What does this research mean for the field?

Accurate study and management of peri-implantitis require ecosystem-specific experimental models that incorporate biomaterial corrosion, barrier biology, and systemic risk factors, moving beyond traditional biofilm-centric approaches. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.ESTABLISHES_NEW_DIRECTION.

What question did this study set out to answer?

To evaluate preclinical in vivo and microengineered models of peri-implantitis based on their capacity to replicate mucosal barrier biology, biomaterial interfaces, and systemic risk factors.

August 28, 2026Periodontology 2000Open Access

Decoding host–microbial dynamics in peri‐implantitis: Ecosystem‐specific experimental models

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Authors

GKGeorgios A. KotsakisRutgers, The State University of New Jersey DSDavi Neto de Araújo SilvaUCLA Health AWAsaf WilenskyHebrew University of Jerusalem

Discussion

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Implication

Narrative review uncovers the role of biomaterial interfaces and systemic modifiers in peri-implantitis models, indicating that multi-component systems are essential for translational research.

Key Points

To evaluate preclinical in vivo and microengineered models of peri-implantitis based on their capacity to replicate mucosal barrier biology, biomaterial interfaces, and systemic risk factors.
Conducted a targeted literature search in PubMed prioritizing in vivo peri-implantitis models assessing local risk factors and systemic comorbidities.
Assessed emerging three-dimensional peri-implant mucosa organ-on-a-chip platforms for their translational capacity and alignment with reduction principles.
Ligature- and infection-induced animal models elucidate bacterial inflammatory pathways, showing that titanium degradation and particle release act as key costimulatory pathogenic drivers.
Integration of systemic comorbidities demonstrates that diabetes, vascular disease, and antiresorptive medications exacerbate peri-implant bone loss and can induce MRONJ-like lesions.
Organ-on-a-chip mucosa systems enable controlled exposure to bacteria, biomechanical strain, and titanium particles while providing human-relevant mucosal barrier readouts.

Cite This Study

Kotsakis et al. (2026) studied this question.

synapsesocial.com/papers/6a914622d15324a1df3a98b4 https://doi.org/10.1111/prd.70076

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August 28, 2026Periodontology 2000Open Access

Decoding host–microbial dynamics in peri‐implantitis: Ecosystem‐specific experimental models

View Full Paper

Ask AI

Bookmark

Authors

GKGeorgios A. KotsakisRutgers, The State University of New Jersey DSDavi Neto de Araújo SilvaUCLA Health AWAsaf WilenskyHebrew University of Jerusalem

Discussion

Member takes

Implication

Narrative review uncovers the role of biomaterial interfaces and systemic modifiers in peri-implantitis models, indicating that multi-component systems are essential for translational research.

Key Points

To evaluate preclinical in vivo and microengineered models of peri-implantitis based on their capacity to replicate mucosal barrier biology, biomaterial interfaces, and systemic risk factors.
Conducted a targeted literature search in PubMed prioritizing in vivo peri-implantitis models assessing local risk factors and systemic comorbidities.
Assessed emerging three-dimensional peri-implant mucosa organ-on-a-chip platforms for their translational capacity and alignment with reduction principles.
Ligature- and infection-induced animal models elucidate bacterial inflammatory pathways, showing that titanium degradation and particle release act as key costimulatory pathogenic drivers.
Integration of systemic comorbidities demonstrates that diabetes, vascular disease, and antiresorptive medications exacerbate peri-implant bone loss and can induce MRONJ-like lesions.
Organ-on-a-chip mucosa systems enable controlled exposure to bacteria, biomechanical strain, and titanium particles while providing human-relevant mucosal barrier readouts.

Cite This Study

Kotsakis et al. (2026) studied this question.

synapsesocial.com/papers/6a914622d15324a1df3a98b4 https://doi.org/10.1111/prd.70076

View Full Paper

Ask AI

Bookmark