Glucocorticoids enhance neutrophil survival via G-CSF
Bibliographic record
Abstract
Abstract Glucocorticoids promote the survival of neutrophils, the mechanism of which is not clear. We found that glucocorticoids and proinflammatory cytokines synergistically induced G-CSF in primary human neutrophils and macrophages and multiple cell lines. The induction is at the transcriptional level and mediated by NF-κB and the glucocorticoid receptor as demonstrated by site-directed mutagenesis and ChIP assays. In both an LPS-induced airway inflammation model and a chronic OVA-induced airway inflammation model, BAL G-CSF, but not KC or IL-6, was resistant to glucocorticoid suppression. Glucocorticoids together with NF-κB inhibitors, but not either agent alone, decreased BAL G-CSF and neutrophils. Neutrophils from G-CSFR null mice, in contrast to those from wild type animals, were no longer protected by glucocorticoids. Furthermore, knockdown of G-CSF abolished the ability of BEAS 2B bronchial epithelial cells to protect neutrophils from spontaneous apoptosis. These data identify G-CSF as a potential target to increase glucocorticoid sensitivity in neutrophil-driven inflammatory conditions such as chronic obstructive pulmonary disease and neutrophil-dominant endotypes of asthma.
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) | 0.001 | 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".