Eduardo Diogo Gurgel-Filho

This study aimed to evaluate the bond strength of a bioceramic endodontic sealer and AH-Plus sealer irrigated with 2% chlorhexidine (CHX), compared to irrigation with 2.5% sodium hypochlorite (NaOCl) as a control group. Thirty freshly extracted single-rooted human teeth were prepared using reciprocating R25 and R40 files. Irrigation consisted of 2.5% NaOCl in the control group and 2% CHX gel in the experimental group, with additional irrigation using saline solution after each instrument change. Samples were divided into four groups: two with CHX, one with bioceramic sealer, and the other with AH-Plus sealer, and two with hypochlorite, one with bioceramic sealer and the other with AH-Plus sealer. The teeth were sectioned, and the resulting slices were subjected to the push-out test using a mechanical testing machine for measuring the microtensile force. After testing, samples were examined to determine the failure pattern. Data normality was assessed (Shapiro-Wilk, P<0.05), and non-parametric analyses (Kruskal-Wallis with Dunn’s post hoc, Wilcoxon rank-sum with Benjamini-Hochberg correction) were applied. Effect sizes (Cohen’s d, Cliff’s Delta), bootstrap 95% confidence intervals (CIs) (2000 replicates), and the post hoc power were calculated. Significance was set at P<0.05. AH-Plus exhibited higher bond strength than Sealer Plus BC across all root thirds, independent of irrigant. For Sealer Plus BC, bond strength was influenced by irrigant, with NaOCl producing higher values than CHX (P<0.05). AH-Plus exhibited superior bond strength irrespective of the irrigant used. In contrast, the bond strength of the Sealer Plus bioceramic sealer was influenced by the irrigant, with NaOCl yielding higher values than CHX.

Background: Migraine is a common and disabling neurological disorder among women, and hormonal variability may influence disease expression during midlife. However, migraine trajectories across the menopausal transition remain heterogeneous and incompletely characterized. This scoping review aimed to map evidence on migraine across menopausal stages, including clinical patterns, associated factors, therapeutic approaches, and knowledge gaps. Methods: Following Joanna Briggs Institute methodology, comprehensive searches were performed. Studies investigating adult women with migraine across premenopause, perimenopause, or postmenopause were included. Findings were synthesized descriptively through evidence mapping. Results: Of 2,199 records identified, 41 studies published between 1993 and 2026 were included. Migraine trajectories were heterogeneous: although prevalence frequently declined after natural menopause, persistence or worsening occurred in a substantial subgroup, particularly during perimenopause or after abrupt hormonal changes. Migraine was consistently associated with vasomotor symptoms, sleep disturbances, mood symptoms, disability, and reduced quality of life. Biological evidence suggested that hormonal instability interacts with persistent neurovascular mechanisms rather than estrogen deficiency alone, while therapeutic evidence remained limited and supported individualized management. Conclusions: Evidence converges toward a multidimensional model in which hormonal instability, persistent neurovascular susceptibility, and contextual clinical factors jointly shape migraine burden across the menopausal transition. These findings challenge the traditional assumption that menopause is uniformly associated with migraine improvement and provide a conceptual framework to support more individualized assessment, management, and future longitudinal research.

This study aimed to compare an annotation‐free deep learning (DL) model with human evaluators for detecting periapical bone rarefactions (PBRs) on panoramic radiographs (PRs) and to assess the clinical acceptability of AI‐supported dental imaging. A mixed‐methods diagnostic validation was conducted using 238 PRs, equally distributed between images with ( n = 119) and without ( n = 119) PBRs. Model performance was compared with that of four calibrated dentists: two oral and maxillofacial radiologists and two endodontists. The reference standard was based on internationally accepted radiographic criteria applied by calibrated researchers under expert supervision, with final classifications verified by the principal investigator. Diagnostic performance was assessed using standard diagnostic metrics, chance‐corrected agreement statistics and receiver operating characteristic analysis, while clinical acceptability was explored through questionnaires and thematically analysed semi‐structured interviews. At the sensitivity‐oriented decision threshold of 0.27, the DL model achieved a sensitivity of 0.924, a specificity of 0.109, an accuracy of 0.517, a precision of 0.509 and an F 1‐score of 0.657. Threshold‐independent binary discrimination was moderate (ROC‐AUC = 0.726). Human evaluators showed more balanced profiles, with accuracy ranging from 0.655 to 0.752 and F 1‐scores from 0.654 to 0.779. Professional perception was generally favourable, although responses varied among evaluators. The annotation‐free DL model showed high sensitivity and moderate discrimination for PBR detection. Although low specificity limits autonomous use, the findings support annotation‐free learning as a potentially scalable strategy, warranting further training with larger and more heterogeneous datasets.

Aim: To discuss how in silico research may function as an early translational decision layer in endodontics by supporting the prioritisation of hypotheses, technologies and experimental conditions before biological and clinical validation. Summary: Endodontic outcomes emerge from interacting anatomical, mechanical, chemical, microbial and host‐related variables. Conventional studies using extracted teeth, artificial canals, selected microbial models and standardised tests remain essential, yet cannot represent the full variability encountered in clinical settings. In silico approaches, including finite element analysis, computational fluid dynamics, probabilistic simulations, molecular modelling and predictive toxicology, may extend preclinical investigation by mapping plausible scenarios across pathological pathways, instrument performance, biomaterials and irrigation. Their contribution depends on a clearly defined context of use, justified input data, transparent assumptions, verification, validation, sensitivity analysis and uncertainty assessment. Computational outputs should be interpreted according to the question the model was designed to address and should guide subsequent experimental selection rather than be treated as independent evidence of clinical effectiveness.

