A Hyperactive Neutrophil Phenotype in Patients With Refractory Periodontitis
Bibliographic record
Abstract
BACKGROUND: Neutrophils (PMNs) are critical components of the innate immune system and help to maintain oral health in the face of a constant bacterial challenge. However, along with protecting the periodontium from microbial invasion, these cells release potent lysosomal enzymes and oxygen radicals that can be destructive to periodontal tissues and lead to tooth loss. We examined neutrophil function in a unique population of patients diagnosed with refractory aggressive periodontitis (RAP). METHODS: Venous blood was obtained from 12 non-smoking patients who had been diagnosed with RAP, 10 patients with chronic periodontitis who had responded to periodontal therapy (CP), and 13 periodontally healthy controls (HCs). Peripheral blood PMNs were loaded with dihydrorhodamine 123 and stimulated with phorbol 12-myristate 13-acetate (PMA) to measure the receptor-independent respiratory burst of these key immune cells. Phagocytosis via the complement and Fc-gamma receptors was also assessed. RESULTS: PMNs from patients with RAP displayed significantly increased PMA-induced oxygen radical production compared to those from the HC and CP patients. PMNs from RAP patients also displayed increased phagocytosis compared to those from the CP group. CONCLUSIONS: Our findings demonstrated a larger receptor-independent respiratory burst and higher phagocytotic activity in PMNs derived from patients with RAP compared to PMNs derived from CP patients and periodontally HCs. We speculate that the higher intrinsic intracellular activity of the nicotinamide adenine dinucleotide phosphate oxidase system may account for the continued periodontal breakdown, despite ongoing periodontal therapy in these challenging patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".