Mapping the ECC-Saliva Neuroimmune Axis Using AI: A System-Level Framework.

Area of Science:

• Oral Health Research
• Bioinformatics
• Immunology

Background:

• Early childhood caries (ECC) research spans multiple domains like microbiome, fluoride, and neuroendocrinology.
• The interconnectedness of ECC and saliva research has not been systematically mapped using natural language processing (NLP).

Purpose of the Study:

• To identify major themes, emerging topics, and potential neuroimmune axes in ECC-saliva research by analyzing PubMed literature.
• To create a bibliometric map of ECC-saliva research using AI-assisted topic modeling and network analysis.

Main Methods:

• Retrieved 298 PubMed records (2000-2025) for ECC and saliva.
• Employed NLP techniques including BERTopic for topic modeling and Prophet for temporal trend analysis.
• Generated a synthetic neuroimmune salivary dataset for illustrative purposes.

Main Results:

• Identified seven ECC-saliva topics, including microbiome, fluoride, antioxidant/redox, proteomic, peptide immunity, and Candida-biofilm themes.
• Highlighted high-novelty topics related to antioxidant capacity and peptide-based host defense, with central processes in reactive oxygen species detoxification.
• Forecasting indicated increasing research focus on antioxidant and peptide-immunity themes, with a potential Candida-cytokine-neuroendocrine link.

Conclusions:

• AI-driven analysis provides a map of ECC-saliva research, emphasizing under-explored antioxidant/redox and neuroimmune salivary axes.
• The study proposes a structured agenda for future ECC research, focusing on novel mechanisms and salivary components.