An integrated global regulatory network of hematopoietic precursor cell self-renewal and differentiation
Bibliographic record
Abstract
Systematic study of the regulatory mechanisms of Hematopoietic Stem Cell and Progenitor Cell (HSPC) self-renewal is fundamentally important for understanding hematopoiesis and for manipulating HSPCs for therapeutic purposes. Previously, we have characterized gene expression and identified important transcription factors (TFs) regulating the switch between self-renewal and differentiation in a multipotent Hematopoietic Progenitor Cell (HPC) line, EML (Erythroid, Myeloid, and Lymphoid) cells. Herein, we report binding maps for additional TFs (SOX4 and STAT3) by using chromatin immunoprecipitation (ChIP)-Sequencing, to address the underlying mechanisms regulating self-renewal properties of lineage-CD34+ subpopulation (Lin-CD34+ EML cells). Furthermore, we applied the Assay for Transposase Accessible Chromatin (ATAC)-Sequencing to globally identify the open chromatin regions associated with TF binding in the self-renewing Lin-CD34+ EML cells. Mass spectrometry (MS) was also used to quantify protein relative expression levels. Finally, by integrating the protein-protein interaction database, we built an expanded transcriptional regulatory and interaction network. We found that MAPK (Mitogen-activated protein kinase) pathway and TGF-β/SMAD signaling pathway components were highly enriched among the binding targets of these TFs in Lin-CD34+ EML cells. The present study integrates regulatory information at multiple levels to paint a more comprehensive picture of the HSPC self-renewal mechanisms.
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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".