Mechanical Force Imprints Neutrophils to Orchestrate Pulmonary Homeostasis
Bibliographic record
Abstract
Abstract Neutrophils are the most abundant immune cells that constantly patrol and marginate into the vascular beds of multiple tissues to support immune homeostasis. The extent to which neutrophils undergo adaptation in response to diverse tissue microenvironments, and the resultant biological implications of such adaptation, remains unclear. Here, we performed intravital imaging, transcriptional, and functional analyses of neutrophils in different tissues. Our findings showed that the lung harbors a transcriptionally distinct neutrophil population with unique migratory behaviors. These resident-like neutrophils guarantee a rapid response upon infection and play an important role in maintaining the homeostasis of pulmonary vasculature. Notably, pulmonary neutrophils are imprinted by mechanical cues via the mechanosensitive ion channel Piezo1. Mice with conditional Piezo1 ablation lost lung-specific neutrophil signatures, and showed impaired lung capillary angiogenesis. Furthermore, these mice displayed increased susceptibility to airway infection. Collectively, these data identify mechanical sensing via Piezo1 as an important driver for tissue-specialized neutrophils that support pulmonary homeostasis.
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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 | 0.001 |
| 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".