Tumor necrosis factor-alpha expressed constitutively in erythroid cells or induced by erythropoietin has negative and stimulatory roles in normal erythropoiesis and erythroleukemia
Bibliographic record
Abstract
Binding of erythropoietin (EPO) to its receptor (EPOR) on erythroid cells induces the activation of numerous signal transduction pathways, including the mitogen-activated protein kinase Jun-N-terminal kinase (JNK). In an effort to understand the regulation of EPO-induced proliferation and JNK activation, we have examined the role of potential autocrine factors in the proliferation of the murine erythroleukemia cell line HCD57. We report here that treatment of these cells with EPO induced the expression and secretion of tumor necrosis factor alpha (TNF-alpha). EPO-dependent proliferation was reduced by the addition of neutralizing antibodies to TNF-alpha, and exogenously added TNF-alpha induced proliferation of HCD57 cells. EPO also could induce TNF-alpha expression in BAF3 and DA3 myeloid cells ectopically expressing EPOR. Addition of TNF-alpha activated JNK in HCD57 cells, and the activity of JNK was partially inhibited by addition of a TNF-alpha neutralizing antibody. Primary human and murine erythroid progenitors expressed TNF-alpha in either an EPO-dependent or constitutive manner. However, TNF-alpha had an inhibitory effect on both immature primary human and murine cells, suggestive that the proliferative effects of TNF-alpha may be limited to erythroleukemic cells. This study suggests a novel role for autocrine TNF-alpha expression in the proliferation of erythroleukemia cells that is distinct from the effect of TNF-alpha in normal erythropoiesis.
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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 | 0.000 |
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".