GA Al Omran, AA Noaimi, Z Al Madfai, H Al Hamamy, Journal of the Faculty of Medicine Baghdad, 2012

Introduction Periodontal diseases are ranked among the most common health problems affecting mankind. These conditions are initiated by bacterial biofilm, which is further modulated by several risk factors. Objectives To investigate the association of different risk factors with periodontal...

The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.

Background & objective: Difficult intubation remains a risk for patients undergoing general anesthesia (GA) or mechanical ventilation in an intensive care unit (ICU). Macroglossia is a known factor for difficult intubation. But it is not routine to assess the tongue size to predict difficult intubation. Studies are found deficient in comparing usefulness of measuring thyromental distance and the tongue thickness (TT) measured by ultrasonography to estimate difficult intubation. We compared tongue thickness measured by ultrasonography and thyromental distance as a means to anticipate difficult intubation. Methodology: A convenient sample of 60 patients; 32 males and 28 females, who were undergoing elective surgery with GA were i

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Background Parkinson’s disease (PD) is currently the fastest-growing neurological disorder in the world. Patients with PD face numerous challenges in managing their chronic condition, particularly in countries with scarce healthcare infrastructure. Objective This qualitative study aimed to delve into neurologists’ perspectives on challenges and gaps in the Iraqi healthcare system that influence the management of PD, as well as strategies to mitigate these obstacles. Method Semi-structured interviews were conducted with neurologists from five different Iraqi provinces, working in both hospitals and private neurology clinics, between November 2024 and January 2025. A thematic analysis approach was employed to identify the main challenge