obtained by experts for data sets from different vendors and centers. Conclusion: A deep learning–based method trained on a data set with high variability can achieve fully automated and accurate cine MRI analysis on multivendor, multicenter cine MRI data

Innovative Housing Policy Tools for Local Governments in Shrinking Communities with a Large Share of Privately Owned Apartments: A Case Study of Valga, Estonia

Shrinking communities face a myriad num­ber of problems. The physical manifestation of urban shrinkage can best be noted in abandoned or underutilized properties, an oversupply or de­teriorating housing stock and inadequate aging infrastructure. These physical manifestations lead to psychological impacts of poor percep­tion of a community, lack of a sense of place, lethargic residents who lack the financial means or motivation to improve their living conditions. Planning for the regeneration and rightsizing of shrinking communities calls for intervention by government sectors. Valga is a small town in Estonia where housing vacancies, low quality of residential premises and the shortage of quality apartments are the result of decades of depop­ulation. As a result of housing privatization after the collapse of the Soviet Union, a large majori­ty of the dwellings are privately owned. Housing demolitions and revitalization are a key part of the small town’s strategy to deal with shrinkage. This paper addresses the question: in an area of urban shrinkage, what kind of housing policy can local government create in the conditions of prevailing private ownership of residential prem­ises?Drawing on a qualitative case study of the town of Valga, the findings show that housing policy plays an important role in urban recovery for a shrinking community and the leadership ca­pacity of local government in this process is crit­ical. Ownership constrains in housing policy can be overcome but the lack of municipal finance and human resources together with insufficient legislation and missing cooperation with the pri­vate sector impedes the process.</p