Endogenous Granulocyte-Macrophage Colony-Stimulating Factor Overexpression In Vivo Results in the Long-Term Recruitment of a Distinct Dendritic Cell Population with Enhanced Immunostimulatory Function
Bibliographic record
Abstract
GM-CSF is critical for dendritic cell (DC) survival and differentiation in vitro. To study its effect on DC development and function in vivo, we used a gene transfer vector to transiently overexpress GM-CSF in mice. We found that up to 24% of splenocytes became CD11c+ and the number of DC increased up to 260-fold to 3 x 10(8) cells. DC numbers remained substantially elevated even 75 days after treatment. The DC population was either CD8alpha+CD4- or CD8alpha-CD4- but not CD8alpha+CD4+ or CD8alpha-CD4+. This differs substantially from subsets recruited in normal or Flt3 ligand-treated mice or using GM-CSF protein injections. GM-CSF-recruited DC secreted extremely high levels of TNF-alpha compared with minimal amounts in DC from normal or Flt3 ligand-treated mice. Recruited DC also produced elevated levels of IL-6 but almost no IFN-gamma. GM-CSF DC had robust immune function compared with controls. They had an increased rate of Ag capture and caused greater allogeneic and Ag-specific T cell stimulation. Furthermore, GM-CSF-recruited DC increased NK cell lytic activity after coculture. The enhanced T cell and NK cell immunostimulation by GM-CSF DC was in part dependent on their secretion of TNF-alpha. Our findings show that GM-CSF can have an important role in DC development and recruitment in vivo and has potential application to immunotherapy in recruiting massive numbers of DC with enhanced ability to activate effector cells.
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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".