Neutrophil tissue delivery, early immune protection and quality of life in neutropenia
Bibliographic record
Abstract
The role of neutrophils in maintaining oral health has been well documented and is best understood when examining the poor oral health-related quality of life of children with neutropenia. Under normal conditions, the bacterial presence in the mouth is kept under control by a constant influx of neutrophils from surrounding periodontal tissues. This chemotactic recruitment of neutrophils to the oral cavity inspired us to develop and validate a non-invasive oral rinse assay to study the delivery of neutrophils to the mouth following chemotherapy and bone marrow transplantation (BMT), and to compare this information to circulating neutrophil levels, oral mucositis scores and infection-related fever episodes following blood neutrophil recovery. Using this oral rinse, we showed that oral neutrophils reappeared and returned to a stable level earlier in the mouth than in the blood following BMT, thus enabling us to successfully predict engraftment much sooner than it was evident in their blood counts as per the conventional definition of engraftment. Furthermore, the timing of neutrophil tissue delivery in the mouth was a good indicator of neutrophil functionality and infection susceptibility in the post-BMT setting. Consequently, we developed a mouse BMT model which uses enhanced green fluorescent protein-expressing donor neutrophils. Besides recapitulating the results from our human study, this mouse BMT model allowed us to better understand neutrophil recovery kinetics following transplantation and how they relate to the restoration of cellular immune function post-BMT. Using the model, we have demonstrated that protection against bacterial infection is conferred at the time of neutrophil tissue delivery which always occurs before neutrophils are detected in the blood. These findings reaffirmed the clinical utility of the oral rinse assay to predict engraftment and susceptibility to infection following transplantation. Moreover, the mouse BMT model served as an in vivo cell migration model to study the effectiveness of specific drug therapies on neutrophil recovery and functionality. This animal model has the potential to help us better understand the molecular mechanisms of neutrophil mobilization, and will allow us to begin to identify the biological determinants that influence the rate of neutrophil tissue penetration, their levels and survival in the tissues.
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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 | 0.001 |
| 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 | 0.000 |
| 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".