Objectives: The aim of the present cross-sectional study was to assess oral health in adolescents selected from the ELSPAC (European Longitudinal Study of Pregnancy and Childhood) Bmo group and complete thus the ELSPAC series of studies on child general health.
Material And Methods: Randomly selected children from the ELSPAC group (n=780) were examined clinically for dental and periodontal status, dental plaque, dental calculus and orthodontic anomalies. The following clinical parameters were assessed: DMFT score and its components, gingival index (GI), plaque index (PI) and calculus index (CSI). GI, PI and CSI were recorded on selected teeth. The presence/absence of orthodontic anomalies and their severity were recorded. ANOVA test for quantitative and XZ2 test for qualitative parameters evaluation were used.
Results: Mean DMFT of the group was 2.82 (SE 0.36), share of caries-free children 25.4%. Mean GI index of the cohort was 0.204 (SE 0.011), grade 0 was found in 36.9% children, grade 1 in 43.0%, and grade 2 in 19.5%. Statistical significant associations (p < 0.05) were observed in GI and DMFT, GI and DT value, GI and severity of orthodontic anomaly; significant difference was found in GI of caries-free and treated children vs. treatment need and in PI value between children with gingivitis vs healthy ones.
Conclusion: The results demonstrated a relatively high caries experience, low level of gingival inflammation and relation between GI and DMFT, particularly in D component, and between GI and orthodontic anomalies.
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Cleft Palate Craniofac J
January 2025
Division of Orthodontics, Hospital for Rehabilitation of Craniofacial Anomalies, University of São Paulo, Bauru, Brazil.
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Department of Advanced Material Technologies, Faculty of Chemistry, Wrocław University of Science and Technology, Smoluchowskiego 25, Wroclaw, 50-372, POLAND.
The objective of this review is to deepen understanding and emphasize scientific and technological progress in the transformation of crop by-products into bio-based dental materials. Amid heightened environmental sustainability consciousness, various sectors including dentistry have achieved novel advancements by utilizing bio-based materials from crop by-products for dental restorations. This paper provides a thorough review of the extraction, processing, and application of natural polymers, biopolymers, and bio-based mixtures at both the macroscopic and nanoscopic scales, with a focus on their contextualization within dental practices.
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Prosthetic Dentistry Discipline, Department 4-Prosthetic Dentistry and Dental Materials Department, "Iuliu Hatieganu" Medicine and Pharmacy University, 400006 Cluj-Napoca, Romania.
: The impact of craniocervical posture on malocclusion has long intrigued researchers in dentistry, orthodontics, and physical therapy. This research aims to elucidate the relationship between craniocervical posture and both dental and skeletal malocclusions and to explore the potential for integrated multidisciplinary therapeutic approaches. : We analyzed peer-reviewed articles published between 2013 and 2023 from PubMed/Medline, Web of Science, EMBASE, and Scopus.
View Article and Find Full Text PDFBioengineering (Basel)
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Departamento de Odontoestomatología, Facultad de Medicina y Ciencias de la Salud, Universidad de Barcelona, Campus Bellvitge, 08097 L'Hospitalet de Llobregat, Barcelona, Spain.
The use of artificial intelligence in orthodontics is emerging as a tool for localizing cephalometric points in two-dimensional X-rays. AI systems are being evaluated for their accuracy and efficiency compared to conventional methods performed by professionals. The main objective of this study is to identify the artificial intelligence algorithms that yield the best results for cephalometric landmark localization, along with their learning system.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Orthodontics, Faculty of Dentistry, Yeditepe University, Istanbul 34728, Turkey.
Cleft lip and palate patients often present with unique anatomical challenges, making dental anomaly detection and numbering particularly complex. The accurate identification of teeth in these patients is crucial for effective treatment planning and long-term management. Artificial intelligence (AI) has emerged as a promising tool for enhancing diagnostic precision, yet its application in this specific patient population remains underexplored.
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