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Innate immunity and oral microbiome: a personalized, predictive, and preventive approach to the management of oral diseases

  • Jack C. Yu(corresponding author)
    ,
  • Hesam Khodadadi
    ,
*Corresponding author for this work
Scholary Output:
Contribution to journal
Review article
Peer-review

Open access

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Three recent advances in immunology, genetics, and microbiology have ushered in a new era in the continued efforts to better understand and treat oral diseases, moving ever closer to the three Ps of modern healthcare: personalized, predictive, and preventive medicine (PPPM). The discovery of now 15 subtypes of innate lymphoid cells, the refinement of DNA sequencing, and culture-independent characterization of the entire microbial community begin to reveal this complex adaptive network. All these advances warrant a systematic review as they have changed and will continue to change dental medicine. We will update dental professionals on these advances as related to oral diseases and associated pathologies in other organ systems such as premature labor, arthrosclerosis, and cancer. The five objectives are:1.Introduce the concept of microbiota and microbiome2.Explain how we study microbiota and microbiome3.Describe the types and functions of innate lymphoid cells4.Inventory the unique demands of the oral cavity5.Provide a heuristic model to integrate the above6.Conclusions

Publication Information

Output type

Scholary Output:
Contribution to journal
Review article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 43-50 (8 pages)

Journal (Volume, Issue Number)

EPMA Journal (Volume 10, Issue 1)

Publication milestones

  • Published - 03/01/2019

Publication status

Published - 03/01/2019

ISSN

1878-5077

Publication IDs

  • Scopus: 85063045447

Publication metrics

Metrics

Scopus
citations
SciVal
citations
9
SciVal
FWCI
1.16
SciVal
Author count
3
SciVal
Paper percentile
87
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
1

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Citation count
43
Captures
73
Mentions
1