DOI 10.3389/fdmed.2026.1864810
Advances in oral disease models: a mini-review of developments from 2015 to 2025.
Аннотация
Oral diseases represent one of the most widespread global health burdens, affecting billions of people worldwide, causing pain, disability, and substantial treatment costs. Despite their prevalence, progress in prevention and therapy has been limited, in part, by experimental models that do not fully capture the complexity of the oral biological and environmental landscape. Over the past decade, however, major advances in model development have expanded the possibilities for studying oral disease. This mini-review summarizes advances from 2015 to 2025, focusing on caries and endodontic infections, gingivitis and periodontitis, peri-implantitis, mucosal disorders, oral and oropharyngeal cancers, and salivary gland diseases. Recent innovations include saliva-derived biofilm systems that reproduce ecological transitions, organ-on-chip systems that replicate fluid dynamics, and patient-derived organoids and xenografts that preserve clinical characteristics. In parallel, immune-integrated models now allow direct interrogation of host responses to pathogens. Separate from these experimental platforms, advanced analytical and computational approaches, including single-cell profiling, spatial transcriptomics, radiomics, and artificial intelligence (AI)-assisted image analysis, are increasingly linking molecular signatures with structural and functional disease outcomes. Together, these experimental models and complementary analytical tools mark a shift from reductionist approaches toward dynamic, patient-relevant frameworks that better capture the complexity of oral diseases. Remaining challenges include modeling chronic disease progression, incorporating viral and autoimmune components, and improving reproducibility through standardization across platforms. Addressing these limitations will be important for translating next-generation experimental models into clinically meaningful advances in oral health care.
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Обработка статьи · этапы, ошибки и управление
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История · было → стало
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