Factors Influencing Basophilic Differentiation of HL-60 Cells
Bibliographic record
Abstract
Lineage-specific hematopoietins apparently act in concert with multipotent factors in an orderly sequence of growth and differentiation. We have used the human acute promyelocytic leukemia cell line HL-60 to examine basophilic differentiation, using radioenzymatic assay of histamine content as an end point. Recombinant human interleukin 1 (rhIL-1), rhIL-2, rhIL-4, and recombinant human alpha and gamma interferons did not stimulate basophilic differentiation either in the presence or absence of sodium butyrate, an important cofactor for induction of differentiation. In contrast, rhG-CSF (granulocyte colony-stimulating factor), rhGM (granulocyte-macrophage) CSF, rhIL-3, rhIL-5, nerve growth factor, conditioned medium (CM) from the hairy T cell leukemic line Mo, and nasal polyp epithelial CM stimulated significant increases in histamine content in HL-60 cells at day 5 in vitro. GM-CSF did not account for all of the basophilic differentiating activity in Mo-CM. The data suggest that a unique, lineage-specific, basophilic cell differentiation factor is produced by T cells and point to the possible diagnostic and therapeutic relevance of in situ hematopoietic mechanisms in human respiratory disease.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".