Evidence map›Paper›PMID 41749544›Full record

ArticleChildren (Basel, Switzerland)2026

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

Ahmed Alamoudi, Hammam Ahmed Bahammam

Abstract read
In one paragraph

Article in Children (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ahmed AlamoudiOral Biology Department, Faculty of Dentistry, King Abdulaziz University, Jeddah P.O. Box 80209, Saudi Arabia.ORCID 0000-0001-7459-5324
Hammam Ahmed BahammamDepartment of Paediatric Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah P.O. Box 80209, Saudi Arabia.ORCID 0000-0001-5946-5337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesEarly childhood caries (ECC) and saliva have been studied across disparate domains, including microbiome, fluoride, immune, oxidative-stress, and neuroendocrine research. However, the ECC-saliva literature has not previously been mapped as a connected system using modern natural language processing (NLP). This study treats PubMed titles and abstracts as data to identify major themes, emerging topics, and candidate neuroimmune axes in ECC-saliva research.

methodsUsing the NCBI E-utilities API, we retrieved 298 PubMed records (2000-2025) matching ("early childhood caries" [Title/Abstract]) AND saliva [Title/Abstract]. Text was cleaned with spaCy and embedded using a transformer encoder; BERTopic combined UMAP dimensionality reduction and HDBSCAN clustering to derive thematic topics. We summarised topics with class-based TF-IDF, constructed keyword co-occurrence networks, defined an internal topic-level Novelty Index (semantic distance plus temporal dispersion), and mapped high-novelty topics to gene ontology and Reactome pathways using g:Profiler. Prophet was used to model temporal trends and forecast topic-level publication trajectories. Finally, we generated a fully synthetic neuroimmune salivary dataset, based on realistic ranges from the literature, to illustrate how the identified axes could be operationalised in future ECC cohorts.

resultsSeven coherent ECC-saliva topics were identified, including classical microbiome and fluoride domains as well as antioxidant/redox, proteomic, peptide immunity, and

conclusionsAI-assisted topic modelling and network analysis provide a reproducible, bibliometric map of ECC-saliva research that highlights underexplored antioxidant/redox and neuroimmune salivary axes. The synthetic neuroimmune dataset and modelling pipeline are illustrative only, but together with the literature map, they offer a structured agenda for future ECC cohorts and mechanistic studies.

Indexed as

biomarkersCandida–cytokine–neuro hypothesisearly childhood caries (ECC)neuro-immune signalling

Identifiers

PMID41749544
PMCPMC12940005

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.