G-CSF preferentially supports the generation of gut-homing Gr-1high macrophages in M-CSF-treated bone marrow cells
Bibliographic record
Abstract
The G-CSF is best known for its activity in the generation and activation of neutrophils. In addition, studies on G-CSF(-/-) or G-CSFR(-/-) mice and BMC cultures suggested a role of G-CSF in macrophage generation. However, our understanding on the role of G-CSF in macrophage development is limited. Here, using in vitro BMC models, we demonstrated that G-CSF promoted the generation of Gr-1(high)/F4/80(+) macrophage-like cells in M-BMCs, likely through suppressing cell death and enhancing generation of Gr-1(high)/F4/80(+) macrophage-like cells. These Gr-1(high) macrophage-like cells produced "M2-like" cytokines and surface markers in response to LPS and IL-4/IL-13, respectively. Adoptive transfer of EGFP-expressing (EGFP(+)) M-BMCs showed a dominant, gut-homing phenotype. The small intestinal lamina propria of G-CSFR(-/-) mice also harbored significantly reduced numbers of Gr-1(high)/F4/80(+) macrophages compared with those of WT mice, but levels of Gr-1(+)/F4/80(-) neutrophil-like cells were similar between these mice. Collectively, these results suggest a novel function of G-CSF in the generation of gut-homing, M2-like macrophages.
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 | 0.001 |
| 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".