Background: Nanoparticles are clusters of atoms in a size range from (1-100) nm. Nano dentistry creates amazing useful structures from individual atoms or molecules (nanoparticles), which provides a new alternative and a possibly superior strategy in prevention and treatment of dental caries through management of dental plaque biofilms. The aim of the study was to test the sensitivity of Streptococcus mutans to different concentrations of hydroxyapatite and iron oxide nanoparticles suspension solutions, in comparison to chlorhexidine, and de-ionized water, in vitro. Materials and methods: Agar well technique was applied to test the sensitivity of Streptococcus mutans to different concentrations of hydroxyapatite and iron oxide nanoparticle

Background: Cross contamination of dental appliances in the dental clinics and laboratories may potentially be a health hazard to the dental team and the patient. This study aimed to evaluate bacterial contamination of acrylic complete denture as received from dental laboratory before delivery to the patient, and then to evaluate the effectiveness of disinfection with 2% chlorhexidine and Kin denture cleaner tablet. Materials and methods: 45 newly made upper complete dentures undergone biaacterial examination for contamination before delivered to the patient. Samples were examined in two stages, first after finishing and polishing; when collected from the laboratory and before inserting to the patient mouth, second; after the samples were

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Background: Enterococcus faecalis (E. faecalis) is a prototypical resistant bacterium in root canal infections and a leading cause of endodontic treatment failure. German chamomile (Matricaria chamomilla) flower extract has been used as a traditional medicine to treat infections. The aim of this study was to investigate the antimicrobial efficacy of chamomile extract on the removal of E. faecalis root canal biofilm. Materials and Methods: Chamomile flower extract was prepared and subjected to detailed chemical analysis. For the in vitro biofilm model, human mandibular premolars (n=48) with 18-20mm working length were used. Root canal preparation was performed using the ProTaper® Next system. Each sample was split longitudinally and reassem

Introduction: We aimed to assess the impact of adhesive and wires types on the tensile bond strength of fixed lingual retainers. Methods: A total of 160 intact bovine teeth were collected, cleaned, stored in 25% sodium hypochlorite, and randomly assigned to two groups based on the adhesive type: a two-step adhesive and a one-step adhesive. Each group was further divided into four subgroups based on the type of lingual retainer wire, which included (A) 8-strand braided stainless steel wire, (B) three-strand titanium retainer wire, (C) stainless steel chain, and (D) fiber-reinforced retainer. A tensile bond strength test was conducted using a universal testing machine at a controlled speed of 10 mm/min. Result: The 8-strand braided stainles

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