Background Unilateral posterior crossbite (UPC) is a common malocclusion in pre-adolescents and adolescents and is often associated with transverse discrepancies and potential skeletal asymmetries. Mandibular asymmetry, particularly involving the condyle and ramus, may either contribute to or result from such malocclusions, thereby impacting diagnosis and treatment planning.Aim To systematically evaluate the association between mandibular asymmetry and unilateral posterior crossbite (UPC) in pre-adolescent and adolescent populations.Types of Studies Reviewed A comprehensive literature search was conducted across databases including, PubMed (MEDLINE), Scopus, Google Scholar, supplemented by manual and gray literature searches upto September 2024. All study types, except case reports and review articles, were included. The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO CRD42025641032). Studies assessing condylar and ramal asymmetry in individuals with UPC compared to those with normal occlusion were included. Risk of bias was assessed using the ROBINS-I tool for non-randomized comparative studies.Result Fourteen studies met the inclusion criteria, predominantly comprising cross-sectional study designs. The majority of studies reported increased condylar and/or ramal asymmetry in patients with UPC, although not all differences reached statistical significance. Variations in measurement methods and outcomes precluded meta-analysis. These findings were supported by GRADE-based evidence assessments and descriptive synthesis.Practical Implication/ Conclusion These findings underscore the potential impact of UPC on mandibular development and reinforce the importance of early diagnosis and intervention. Future well-designed, longitudinal studies employing standardized imaging protocols and outcome measures are needed to confirm these associations and guide clinical decision-making.
Background The evolving landscape of dentistry in the United States demands a core shift from transactional to transformational leadership among practitioners. Historically, dental practices have operated as small, solo entities where short-term, task-focused leadership sufficed. However, increasing consolidation and technological advancements are driving dentistry toward larger, more complex organizations.Discussion This transition exposes the inadequacy of current dental education, which emphasizes technical competency but lacks formal leadership training. Two ethical frameworks, relationship-based and market-driven, shape how dentists view their roles and responsibilities, yet the future of the profession requires leaders who can bridge both perspectives, inspire teams, foster innovation, and facilitate organizational growth. Transformational leadership is essential for improving patient outcomes, maintaining staff engagement, adapting to rapid technological change, and ensuring the overall success of dental practices. Addressing this need, dental education programs and accrediting standards must integrate comprehensive leadership training and continuing professional development for both students and practitioners. Effective mentorship, collaboration with business, schools, and ongoing education will be critical to preparing dentists to be visionary leaders within an expanding and increasingly complex health care ecosystem.
Background Artificial intelligence (AI) is becoming an increasingly visible force in dentistry – shaping imaging and diagnostics, treatment planning, robotics and automation, virtual and augmented reality, predictive analytics, and administrative support. Yet the United States has limited AI-specific regulation in health care, leaving professional self-governance and ethical stewardship as primary safeguards. To maintain public trust and protect patients, dentistry must define how AI should be used, how accountability is preserved, and what competencies are required for safe adoption.Case Description Dentistry should formally embrace an augmented intelligence (AUI) posture – a “human-in-the-loop” model in which AI supports, but does not replace, clinical judgment and professional responsibility. An education-forward strategy grounded in four learning domains (fundamentals, applications, assessment, and governance/ethics) is proposed to ensure dentists can evaluate AI outputs, recognize signs of bias, and apply AI appropriately within clinical and operational contexts. Building on this framework, three profession-level priorities are emphasized: (1) curricular reform to establish consistent AI competencies across training programs; (2) improved clinical governance to guide selection, validation, monitoring, and documentation of AI tools in practice; and (3) data democratization to strengthen transparency, equity, and shared learning across institutions and settings.
