Background: Dental students are frequently affected by work-related musculoskeletal symptoms (WMSs) due to reasons such as working conditions, difficult education process and long work periods. The aim of the study was to investigate the frequency and anatomical distribution of WMSs, and its effect on the quality of life (QoL) in dental students. Methods: Sociodemographic and health-related characteristics of one-hundred and five dental students were recorded. WMSs were scored by the participants with the Nordic Musculoskeletal Questionnaire. Then, participants were asked to evaluate their QoL by scoring the World Health Organization Quality of Life-Brief Form. Differences between independent groups for continuous variables were evaluated by Student’s t-test and ANOVA as appropriate. Linear regression analysis was performed to determine the effect of demographic and health-related parameters in predicting the QoL subscales. Results: The most common painful region in the last 12 months was the neck (66.7%). The body region with the most WMSs in the last 7 days was the upper back (43.8%). Physical health-related QoL of those with diagnosed musculoskeletal symptoms, and general health-related QoL of those using medicine due to any musculoskeletal symptoms were found to be statistically significantly lower (p = 0.018, p = 0.041, respectively). It was observed that the general and physical health, psychological well-being, and social relationship of the participants who reported the presence of neck pain in the last 7 days were statistically significantly lower (p = 0.003, p < 0.001, p = 0.004, p = 0.012; respectively). According to multiple regression analyses, pain occurrence in the body in the last 12 months and/or in the last 7 days had a negative impact on the participants’ general and physical health, psychological well-being, social relationship, and environmental status and related QoL (p = 0.026, p = 0.047, p = 0.021, p = 0.001, p = 0.027, respectively). Conclusions: The results of this study show that dental students’ body regions, especially the neck and the back, are affected by WMSs. These negative changes observed in the body had a negative effect on the QoL of the dental students.

Objective: The objective of this study was to evaluate the remineralization effect of two different mineral containing agents on white/creamy and yellow/brown demarcated opacities in incisors in children with molar-incisor hypomineralization (MIH) by using laser fluoresence (LF). Study Design: Fifty-three children (n=401 lesions) with MIH were randomly divided into three groups: (1)calcium glycerophosphate (CaGP), (2)casein phosphopeptide amorphous calcium fluoride phosphate (CPP-ACFP) and, (3)control (1450 ppm fluoride toothpaste). Remineralization was evaluated by means of LF, at baseline, after one and threemonths. Anova Test for Repeated Measurements in intra-group comparisons in evaluating the effectiveness of remineralization agents. One-way Variance Analysis (ANOVA) and Tukey-Kramer Multiple Comparison test were used in the comparisons between groups and, Student Newman Keuls Multpile Comparison Test was used to determine the differences between the measurement averages in case of p<0.05. Results: There was a significant improvement in MIH-lesions over time in all groups (p20 scores, the highest percentage changes in CaGP. There was no significant difference between the groups over the time for all the used outcome measures (p>0.05). Conclusion: The additional use of both mineral containing agents in MIH-affected teeth improved these hypomineralized lesions with mineral deposition. Even if both agents could be used in the hypomineralized teeth with demarcated opacities, future studies are recommended the long-term effect of these mineral containing agents with longer observation and a larger sample size.

This study aimed to evaluate and compare the performance of four advanced artificial intelligence-powered chatbots—ChatGPT-4 Omni (ChatGPT-4o), DeepSeek, Gemini Advanced, and Claude 3.7 Sonnet—in responding to questions related to traumatic dental injuries (TDIs) in the primary dentition. The assessment focused on accuracy, completeness, readability, and response time, aligning with the 2020 International Association of Dental Traumatology guidelines. Twenty-five open-ended TDI questions were submitted to each model in two separate sessions. Responses were anonymized and evaluated by four pediatric dentists. Accuracy and completeness were rated using Likert scales; readability was assessed using five standard indices; and response times were recorded in seconds. ChatGPT-4o demonstrated significantly higher accuracy than Gemini Advanced (p = 0.005), while DeepSeek outperformed Gemini Advanced in completeness (p = 0.010). Response times differed significantly (p < 0.001), with DeepSeek being the slowest and ChatGPT-4o and Gemini Advanced being the fastest. DeepSeek produced the most readable outputs relatively, though none met public readability standards. Claude 3.7 generated the most complex texts (p < 0.001). A strong correlation existed between accuracy and completeness (ρ = 0.701, p < 0.001). These findings emphasize the cautious integration of artificial intelligence chatbots into pediatric dental care due to varied performance. Clinical accuracy, completeness, and readability are critical when offering information aligned with guidelines to support decisions in dental trauma management.

Background: The use of artificial intelligence in the field of health sciences is becoming widespread. It is known that patients benefit from artificial intelligence applications on various health issues, especially after the pandemic period. One of the most important issues in this regard is the accuracy of the information provided by artificial intelligence applications. Objective: The purpose of this study was to the frequently asked questions about dental amalgam, as determined by the United States Food and Drug Administration (FDA), which is one of these information resources, to Chat Generative Pre-trained Transformer version 4 (ChatGPT-4) and to compare the content of the answers given by the application with the answers of the FDA. Methods: The questions were directed to ChatGPT-4 on May 8th and May 16th, 2023, and the responses were recorded and compared at the word and meaning levels using ChatGPT. The answers from the FDA webpage were also recorded. The responses were compared for content similarity in “Main Idea”, “Quality Analysis”, “Common Ideas”, and “Inconsistent Ideas” between ChatGPT-4’s responses and FDA’s responses. Results: ChatGPT-4 provided similar responses at one-week intervals. In comparison with FDA guidance, it provided answers with similar information content to frequently asked questions. However, although there were some similarities in the general aspects of the recommendation regarding amalgam removal in the question, the two texts are not the same, and they offered different perspectives on the replacement of fillings. Conclusions: The findings of this study indicate that ChatGPT-4, an artificial intelligence based application, encompasses current and accurate information regarding dental amalgam and its removal, providing it to individuals seeking access to such information. Nevertheless, we believe that numerous studies are required to assess the validity and reliability of ChatGPT-4 across diverse subjects.