Hyperfunctional Neutrophils in Aged Mice Are Linked to Enhanced Bone Loss in Ligature-Induced Periodontitis
Bibliographic record
Abstract
Background/Objectives: Aging alters neutrophil functions, which may contribute to the progression and severity of periodontitis-related alveolar bone loss. Neutrophils play a key role in immune defense. However, the effects of aging on neutrophil functions and their contribution to periodontal disease remain unclear. This study examined age-related neutrophil dysfunction and its impact on periodontal bone loss. Methods: We used young (6 weeks old) and aged (18 months old) C57BL/6 mice to assess age-related neutrophil function. Neutrophil migration, superoxide production, phagocytic activity, and NETosis were evaluated. A peritonitis model and a ligature-induced periodontitis model were employed to investigate the relationship between neutrophil activity and alveolar bone loss. Results: Neutrophils from aged mice exhibited reduced migration toward pathogens compared to those from young mice. However, aged neutrophils showed increased superoxide production, elevated phagocytic activity, and enhanced NETosis. In the periodontitis models, these age-related neutrophil alterations coincided with accelerated alveolar bone loss in aged mice. Conclusions: The findings indicate that aging is linked to dysregulated neutrophil functions, characterized by excessive oxidative stress, heightened phagocytosis, and increased NETosis. These functional changes may contribute to immune dysregulation and tissue damage, thereby promoting age-related alveolar bone loss in periodontitis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".