Objectives: The objective of this single-use, five-treatment, five-period, cross-over randomized controlled trial (RCT) was to compare the efficacy in dental plaque removal of a new Y-shaped automatic electric toothbrush (Y-brush) compared to a U-shaped automatic electric toothbrush (U-brush), a manual toothbrushing procedure (for 45 and 120 s), and no brushing (negative control).
Materials And Methods: Eligible participants were volunteer students randomized to the treatments in the five periods of the study. The primary outcome measure was the reduction in full-mouth plaque score (FMPS) after brushing while the secondary outcome variable was a visual analogic scale (VAS) on subjective clean mouth sensation. Mixed models were performed for difference in FMPS and VAS.
Results: After brushing procedures, manual toothbrushing (120 s) showed a statistically significant reduction in FMPS than Y-brush (difference 36.9; 95%CI 29.6 to 44.1, p < 0.0001), U-brush (difference 42.3; 95%CI 35.1 to 49.6, p < 0.0001), manual brushing (45 s) (difference 13.8; 95%CI 6.5 to 21.1, p < 0.0001), and No brushing (difference 46.6; 95%CI 39.3 to 53.9, p < 0.0001). Y-brush was significantly more effective than No brushing (difference 9.8; 95%CI 2.5 to 17.0, p = 0.0030), while there was no significant difference compared to U- brush. Similar results were obtained for the differences in the Clean Mouth VAS.
Conclusions: Y-brush was significantly more effective than no brushing (negative control) in removing dental plaque. When compared to manual toothbrushing for both 45 and 120 s, however, Y-brush was less effective in dental plaque removal.
Clinical Relevance: Modified design of automatic toothbrushing devices could improve plaque reduction, especially in patients with intellectual disabilities or motor difficulties.
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http://dx.doi.org/10.1007/s00784-024-05601-w | DOI Listing |
Front Robot AI
January 2025
Department of Materials and Production, Aalborg University, Aalborg, Denmark.
Object pose estimation is essential for computer vision applications such as quality inspection, robotic bin picking, and warehouse logistics. However, this task often requires expensive equipment such as 3D cameras or Lidar sensors, as well as significant computational resources. Many state-of-the-art methods for 6D pose estimation depend on deep neural networks, which are computationally demanding and require GPUs for real-time performance.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiovascular Surgery, Gaozhou People's Hospital, Gaozhou, Guangdong, China.
Objective: The objective of this study was to improve long-term postoperative survival in a porcine cardiac valve surgery model by utilizing cardiopulmonary bypass (CPB) via left thoracotomy. The study aimed to share refined techniques and insights accumulated over years at a single-center animal clinical trial facility.
Method: A total of 196 Chinese Large White pigs weighing between 60 and 75 kg were used in the study.
ACS Sens
January 2025
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, P. R. China.
Accurate and efficient sorting of single target cells is crucial for downstream single-cell analysis, such as RNA sequencing, to uncover cellular heterogeneity and functional characteristics. However, conventional single-cell sorting techniques, such as manual micromanipulation or fluorescence-activated cell sorting, do not match current demands and are limited by low throughput, low sorting efficiency and precision, or limited cell viability. Here, we report an automated, highly efficient single-cell sorter, integrating laser-induced forward transfer (LIFT) with a high-throughput picoliter micropore array.
View Article and Find Full Text PDFFront Artif Intell
January 2025
Department of Computer and Automatic Control, Faculty of Engineering, Tanta University, Tanta, Egypt.
Introduction: Diabetes prediction using clinical datasets is crucial for medical data analysis. However, class imbalances, where non-diabetic cases dominate, can significantly affect machine learning model performance, leading to biased predictions and reduced generalization.
Methods: A novel predictive framework employing cutting-edge machine learning algorithms and advanced imbalance handling techniques was developed.
Magn Reson Med
January 2025
Advanced Research Promotion Center, Health Sciences University of Hokkaido, Ishikari, Japan.
Purpose: Redox homeostasis plays a key role in regulating the overall health and development of organisms. This study aimed to develop a compact and mobile continuous-wave (CW) electron paramagnetic resonance (EPR) imager to facilitate stable, highly sensitive fast three-dimensional (3D) whole-body imaging of nitroxide-infused mice.
Methods: A multiturn loop gap resonator with a diameter of 30 mm and length of 35 mm was designed for whole-body EPR imaging.
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