Oral hygiene status and oral care motivation in children aged 7-9 years in a Vietnam primary school: A cross-sectional study.

INTRODUCTION: Oral hygiene is a crucial factor in oral health, especially in children. To increase the awareness of oral care behaviour among children, oral care motivation plays a critical role in daily dental practices. Therefore, this cross-sectional study was conducted to investigate the current oral hygiene status and evaluate the association between oral care motivation and oral hygiene index in 7-9-year-old children at Primary School in Hanoi, Vietnam. METHODS: Clinical examinations were performed on 200 randomly selected children to assess the Simplified Oral Hygiene Index (OHI-S). Face-to-face interviews were applied to record students' intrinsic and extrinsic motivation for oral care through a questionnaire, which consisted of questions regarding demographic characteristics and oral care motivation. Data were analyzed using STATA 15.0 software and a p-value < 0.05 was statistically significant. RESULTS: The mean OHI-S score was 2.48 ± 0.72. Good and fair oral hygiene were observed in 7.5 % and 66 % of participants, respectively. Students' motivation for dental care was predominantly extrinsic, with a mean score of 15.87 ± 1.322. Higher motivation in dental care is statistically significantly associated with oral hygiene index score (Coef=-0.27). CONCLUSION: These results indicate that students with intrinsic motivation exhibit better oral hygiene practices. Consequently, strengthening oral health educational programs in primary schools based on intrinsic motivation could be helped improve the oral hygiene status and oral care behaviours of children.

Proof-of-Concept Study on an Automatic Computational System in Detecting and Classifying Occlusal Caries Lesions from Smartphone Color Images of Unrestored Extracted Teeth.

Dental caries has been considered the heaviest worldwide oral health burden affecting a significant proportion of the population. To prevent dental caries, an appropriate and accurate early detection method is demanded. This proof-of-concept study aims to develop a two-stage computational system that can detect early occlusal caries from smartphone color images of unrestored extracted teeth according to modified International Caries Detection and Assessment System (ICDAS) criteria (3 classes: Code 0; Code 1-2; Code 3-6): in the first stage, carious lesion areas were identified and extracted from sound tooth regions. Then, five characteristic features of these areas were intendedly selected and calculated to be inputted into the classification stage, where five classifiers (Support Vector Machine, Random Forests, K-Nearest Neighbors, Gradient Boosted Tree, Logistic Regression) were evaluated to determine the best one among them. On a set of 587 smartphone images of extracted teeth, our system achieved accuracy, sensitivity, and specificity that were 87.39%, 89.88%, and 68.86% in the detection stage when compared to modified visual and image-based ICDAS criteria. For the classification stage, the Support Vector Machine model was recorded as the best model with accuracy, sensitivity, and specificity at 88.76%, 92.31%, and 85.21%. As the first step in developing the technology, our present findings confirm the feasibility of using smartphone color images to employ Artificial Intelligence algorithms in caries detection. To improve the performance of the proposed system, there is a need for further development in both in vitro and in vivo modeling. Besides that, an applicable system for accurately taking intra-oral images that can capture entire dental arches including the occlusal surfaces of premolars and molars also needs to be developed.

Mitigating the Agglomeration of Nanofiller in a Mixed Matrix Membrane by Incorporating an Interface Agent.

Nanodiamonds (ND) have recently emerged as excellent candidates for various applications including membrane technology due to their nanoscale size, non-toxic nature, excellent mechanical and thermal properties, high surface areas and tuneable surface structures with functional groups. However, their non-porous structure and strong tendency to aggregate are hindering their potential in gas separation membrane applications. To overcome those issues, this study proposes an efficient approach by decorating the ND surface with polyethyleneimine (PEI) before embedding it into the polymer matrix to fabricate MMMs for CO2/N2 separation. Acting as both interfacial binder and gas carrier agent, the PEI layer enhances the polymer/filler interfacial interaction, minimising the agglomeration of ND in the polymer matrix, which is evidenced by the focus ion beam scanning electron microscopy (FIB-SEM). The incorporation of PEI into the membrane matrix effectively improves the CO2/N2 selectivity compared to the pristine polymer membranes. The improvement in CO2/N2 selectivity is also modelled by calculating the interfacial permeabilities with the Felske model using the gas permeabilities in the MMM. This study proposes a simple and effective modification method to address both the interface and gas selectivity in the application of nanoscale and non-porous fillers in gas separation membranes.