The trapping of live neutrophils by macrophages during infection
Bibliographic record
Abstract
Abstract Neutrophils are highly abundant in the oral mucosal tissues, and their balanced activation and clearance are essential for immune homeostasis. Here, we demonstrate that neutrophils infected with the bacterial pathogen Porphyromonas gingivalis (Pg) are captured alive by macrophages in a manner that bypasses all known receptor-ligand interactions involved in the phagocytosis of either live or dead cells. Mechanistically, upon interaction with Pg, or its protease RgpB (gingipains), live neutrophils undergo rapid remodeling of their proteomes, generating neoepitopes. N-terminomics-based proteomic profiling identified multiple RgpB cleavage sites on several azurophilic granule proteins that are translocated to the surface of live neutrophils via low-level degranulation and activate macrophage αMβ2 integrin receptors, thus mediating internalization of non-apoptotic neutrophils within macrophage phagosomes. Macrophages with entrapped live neutrophils exhibit phenotypic and transcriptional reprogramming, consistent with inflammatory outcomes in vitro and in vivo. In contrast to the immunosuppressive outcomes associated with efferocytosis of apoptotic neutrophils, live neutrophil entrapment failed to fully activate several catabolic and metabolic processes and exhibited a defective activation of PPAR-γ mediated pro-resolution pathways, thereby promoting bacterial persistence and hindering the resolution of inflammation. Thus, our data demonstrate a novel immune subversion strategy unique to Pg and reveal a previously unknown mode of live neutrophil sequestration into macrophages during an infection.
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 | 0.000 |
| 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) | 0.000 | 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".