Background: Pulp calcification (PC) is a common imaging finding traditionally attributed to local factors or ageing. However, increasing evidence suggests that it may be associated with broader systemic biological disturbances. Clarifying this association may help determine whether dental pulp findings contribute to the interpretation of systemic health. Objectives: To evaluate whether imaging‐detected PC is associated with systemic conditions by synthesising evidence across diverse disorders and identifying recurring biological and methodological patterns. Methods: Comprehensive searches were conducted in EMBASE, ProQuest, PubMed, SciELO, Scopus, Web of Science, and the Virtual Health Library up to November 2025. Observational studies assessing associations between imaging‐detected PC and systemic conditions were included. Study quality and risk of bias were assessed using the Newcastle–Ottawa Scales and Joanna Briggs Institute tools. A mixed‐methods synthesis combined thematic analysis with random‐effects meta‐analysis. Associations were expressed as odds ratios (ORs) with 95% confidence intervals (CIs), and certainty of evidence was evaluated using GRADE. Results: Thirty‐three studies were included, comprising 19 057 patients. The primary meta‐analysis ( n = 22) showed a statistically significant association between systemic conditions and PC (OR = 2.69; 95% CI: 2.04–3.54), although substantial heterogeneity was observed. Subgroup analyses identified a consistent association for diabetes mellitus, with no statistical heterogeneity (OR = 2.30; I ² = 0.0%), while the atherosclerosis‐focused analysis showed the highest magnitude of association (OR = 4.70; I ² = 0.0%). Broader cardiovascular disease conditions did not reach statistical significance ( p = 0.155). Renal and genetic specialised conditions showed only exploratory evidence, based on two studies and rated as very low certainty. Thematic analysis suggested that PC may be associated with metabolic and vascular triggers, modulated by molar predilection and constrained by imaging resolution. The certainty of evidence ranged from low to very low across outcomes. Conclusion: Current evidence supports a statistically significant association between imaging‐detected PC and systemic metabolic and vascular conditions, particularly diabetes mellitus and atherosclerosis‐related outcomes. However, the evidence is predominantly observational and does not establish causality, temporality, prediction, or diagnostic utility. PC may represent an imaging finding associated with systemic dysregulation, but its biological significance remains uncertain and its interpretation should remain cautious and context‐dependent.

Background: Artificial intelligence (AI) applied to magnetic resonance imaging (MRI) may improve detection of cervical lymph node metastases in oral squamous cell carcinoma (OSCC) but is heterogeneous. Methods: A systematic review identified observational studies (from 2000) evaluating AI‐based MRI in adults with histopathologically confirmed OSCC. Risk of bias was assessed with QUADAS‐AI. Diagnostic performance was synthesized using a hierarchical bivariate model. Publication bias and certainty of evidence were assessed using Deeks' test and GRADE. Results: Twelve studies were included; seven datasets (548 participants) were meta‐analyzed. Pooled sensitivity was 0.72 (95% CI: 0.62–0.80) and specificity 0.79 (95% CI: 0.73–0.83), with AUC 0.82 and diagnostic odds ratio 9.42. Heterogeneity is mainly related to threshold effects. No significant publication bias was detected ( p = 0.536). Evidence certainty was low. Conclusions: AI‐assisted MRI shows moderate diagnostic performance. Multicenter validation is required before clinical implementation. Clinical Relevance: AI‐supported MRI may serve as an adjunctive tool to improve preoperative risk stratification of cervical lymph node metastasis in OSCC.

Artificial intelligence (AI) models for diagnostic imaging face reproducibility challenges due to inconsistent reporting. Existing guidelines also lack specificity for imaging-based AI diagnostics, particularly regarding clinical usability and technical transparency. To address these gaps, the Completeness, Learnability, Applicability, Interpretability, Reproducibility, and Evaluation (CLAIRE) framework was developed as a practical reporting aid by a multidisciplinary team of clinicians and AI experts. CLAIRE was retrospectively validated on a subset of 10 imaging studies selected by theoretical saturation in medical and dental imaging. Internal validation demonstrated high reliability, with inter-rater agreement improving from Cohen’s κ 0.286 to 0.987 (p < 0.01) after calibration, alongside a mean intra-rater reliability of 0.997 after a six-month washout period. This process yielded a 15-item structured checklist for standardising AI reporting, supported by an objective scoring system for quality categorisation and an editorial reference guide to facilitate systematic appraisal by reviewers and editors. CLAIRE aims to enhance clinician accessibility through plain-language technical summaries and assessments of real-world applicability. This proposal provides a unified and practical structure that improves reporting consistency, supports systematic assessment, and strengthens both reproducibility and clinical translation of AI-based imaging models.

Selective root canal retreatment preserves well‐filled canals by treating only roots showing clinical or imaging evidence of failure, providing a minimally invasive alternative to conventional full retreatment. This scoping review, supported by metasynthesis through thematic analysis, synthesised clinical and imaging evidence in multirooted teeth. Five studies, including experimental research and case reports, were analysed. Thematic analysis revealed four core themes: clinical outcomes, imaging assessment, procedural features, and methodological limitations. Short‐term outcomes of selective retreatment were comparable to full retreatment, with high tooth survival and low incidence of new lesions. Three‐dimensional imaging played a pivotal role in detecting root‐confined pathology, planning selective access, and supporting structural preservation. Evidence remains limited by small sample sizes, retrospective designs, and heterogeneity in study protocols. This review offers a structured synthesis of selective retreatment, integrating clinical and imaging insights to inform minimally invasive endodontic practice in a research and clinical context.