Interactions of Hemopoietic Cytokines on Differentiation of HL-60 Cells
Bibliographic record
Abstract
Nerve growth factor (NGF) is a neurotropic polypeptide which has broad biological activity other than support of growth and survival of sympathetic, sensory and central neurons. NGF promotes rat mast cell hyperplasia in vivo and human granulopoiesis in vitro, selectively augmenting basophil/mast cell differentiation in the presence of T cells or conditioned medium derived from a human T cell line (Mo-CM), a source of granulocyte-macrophage colony-stimulating factor (GM-CSF). NGF also synergizes with GM-CSF to promote human basophil/mast cell differentiation in both methylcellulose and suspension cultures of myeloid progenitors. In the current studies, we examined the interactions of NGF and several cytokines considered to be involved in human basophil/mast cell and eosinophil growth and differentiation, including interleukin (IL)-3, IL-4, IL-5, GM-CSF and granulocyte colony-stimulating factor (G-CSF). NGF synergistically enhanced IL-5 induced dose-dependent increases in histamine content and basophilic cell differentiation of myeloid leukemic HL-60 cells, but was only additive to similar effects of IL-3. In contrast, IL-4 and G-CSF did not promote basophilic differentiation of HL-60 cells in the presence or absence of NGF. Various combinations of GM-CSF, G-CSF, IL-3, IL-4 and IL-5 could not reproduce the synergy observed between NGF and either IL-5 or GM-CSF. NGF appears to represent a class of lineage-specific co-factors, in this case being involved in GM-CSF- or IL-5-induced basophilic lineage differentiation, thus contributing to tissue inflammation or repair.
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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) | 0.000 | 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".