Objectives: To assess dental root development in two groups of paediatric patients who received treatments with reverse headgear and rapid maxillary expansion and slow maxillary dental arch expansion.
Materials And Methods: The 20 subjects (13 girls, 7 boys; mean age: 8.9 ± 1.3 years) in the first group were treated with a Petit-type reverse headgear attached to a full-coverage bonded rapid maxillary expander via elastics (RME&RHg group). The 20 subjects included in the second group (9 girls, 11 boys; mean age: 9.1 ± 2.2 years) were selected among patients who were treated with Hawley appliances for slow maxillary expansion (SME group). Digitized panoramic radiographs were used. A total of 960 permanent teeth (maxillary-mandibular incisors, canines, premolars, and first molars) were measured quantitatively for pre-treatment and post-treatment.
Results: No significant increase was found except for the right and left maxillary and mandibular second premolars and left mandibular and first premolar in the RME&RHg group (P < 0.05). Teeth length values increased significantly in all maxillary and mandibular teeth except maxillary first molars and mandibular incisors in the SME group (P < 0.05). Inter-group comparisons showed that statistically significant differences were observed in maxillary and mandibular incisors, left maxillary first premolar, and molar teeth (P > 0.05).
Limitation: A limitation of this study is the use of two-dimensional radiographic images for root length measurement. However, ethical obligations limit the dental cone beam computed tomography imaging application for protection of paediatric patients from harm.
Conclusions: RME&RHg therapy inhibits root development of maxillary and mandibular teeth in the early period. However, further studies should be performed to determine whether this effect on root development is reversible or irreversible.
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Environ Res
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Department of Chemistry, University college in Al-Jamoum, Umm Al-Qura University, 21955, Makkah, Saudi Arabia.
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Faculty of Educational Studies, Adam Mickiewicz University, Poznań, Poland.
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Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea. Electronic address:
This study evaluated the performance of a deep-learning-based model that predicted cooking loss in the semispinalis capitis (SC) muscle of pork butts using hyperspectral images captured 24 h postmortem. To overcome low-scale samples, 70 pork butts were used with pixel-based data augmentation. Principal component regression (PCR) and partial least squares regression (PLSR) models for predicting cooking loss in SC muscle showed higher R values with multiplicative signal correction, while the first derivative resulted in a lower root mean square error (RMSE).
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