Oral Neutrophils Display a Site‐Specific Phenotype Characterized by Expression of T‐Cell Receptors
Bibliographic record
Abstract
BACKGROUND: Neutrophils, key cells of the innate immune system, were previously thought to be terminally differentiated cells, incapable of altering their gene expression after differentiation and maturation in the bone marrow. Only recently has it been shown that neutrophils perform rapid and complex changes in gene expression during inflammatory responses. Previous work by the authors has demonstrated differences in reactive oxygen species production between oral and peripheral blood neutrophils isolated from patients with chronic periodontitis, suggesting that oral neutrophils present with a unique oral phenotype. Understanding differences in the neutrophil transcriptome after transit from circulation into the site of inflammation will give new insights into how these innate immune cells function during inflammation. METHODS: Venous blood and oral rinse samples were obtained from five healthy participants. Blood neutrophils were isolated using a standard gradient method. Oral neutrophils were isolated through nylon mesh filters of different pore sizes (40 to 10 μm). RNA was purified from isolated neutrophils, and gene expression microarray analysis was completed. Results were confirmed by quantitative reverse transcription-polymerase chain reaction and immunofluorescence microscopy. RESULTS: Oral neutrophil isolation, which is critical when analyzing gene expression with samples clear of epithelial cell contamination, was optimized. It was also demonstrated that oral neutrophils present with a significant increase in T-cell receptor expression compared with circulating neutrophils, suggesting a role for oral neutrophils in crosstalk between the innate and adaptive immune system in the mouth. CONCLUSION: To the best of the authors' knowledge, it is demonstrated for the first time that, compared with circulating neutrophils, oral neutrophils present a site-specific gene expression profile in healthy individuals.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".