Background: As artificial intelligence (AI) becomes increasingly important in modern dentistry, we aimed to assess patients’ perspectives on AI in dentistry specifically for radiographic caries detection and the impact of AI-based diagnosis on patients’ trust. Methods: Validated questionnaires with Likert-scale batteries (1: “strongly disagree” to 5: “strongly agree”) were used to query participants’ experiences with dental radiographs and their knowledge/attitudes towards AI as well as to assess how AI-based communication of a diagnosis impacted their trust, belief, and understanding. Analyses of variance and ordinal logistic regression (OLR) were used (p < 0.05). Results: Patients were convinced that “AI is useful” (mean Likert ± standard deviation 4.2 ± 0.8) and did not fear AI in general (2.2 ± 1.0) nor in dentistry (1.6 ± 0.8). Age, education, and employment status were significantly associated with patients’ attitudes towards AI for dental diagnostics. When shown a radiograph with a caries lesion highlighted by an arrow, patients recognized the lesion significantly less often than when using AI-generated coloured overlays highlighting the lesion (p < 0.0005). AI-based communication did not significantly affect patients’ trust in dentists’ diagnosis (p = 0.44; OLR). Conclusions: Patients showed a positive attitude towards AI in dentistry. AI-supported diagnostics may assist communicating radiographic findings by increasing patients’ ability to recognize caries lesions on dental radiographs.

Objectives: To investigate the effect of different pre-treatments on the long-term bond strength of fiberglass posts luted either with dual-curing self-etch adhesives and core build-up composites or with a self-adhesive resin (SAR) cement. Materials and methods: In total, 180 human root-filled teeth received post-space preparations and three different dentin pre-treatments (PTs): PT1, ethanol (99%); PT2, ethanol-tertiary-butanol-water-solution (AH Plus Cleaner, Dentsply Sirona; York, USA); and PT3, distilled water (control). Five luting systems were used: FU, Futurabond U (Voco; Cuxhaven, Germany); CL, Clearfil DC Bond (Kuraray Noritake; Okayama, Japan); GR, Gradia Core SE Bond (GC Europe NV; Leuven, Belgium); LU, LuxaBond Universal (DMG; Hamburg, Germany); and RX, RelyX Unicem 2 (3M; Minnesota, USA). Roots were cut into six slices (1 mm thick). From each root canal region, three slices were submitted to immediate and three to post-storage push-out testing. The latter were subjected to thermocycling (5–55°C, 6.000 cycles) and stored for six months in saline solution (0.9%, 37°C). Data were analysed using repeated measures ANOVA and chi-square tests (MV±SD). Results: Bond strength was significantly affected by material (p<0.0005), pre-treatment (p=0.016), and storage (p<0.0005; repeated-measures ANOVA). LU (18.8±8.1MPa) revealed significantly higher bond strength than RX (16.08±6.4MPa), GR (15.1±4.6MPa), CL (13.95±5.2MPa), and FU (13.7±6.3MPa). PT1 (16.5±6.9MPa) revealed significantly higher bond strength than PT3 (14.5±5.7MPa). Conclusions: A universal adhesive in self-etch mode combined with a core build-up material revealed higher bond strength than a SAR cement, both interacted positively with Ethanol pre-treatment. Clinical relevance statement: Ethanol (99%) rinsing can be recommended as part of post and core pre-treatment for the investigated luting systems.

