Background Despite drawbacks, cold-cured acrylic resin is still the most common material used in denture repair. Zirconia nanoparticles were among the reinforcements added to increase the strength of the resin. The effect on Candida due to the addition of zirconia nanoparticles to the resin has not been investigated. Purpose The aim of this study was to evaluate the effect of zirconia nanoparticles added to cold-cured acrylic resin on Candida albicans adhesion. Materials and methods A total of 120 acrylic resin specimens with dimensions measuring 22×10×2.5 mm 3 were prepared and divided into two equal groups. One group (repair) comprised heat-polymerized specimens that were sectioned at the center and prepared to create a 2 mm repair area that was repaired with cold-cured resin reinforced with 0% wt, 2.5% wt, 5% wt, and 7.5% wt zirconia nanoparticles. The second group contained intact cold-cured acrylic resin specimens reinforced with 0% wt, 2.5% wt, 5% wt, and 7.5% wt zirconia nanoparticles. Specimens were incubated at 37°C in artificial saliva containing C. albicans , and the effect of zirconia nanoparticles on C. albicans was assessed using two methods: 1) a slide count method and 2) a direct culture test. Variations in the number of living Candida were observed in relation to the different concentrations of zirconia nanoparticles. Analysis of variance (ANOVA) and post hoc Tukey’s tests were performed for data analysis. If the P -value was ≤0.05, then the difference was considered as statistically significant. Results It was found that C. albicans adhesion to repaired specimens was significantly decreased by the addition of zirconia nanoparticles ( P <0.00001) in comparison with the control group. Intact cold-cured groups and groups repaired with cold-cured resin reinforced with 7.5% wt zirconia nanoparticles showed the lowest Candida count. Tukey’s test showed a significant difference between the repaired group and the intact cold-cured group, while the later demonstrated a lower Candida count. Conclusion The addition of zirconia nanoparticles to cold-cured acrylic resin is an effective method for reducing Candida adhesion to repaired polymethyl methacrylate (PMMA) denture bases and cold-cured removable prosthesis. Clinical significance Based on the results of the current study, zirconia nanoparticles have an antifungal effect, which could be incorporated in the repair material for repairing denture bases and in PMMA removable prostheses as a possible approach for denture stomatitis prevention.

Background This study aimed to assess the knowledge of dental professionals in Saudi Arabia regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19). Methods A questionnaire was developed to assess various dental professionals from both governmental and private sectors through online and social media outlets. Results A total of 1,033 questionnaires were collected (273 dental students, 193 dental auxiliary personnel, 544 dentists). In all, 63.4% of the respondents worked in hospitals. Of all the respondents, 44.9%, 33.4%, and 21.7% worked in governmental clinics, academia, and the private sector, respectively. Overall knowledge of the incubation period and route of transmission of SARS-CoV-2 was consistent across all dental professions. Knowledge of hand-soap cleaning time was significantly different among dental professionals (p < 0.001). Dental professionals displayed significant disagreement on the survival of SARS-CoV-2 outside the host (p < 0.001). Furthermore, 75.1% of the respondents were reluctant to treat a suspected COVID-19 patient, and 92% of the participants believed that the mode of transmission was droplet inhalation. Fever, coughing, and shortness of breath were identified as the most common symptoms of COVID-19. Most standard methods of prevention in the dental office were selected by at least 50% of the participants. Conclusions Dental professionals seem to be consistent regarding their knowledge of the incubation period of SARS-CoV-2. However, knowledge of viral survivability and recommended hand-soap washing time was significantly variable among the professionals. A high degree of apprehension toward suspected COVID-19 patients existed among all dental professionals. Pandemic-awareness campaigns are essential among healthcare providers.

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Objectives Many countries have enforced lockdowns on their populations due to the coronavirus disease 2019 (COVID‐19) pandemic. This study aimed to assess the effects of the lockdown on dental students. Methods A longitudinal, repeated cross‐sectional study was conducted to evaluate psychological problems experienced by dental students during the COVID‐19 lockdown in Saudi Arabia. The dental students were selected from different universities using 2‐stage cluster sampling. The validated Arabic version of the 21‐item depression, anxiety, and stress scale questionnaire was distributed at the beginning and end of the lockdown. Mann–Whitney U and Kruskal–Wallis tests were used as appropriate. Chi‐square test was used to compare the proportions between the sociodemographic data, and logistic regression analysis was used to identify variables associated with the students’ responses. Results A total of 1287 respondents participated in this study (695 first‐survey respondents, 592 second‐survey respondents). There were longitudinally significant differences in the students’ mental health outcomes based on gender, university, class year, and survey time during the COVID‐19 lockdown. The lockdown increased the likelihood of female, single, and junior students experiencing stress. The students who lived alone recorded a high chance of elevated levels of depression, anxiety, and stress, which showed a significant longitudinal reduction during the lockdown. Moreover, the lockdown increased the likelihood of mental health problems among the students staying in households of two persons or two‐five persons. Conclusions This study indicates the importance of considering the detrimental mental health consequences on dental students in the event of future pandemics.

Computer-based technologies play a central role in the dentistry field, as they present many methods for diagnosing and detecting various diseases, such as periodontitis. The current study aimed to develop and evaluate the state-of-the-art object detection and recognition techniques and deep learning algorithms for the automatic detection of periodontal disease in orthodontic patients using intraoral images. In this study, a total of 134 intraoral images were divided into a training dataset (n = 107 [80%]) and a test dataset (n = 27 [20%]). Two Faster Region-based Convolutional Neural Network (R-CNN) models using ResNet-50 Convolutional Neural Network (CNN) were developed. The first model detects the teeth to locate the region of interest (ROI), while the second model detects gingival inflammation. The detection accuracy, precision, recall, and mean average precision (mAP) were calculated to verify the significance of the proposed model. The teeth detection model achieved an accuracy, precision, recall, and mAP of 100 %, 100%, 51.85%, and 100%, respectively. The inflammation detection model achieved an accuracy, precision, recall, and mAP of 77.12%, 88.02%, 41.75%, and 68.19%, respectively. This study proved the viability of deep learning models for the detection and diagnosis of gingivitis in intraoral images. Hence, this highlights its potential usability in the field of dentistry and aiding in reducing the severity of periodontal disease globally through preemptive non-invasive diagnosis.