Periodontal Inflammation Primes the Systemic Innate Immune Response
Bibliographic record
Abstract
The presence of periodontal diseases (PDs) often strongly correlates with other severe chronic inflammatory conditions, including cardiovascular disease, diabetes, and arthritis. However, the mechanisms through which these diseases interact are unclear. In PD, tissue and bone destruction in the mouth is driven by elevated recruitment of polymorphonuclear neutrophils (PMNs), which are primed and recruited from the circulation to sites of inflammation. We predicted that systemic effects on PMN mobilization or priming could account for the interaction between PD and other inflammatory conditions. We tested this using a mouse model of ligature-induced PD and found elevated PMN counts specifically in bone marrow, supporting a systemic effect of periodontal tissue inflammation on PMN production. In contrast, mice with induced peritonitis had elevated PMN counts in the blood, peritoneum, and colon. These elevated counts were further significantly increased when acute peritonitis was induced after ligature-induced PD in mice, revealing a synergistic effect of multiple inflammatory events on PMN levels. Flow cytometric analysis of CD marker expression revealed enhanced priming of PMNs from mice with both PD and peritonitis compared to mice with peritonitis alone. Thus, systemic factors associated with PD produce hyperinflammatory PMN responses during a secondary infection. To analyze this systemic effect in humans, we induced gingival inflammation in volunteers and also found significantly increased activation of blood PMNs in response to ex vivo stimulation, which reverted to normal following resolution of gingivitis. Together, these results demonstrate that periodontal tissue inflammation has systemic effects that predispose toward an exacerbated innate immune response. This indicates that peripheral PMNs can respond synergistically to simultaneous and remote inflammatory triggers and therefore contribute to the interaction between PD and other inflammatory conditions. This suggests larger implications of PD beyond oral health and reveals potential new approaches for treating systemic inflammatory diseases that interact with PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".