Oral and Blood Neutrophil Activation States during Experimental Gingivitis
Bibliographic record
Abstract
Polymorphonuclear neutrophils (PMNs) are the primary leukocytes present in the healthy and inflamed oral cavity. While unique PMN activation states have been shown to differentiate health and periodontitis, little is known about the changes in PMN activation states that occur during the transition from periodontal health to gingivitis. The objective of this study was to characterize oral and circulatory PMNs during induction and resolution of experimental gingivitis. Healthy volunteers were recruited to undergo experimental gingivitis. Clinical assessment of pocket depths, bleeding on probing, gingival index, and plaque index, as well as flow cytometric analysis of CD (cluster of differentiation) activation markers on blood and oral PMNs, was performed weekly. All clinical parameters increased significantly during the induction period and returned to baseline levels during the resolution phase. During the induction phase, while oral PMN counts increased, oral PMN activation state based on surface expression of CD63, CD11b, CD16, and CD14 was diminished compared to those seen in health and during the resolution phase. PMNs in circulation during onset showed increased activation based on CD55, CD63, CD11b, and CD66a. Using clinical parameters and oral PMN counts assessed at day 21, we noted 2 unique disease patterns where one-third of subjects displayed an exaggerated influx of oral PMNs with severe inflammation compared to the majority of the population who experienced a moderate level of inflammation and PMN influx. This supports the notion that PMN influx and severe inflammatory changes during gingivitis could identify subjects at risk for the development of severe gingival inflammation and progression toward destructive periodontitis. This study demonstrates that oral PMN activation states are reduced in gingivitis and suggest that only in periodontitis do PMNs become hyperactivated and tissue damaging. Knowledge Transfer Statement: Our article creates a paradigm for future studies of the evolution of essential oral and circulatory biomarkers to identify individuals at risk to develop periodontitis at an early stage of periodontal disease, which is reversible upon proper oral hygiene practices and dental treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".