Introduction: Oral diseases are common and affect millions of people worldwide. They can range from mild and easily treatable conditions to more severe and serious diseases. Proper oral hygiene and regular dental monitoring are essential for maintaining good oral health. When it comes to children’s health and well-being, parents’ education level plays a critical role. Research has shown that parents’ higher educational attainment is associated with better health outcomes for their children. Our aim is to evaluate whether parents’ education level and employment influence children oral health and its impact on the family. Methods: We enrolled consecutively healthy subjects aged between 0–16 and their parents at the Dental Clinic of the University of Campania “L. Vanvitelli”. The Italian version of the ECOHIS (I-ECOHIS) was administered to parents of the enrolled subjects referred to the Dental Clinic of the University of Campania “L. Vanvitelli”. Linear regression models, adjusted for age and sex, were used to explore the association between parents’ employment or education level and the ECOHIS scores. Statistical significance was accepted when p value < 0.05. Results: We found a significative association of a higher I-ECOHIS total score (coeff. 4.04244; CI 95%: 1.530855–6.554026; p = 0,002) and higher I-ECOHIS children section score (coeff. 3.2794; CI 95%: 1.29002–5.268; P = 0,002) and the father unemployed status. We also found that a higher education level of the father was associated with a lower ECOHIS total score (coeff. -1.388; IC 95%: -2.562115—-0.214 p = 0.021) and a higher education level of the mother was associated with a lower ECOHIS in children section (coeff. -0.972; IC95%: -1.909356—0.034; p = 0.042). Conclusions: Father unemployed status and a lower educational level for both parents may negatively affect oral health status.

Introduction: While Temporomandibular disorders (TMDs) are not typically considered a primary symptom of Parkinson disease (PD), recent studies have documented a correlation between ageing and TMDs, a cluster of conditions affecting the temporomandibular joint and surrounding musculature, thereby underscoring the potential for an increased frequency of TMDs in the ageing PD population.Objective: The purpose of this review is to systematically evaluate the existing literature on the topic and provide a comprehensive overview of the prevalence of TMDs in patients with PD.Methods: To determine eligibility, we utilised the Population (human subjects), Exposure (PD), Comparator (PD vs non‐PD subjects), and Outcomes (TMD) (PECO) model. To conduct this systematic review, we searched for articles published in PubMed, Web of Science and Lilacs from the beginning until April 15, 2023.Results: Three studies were selected. All together they comprised a total of 55 828 subjects, out of which 12 629 were affected by PD or Parkinsonism, and the remaining 43 199 were non‐PD subjects matched for age and sex. The study aimed to evaluate the prevalence of TMDs in subjects affected by PD. The results showed that 193/12629 (1.53%) of PD individuals presented with TMD symptoms or were diagnosed with TMD, while 260/43199 (0.6%) of non‐PD subjects were diagnosed with the same. The meta‐analysis showed that there was a higher TMD prevalence in PD subjects compared to non‐PD subjects (RR 1.57; 95% CI: 1.30–1.89).Conclusion: The studies reviewed suggest a possible association between TMD and PD. Further research is needed to clarify the relationship between TMD and PD and to identify possible mechanisms and treatment strategies.

Periodontitis is an inflammatory disease of the gums characterized by the degeneration of periodontal ligaments, the formation of periodontal pockets, and the resorption of the alveolar bone, which results in the destruction of the teeth’s supporting structure. Periodontitis is caused by the growth of diverse microflora (particularly anaerobes) in the pockets, releasing toxins and enzymes and stimulating the immune system. Various approaches, both local and systemic, have been used to treat periodontitis effectively. Successful treatment depends on reducing bacterial biofilm, bleeding on probing (BOP), and reducing or eliminating pockets. Currently, the use of local drug delivery systems (LDDSs) as an adjunctive therapy to scaling and root planing (SRP) in periodontitis is a promising strategy, resulting in greater efficacy and fewer adverse effects by controlling drug release. Selecting an appropriate bioactive agent and route of administration is the cornerstone of a successful periodontitis treatment plan. In this context, this review focuses on applications of LDDSs with varying properties in treating periodontitis with or without systemic diseases to identify current challenges and future research directions.

The accuracy of 3D reconstructions of the craniomaxillofacial region using cone beam computed tomography (CBCT) is important for the morphological evaluation of specific anatomical structures. Moreover, an accurate segmentation process is fundamental for the physical reconstruction of the anatomy (3D printing) when a preliminary simulation of the therapy is required. In this regard, the objective of this study is to evaluate the accuracy of four different types of software for the semiautomatic segmentation of the mandibular jaw compared to manual segmentation, used as a gold standard. Twenty cone beam computed tomography (CBCT) with a manual approach (Mimics) and a semi-automatic approach (Invesalius, ITK-Snap, Dolphin 3D, Slicer 3D) were selected for the segmentation of the mandible in the present study. The accuracy of semi-automatic segmentation was evaluated: (1) by comparing the mandibular volumes obtained with semi-automatic 3D rendering and manual segmentation and (2) by deviation analysis between the two mandibular models. An analysis of variance (ANOVA) was used to evaluate differences in mandibular volumetric recordings and for a deviation analysis among the different software types used. Linear regression was also performed between manual and semi-automatic methods. No significant differences were found in the total volumes among the obtained 3D mandibular models (Mimics = 40.85 cm³, ITK-Snap = 40.81 cm³, Invesalius = 40.04 cm³, Dolphin 3D = 42.03 cm³, Slicer 3D = 40.58 cm³). High correlations were found between the semi-automatic segmentation and manual segmentation approach, with R coefficients ranging from 0,960 to 0,992. According to the deviation analysis, the mandibular models obtained with ITK-Snap showed the highest matching percentage (Tolerance A = 88.44%, Tolerance B = 97.30%), while those obtained with Dolphin 3D showed the lowest matching percentage (Tolerance A = 60.01%, Tolerance B = 87.76%) (p < 0.05). Colour-coded maps showed that the area of greatest mismatch between semi-automatic and manual segmentation was the condylar region and the region proximate to the dental roots. Despite the fact that the semi-automatic segmentation of the mandible showed, in general, high reliability and high correlation with the manual segmentation, caution should be taken when evaluating the morphological and dimensional characteristics of the condyles either on CBCT-derived digital models or physical models (3D printing).