Periodontitis is a multifactorial chronic inflammatory disease that affects tooth-supporting soft/hard tissues of the dentition. The dental plaque biofilm is considered as a primary etiological factor in susceptible patients; however, other factors contribute to progression, such as diabetes and smoking. Current management utilizes mechanical biofilm removal as the gold standard of treatment. Antibacterial agents might be indicated in certain conditions as an adjunct to this mechanical approach. However, in view of the growing concern about bacterial resistance, alternative approaches have been investigated. Currently, a range of antimicrobial agents and protocols have been used in clinical management, but these remain largely non-validated. This review aimed to evaluate the efficacy of adjunctive antibiotic use in periodontal management and to compare them to recently suggested alternatives. Evidence from in vitro, observational and clinical trial studies suggests efficacy in the use of adjunctive antimicrobials in patients with grade C periodontitis of young age or where the associated risk factors are inconsistent with the amount of bone loss present. Meanwhile, alternative approaches such as photodynamic therapy, bacteriophage therapy and probiotics showed limited supportive evidence, and more studies are warranted to validate their efficiency.
Background: The primary stability of the dental implant is a crucial factor determining the ability to initiate temporary implant-supported prosthesis and for subsequent successful osseointegration, especially in the maxillary non-molar sites. This study assessed the reliability of the insertion torque of dental implants by relating it to the implant stability quotient values measured by the Osstell device. Material and methods: This study included healthy, non-smoker patients with no history of diabetes or other metabolic, or debilitating diseases that may affect bone healing, having non-restorable fractured teeth and retained roots in the maxillary non-molar sites. Primary dental implant stability was evaluated using a torque ratc
... Show MoreIn this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show MoreThere are two main categories of force control schemes: hybrid position-force control and impedance control. However, the former does not take into account the dynamic interaction between the robot’s end effector and the environment. In contrast, impedance control includes regulation and stabilization of robot motion by creating a mathematical relationship between the interaction forces and the reference trajectories. It involves an energetic pair of a flow and an effort, instead of controlling a single position or a force. A mass-spring-damper impedance filter is generally used for safe interaction purposes. Tuning the parameters of the impedance filter is important and, if an unsuitable strategy is used, this can lead to unstabl
... Show MoreThis study compared the clinicopathological, immunohistochemical characteristics and Epstein-Barr virus (EBV) detection of Burkitt's lymphoma (BL) in the abdomen and jaw of Iraqi patients. A cohort/retrospective study was carried out between August and September 2024 using 25 tissue blocks (14 gnathic and 11 abdominal BL) from the Oral and Maxillofacial Laboratory, University of Baghdad, College of Dentistry, and the National Centre for Educational Laboratories. The sections were stained with haematoxylin and eosin (H&E), while CD10, CD20, Bcl-2, BCl-6, C-Myc and Ki-67 markers were used for diagnosis. The DNA detection of the EBV was performed by polymerase chain reaction (PCR). The tumours showed 22 classical and 3 atypical histologi
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreLexicography, the art and craft of dictionary-making, is as old as writing. Since its very early stages several thousands of years ago, it has helped to serve basically the every-day needs of written communication among individuals in communities speaking different languages or different varieties of the same language. Two general approaches are distinguished in the craft of dictionary-making: the semasiological and the onomasiological. The former is represented by usually-alphabetical dictionaries as such, i.e. their being inventories of the lexicon, while the latter is manifested in thesauruses. English and Arabic have made use of both approaches in the preparation of their dictionaries, each having a distinct aim ahead. Wit
... Show MoreEvaluation of the Antibacterial Efficacy of Electrolyzed Oxidizing Water as an Irrigant against Enterococcus faecalis (An In vitro Study), Noor A Khait*, Muna Saleem Kalaf
Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.