Single-Appointment Fabrication of Interim Immediate Denture: A Clinical Report

Objective: An immediate complete denture is fabricated before the extraction of all teeth. It has several advantages such as preservation of esthetics, muscular tone, normal speech and reduction of post-operative pain. This report describes a method of using patient’s current fixed partial denture (FPD) for single-appointment construction of interim immediate denture.Case: We used patient’s existing maxillary FPD for single-appointment fabrication of an interim immediate denture; which was delivered to the patient after the extraction of his remaining maxillary teeth.Conclusion: Within a short time, an interim immediate denture can be fabricated for patients to preserve occlusion, vertical facial height and facial appearance until the fabrication of final prosthesis

An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation

Generative modelling for shapes is a prerequisite for In-Silico Clinical Trials (ISCTs), which aim to cost-effectively validate medical device interventions using synthetic anatomical shapes, often represented as 3D surface meshes. However, constructing AI models to generate shapes closely resembling the real mesh samples is challenging due to variable vertex counts, connectivities, and the lack of dense vertex-wise correspondences across the training data. Employing graph representations for meshes, we develop a novel unsupervised geometric deep-learning model to establish refinable shape correspondences in a latent space, construct a population-derived atlas and generate realistic synthetic shapes. We additionally extend our proposed base model to a joint shape generative-clustering multi-atlas framework to incorporate further variability and preserve more details in the generated shapes. Experimental results using liver and left-ventricular models demonstrate the approach's applicability to computational medicine, highlighting its suitability for ISCTs through a comparative analysis

Teachers’ use of Descriptive Assessment methods in primary school mathematics education in Iran

International audienc

Dusty Air Pollution is Associated with an Increased Risk of Allergic Diseases in Southwestern Part of Iran

Concerns have been raised about the adverse impact of dusty air pollution (DAP) on human health. The aim of this study was to find the association between dusty air pollution based on air quality index (AQI) and the risk of allergic diseases in southwestern provinces of Iran, with assessing cytokine profiles and lymphocyte immunophenotypes. In this case control study 148 individuals participated. The sampling was done in hazardous condition (AQI >300) as the case and clean air (AQI <50) as the control. We measured cytokine production by using ELISA method and phenotypes of T-lymphocytes (CD4+ and CD8+), CD19+ B-lymphocytes, CD25+, CD4+ CD25+ cells by FACSort flow cytometer. The mean serum level of IL-4 (33.4±2.9 vs 0.85± 0.65 pg/dl) and IL-13 (15.1±4.4 vs. 0.12±0.7 pg/dl) in the subjects exposed to ambient DAP was increased significantly compared to the individuals in the clean air condition. Also, CD19+ B-lymphocytes (12.6± 4.9 vs 8.9±3.2%) and CD4+ CD25+ cell count (13.6± 4.6 vs 7.7± 3.8%) in peripheral blood were increased significantly in subjects exposed to ambient DAP compared with the controls. The result of our study suggested that ambient DAP affected immune system in a way that might lead to allergic diseases in the population

Common Aeroallergens in Patients with Asthma and Allergic Rhinitis Living in Southwestern Part of Iran: Based on Skin Prick Test Reactivity

Aeroallergens continue to have a key role in the pathogenesis of asthma and allergic diseases and have recently received increased attention in medical research throughout the world. The prevalence of aeroallergens vary in different regions, depending on the type of climate. The aim of the present study was to determine prevalence of the sensitivity to aeroallergens among patients with asthma and allergic rhinitis (AR), based on skin prick test (SPT) reactivity in the province of Bushehr, Iran. In this cross-sectional study, 743 patients were enrolled. The participants had asthma and AR and reacted to at least one allergen with SPT. Skin prick test with standard extracts including house dust mites (HDMs), animal dander, molds and pollens were performed on patients according to the herbal geography of the area. The male to female ratio and mean age of the patients were 1.03 and 27.6± 15.4 year, respectively. Out of 567 patients with AR, the common aeroallergens were HDMs (88.5%), molds (82.9%), animal dander (79.5%), weeds (77.6%), trees (75.5%) and grass pollen (71.5%). Moreover, among 176 patients with asthma, the prevalence of aeroallergens were HDMs (90.5 %), molds (80.7%), animal dander (77.5%), weeds (73.3%), trees (73.3%) and grass pollen (67.9%). The sensitivity to animal dander, Chenopodium album and Russian thistle pollens were significantly associated with the severity of AR. Moreover, sensitivity to animal dander such as cat and feather of birds, cockroach, Bermuda grass and Chenopodium album pollens were significantly associated with the severity of asthma. The results of this study revealed that HDM was the most common sensitizing aeroallergen in patients with asthma and AR. Molds and animal dander as indoor allergens were also common aeroallergens. We suggest that the hot weather and ambient humidity in the region may be the main cause of the change in the pattern of SPT reactivity

Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data

A probabilistic framework for registering generalised point sets comprising multiple voxel-wise data features such as positions, orientations and scalar-valued quantities, is proposed. It is employed for the analysis of magnetic resonance diffusion tensor image (DTI)-derived quantities, such as fractional anisotropy (FA) and fibre orientation, across multiple subjects. A hybrid Student’s t-Watson-Gaussian mixture model-based non-rigid registration framework is formulated for the joint registration and clustering of voxel-wise DTI-derived data, acquired from multiple subjects. The proposed approach jointly estimates the non-rigid transformations necessary to register an unbiased mean template (represented as a 7-dimensional hybrid point set comprising spatial positions, fibre orientations and FA values) to white matter regions of interest (ROIs), and approximates the joint distribution of voxel spatial positions, their associated principal diffusion axes, and FA. Specific white matter ROIs, namely, the corpus callosum and cingulum, are analysed across healthy control (HC) subjects (K = 20 samples) and patients diagnosed with mild cognitive impairment (MCI) (K = 20 samples) or Alzheimer’s disease (AD) (K = 20 samples) using the proposed framework, facilitating inter-group comparisons of FA and fibre orientations. Group-wise analyses of the latter is not afforded by conventional approaches such as tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM)