Neutrophil FcγRI expression as a determinant of oxidative responses in human blood
Bibliographic record
Abstract
ABSTRACT Neutrophils express Fc receptors on their surface to trap immune complexes. While the roles of FcγRIIa and FcγRIIIb have extensively been studied in that context, that of FcγRI remains elusive. Recently, aggregated IgGs have been shown to induce rapid FcγRI up-regulation and reactive oxygen species (ROS) generation, but the biological relevance of this process is still unclear. In this study, incubation of blood samples from healthy volunteers with heat-aggregated IgGs, used as a model of immune complexes, rapidly up-regulated the surface expression of FcγRI, predominantly on neutrophils, as measured by flow cytometry. Stimulation of isolated neutrophils with aggregated IgGs resulted in the production of ROS in an FcγRI-dependent fashion, as monitored with a luminol-based chemiluminescence assay. Cytochalasin B potentiated FcγRI expression and ROS production. In resting blood, positive correlations between neutrophil FcγRI and ROS production were observed, both in healthy volunteers and patients with lupus. This study unveils a potentially central regulatory role for neutrophil FcγRI in ROS production, both in healthy individuals and patients with lupus, and identifies neutrophil FcγRI as a promising target to modulate oxidative response.
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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 | 0.000 |
| 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".