Background: Direct pulp capping (DPC) is the least minimal approach for maintaining pulp vitality after pulp exposure. Besides calcium hydroxide (CaOH), hydraulic calcium silicate cements (HCSC) have increasingly been used for DPC. Objectives: During the S3 level guideline development for material choice in DPC, we conducted a systematic review and meta‐analysis of existing literature comparing CaOH and HCSC for DPC on permanent teeth. We aimed (1) to assess clinical and radiographic outcomes and (2) patient‐reported outcomes of DPC. Method: Three databases from 1 January 1990 to 19 February 2025 (MEDLINE via PubMed, EMBASE and Cochrane Database of Systematic Reviews). Prospective comparative clinical studies comparing CaOH to HCSC for DPC in permanent teeth with healthy or reversibly inflamed pulps were included. Studies on primary teeth or teeth indicative of irreversible pulpitis, teeth with unclear diagnoses or pulp exposure of non‐cariogenic origin were excluded. The risk of bias and certainty of evidence were evaluated using the GRADE approach. Using the effect sizes and standard errors for every study, pairwise meta‐analysis was performed comparing CaOH and different subgroups of HCSC. Success was defined as the absence of any clinical symptoms (e.g. pain, swelling) and any radiographical signs of an apical lesion. Patient‐reported outcomes were additionally sought after. Results: Five randomized‐controlled trials including 552 teeth with an overall moderate certainty of evidence were included. HCSC showed a significantly higher probability of success compared to CaOH (Odds Ratio (OR): 2.68, 95% confidence interval [1.7, 4.22], I ² = 0%). The differences between various HCSC materials were minimal. Meta‐regression indicated that neither follow‐up nor risk of bias significantly influenced treatment outcomes, and the funnel plot did not reveal evidence of publication bias. Conclusion: HCSC showed significantly higher probability for clinical and radiographic success than CaOH. This finding comes with moderate certainty. The impact of material choice on postoperative pain remains unclear. Future clinical studies should include patient‐reported outcomes.

Objectives: Age and gender estimation is crucial for various applications, including forensic investigations and anthropological studies. This research aims to develop a predictive system for age and gender estimation in living individuals, leveraging dental measurements such as Coronal Height (CH), Coronal Pulp Cavity Height (CPCH), and Tooth Coronal Index (TCI). Methods: Machine learning models were employed in our study, including Cat Boost Classifier (Catboost), Gradient Boosting Machine (GBM), Ada Boost Classifier (AdaBoost), Random Forest (RF), eXtreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGB), and Extra Trees Classifier (ETC), to analyze dental data from 862 living individuals (459 males and 403 females). Specifically, periapical radiographs from six teeth per individual were utilized, including premolars and molars from both maxillary and mandibular. A novel ensemble learning technique was developed, which uses multiple models each tailored to distinct dental metrics, to estimate age and gender accurately. Furthermore, an explainable AI model has been created utilizing SHAP, enabling dental experts to make judicious decisions based on comprehensible insight. Results: The RF and XGB models were particularly effective, yielding the highest F1 score for age and gender estimation. Notably, the XGB model showed a slightly better performance in age estimation, achieving an F1 score of 73.26%. A similar trend for the RF model was also observed in gender estimation, achieving a F1 score of 77.53%. Conclusions: This study marks a significant advancement in dental forensic methods, showcasing the potential of machine learning to automate age and gender estimation processes with improved accuracy.

Objective: This review aimed to evaluate whether the use of a certain cavity lining material (I) in patients with deep caries lesions in mature or immature permanent teeth associated with no symptoms or reversible pulpitis (P) is as efficacious as other materials or no cavity lining (C) in terms of patient-reported and clinically-reported outcomes (O), with “failure” identified as the primary critical outcome. Materials and methods: Two independent reviewers selected studies, extracted data, and assessed the risk of bias. The systematic literature search was restricted to English-language publications using Cochrane Review, PubMed (Medline) and Ovid databases. Search strategies included combinations of free keywords, controlled vocabulary terms (Medical Subject Headings-MeSH), Boolean operators, truncations and proximity operators. Eligible studies included randomized controlled trials (RCTs), and comparative clinical trials (CCTs). Due to variability in reported outcomes, a meta-analysis was not conducted. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Results: Analysis of 12 studies showed no significant differences in clinical outcomes between restorations with and without cavity liners. Studies directly comparing restorations with and without liners showed no statistically significant differences in key outcomes such as failure rates, postoperative hypersensitivity or secondary caries. (GRADE: low certainty) and minimizing postoperative hypersensitivity (GRADE: very low certainty). The effect of cavity lining on tooth survival (success rate: 94%-100%) and restoration longevity (failure rate: 0%-6%) was of low certainty. Conclusion: Cavity liners, regardless of the material, do not consistently deliver superior clinical outcomes compared to no liners. Clinical relevance: The findings of this systematic review suggest that routine use of cavity liners in deep caries management may not be necessary for achieving successful restorative outcomes.