As soon as saliva contacts the teeth surface, salivary proteins adhere to the tooth surface to form acquired salivary pellicle. The formation of this acquired salivary pellicle is a dynamic and selective process of macromolecular adsorption and desorption. Although acquired salivary pellicle contains proteins and peptides, it also contains lipids, and other macro-molecules, all of which contribute to its protective properties. Acquired salivary pellicle is related to the development of common oral diseases, such as erosion, dental caries, and periodontal disease. Acquired salivary pellicle acts as a natural barrier to prevent a tooth’s surface from making direct contact with acids and to protect it from erosive demineralization. It contributes to the control of dental erosion by modulating calcium and phosphate concentrations on the tooth surface. It also influences the initial colonizer of oral biofilm and affects the transportation pathway of the acidic products of cariogenic bacteria, which affects the development of dental caries. In addition, it influences periodontal disease by acting on the colonization of periodontal pathogens. This paper’s aim is to provide an overview of the acquired salivary pellicle, highlighting its composition, structure, function, role in common oral diseases, and modification for the prevention of oral diseases.

Artificial intelligence (AI) has made deep inroads into dentistry in the last few years. The aim of this systematic review was to identify the development of AI applications that are widely employed in dentistry and evaluate their performance in terms of diagnosis, clinical decision-making, and predicting the prognosis of the treatment.

The literature for this paper was identified and selected by performing a thorough search in the electronic data bases like PubMed, Medline, Embase, Cochrane, Google scholar, Scopus, Web of science, and Saudi digital library published over the past two decades (January 2000-March 15, 2020).After applying inclusion and exclusion criteria, 43 articles were read in full and critically analyzed. Selleckchem Elesclomol Quality analysis was performed using QUADAS-2.

AI technologies are widely implemented in a wide range of dentistry specialties. Most of the documented work is focused on AI models that rely on convolutional neural networks (CNNs) and artificial neural networks (ANNs). These AI models have been used in detection and diagnosis of dental caries, vertical root fractures, apical lesions, salivary gland diseases, maxillary sinusitis, maxillofacial cysts, cervical lymph nodes metastasis, osteoporosis, cancerous lesions, alveolar bone loss, predicting orthodontic extractions, need for orthodontic treatments, cephalometric analysis, age and gender determination.

These studies indicate that the performance of an AI based automated system is excellent. They mimic the precision and accuracy of trained specialists, in some studies it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.

These studies indicate that the performance of an AI based automated system is excellent. They mimic the precision and accuracy of trained specialists, in some studies it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.Periodontitis is a progressive inflammation disease, the clinical management of which remains a challenge. The traditional management may control periodontal inflammation, but failed to regenerate functional periodontium. This review summarizes the most advancing regenerative techniques regarding stem cell culture and scaffold fabrication, such as cell sheeting, spheroid culture, electrospinning and 3D printing. The applications of different techniques manifest tremendous potential of regenerating the complete and functional periodontium. Albeit promising, new technologies have met with their own drawbacks such as insufficient vascularization and precision, which necessitate deeper modification. Thus, this review also points out the potential perspectives and methods aiming at their disadvantages, illuminating the directions of future researches to successful clinical scenarios.

In the recent years artificial intelligence (AI) has revolutionized in the field of dentistry. The aim of this systematic review was to document the scope and performance of the artificial intelligence based models that have been widely used in orthodontic diagnosis, treatment planning, and predicting the prognosis.

The literature for this paper was identified and selected by performing a thorough search for articles in the electronic data bases like Pubmed, Medline, Embase, Cochrane, and Google scholar, Scopus and Web of science, Saudi digital library published over the past two decades (January 2000-February 2020). After applying the inclusion and exclusion criteria, 16 articles were read in full and critically analyzed. QUADAS-2 were adapted for quality analysis of the studies included.

AI technology has been widely applied for identifying cephalometric landmarks, determining need for orthodontic extractions, determining the degree of maturation of the cervical vertebra, predicting the facial attractcan be of great value in orthodontics.Odontogenic maxillary sinusitis (OMS) is a well-recognized condition in both the dental and otolaryngology communities. Close to 30% of cases of unilateral maxillary sinusitis may have an underlying dental pathology. Failure to identify a dental cause usually lead to cases recalcitrant sinusitis often associated with serious complications. The aim of this study is to describe the literature findings on odontogenic maxillary sinusitis that discuss anatomy, epidemiology, etiology, bacteriology, diagnosis and treatment. The present review is based on a current search using bibliographic database and academic search engine. All the articles on odontogenic maxillary sinusitis published after 2000 were included. This study seeks to provide clinicians with evidence that motivates a comprehensive approach to the evaluation and management of OMS. Controversies on diagnosis and management have been addressed and data from different treatment plans were collected by exploring relevant publications. The surgical treatment of OMS is based essentially on the dental surgery, combined with endoscopic sinus surgery, in order to completely remove the infection, restore the physiological drainage of the sinus and prevent recurrences of sinusitis.