Salivary Biomarkers Identification: Advances in Standard and Emerging Technologies
Introduction: Salivary biomarkers have been extensively studied in relation to oral disease, such as periodontal disease, oral cancer, and dental caries, as well as systemic conditions including diabetes, cardiovascular diseases, and neurological disorders. Literature Review: A systematic literature...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Oral |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-6373/5/2/26 |
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| Summary: | Introduction: Salivary biomarkers have been extensively studied in relation to oral disease, such as periodontal disease, oral cancer, and dental caries, as well as systemic conditions including diabetes, cardiovascular diseases, and neurological disorders. Literature Review: A systematic literature review was conducted, analyzing recent advancements in salivary biomarker research. Databases such as PubMed, Scopus, and Web of Science were searched for relevant studies published in the last decade. The selection criteria included studies focusing on the identification, validation, and clinical application of salivary biomarkers in diagnosing oral and systemic diseases. Various detection techniques, including enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), mass spectrometry, and biosensor technologies, were reviewed to assess their effectiveness in biomarker analysis. Specific biomarkers, such as inflammatory cytokines, oxidative stress markers, and microRNAs, have been identified as reliable indicators of disease progression. Current Trends and Future Perspectives: Advances in proteomics, genomics, and metabolomics have significantly enhanced the ability to analyze salivary biomarkers with high sensitivity and specificity. Despite the promising findings, challenges remain in standardizing sample collection, processing, and analysis to ensure reproducibility and clinical applicability. Conclusions: Future research should focus on developing point-of-care diagnostic tools and integrating artificial intelligence to improve the predictive accuracy of salivary biomarkers. |
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| ISSN: | 2673-6373 |