Ectopic expression of interferon regulatory factor-1 potentiates granulocytic differentiation
Bibliographic record
Abstract
Numerous transcription factors allow haematopoietic cells to respond to lineage- and stage-specific cytokines and to act as their effectors. It is increasingly evident that the interferon regulatory factor-1 (IRF-1) transcription factor can selectively regulate different sets of genes depending on the cell type and/or the nature of cellular stimuli, evoking distinct responses in each. In the present study, we investigated mechanisms underlying the differentiation-inducing properties of granulocytic colony-stimulating factor (G-CSF) and whether IRF transcription factors are functionally relevant in myeloid differentiation. Both normal human progenitors and murine 32Dcl3 myeloblasts induced to differentiate along the granulocytic pathway showed an up-regulation of IRF-1 expression. Ectopic expression of IRF-1 did not abrogate the growth factor requirement of 32Dcl3 cells, although a small percentage of cells that survived cytokine deprivation differentiated fully to neutrophils. Moreover, in the presence of G-CSF, granulocytic differentiation of IRF-1-expressing cells was accelerated, as assessed by morphology and expression of specific differentiation markers. Down-modulation of c-Myb protein and direct stimulation of lysozyme promoter activity by IRF-1 were also observed. Conversely, constitutive expression of IRF-2, a repressor of IRF-1 transcriptional activity, completely abrogated the G-CSF-induced neutrophilic maturation. We conclude that IRF-1 exerts a pivotal role in granulocytic differentiation and that its induction by G-CSF represents a limiting step in the early events of differentiation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".