Lineage‐instructive functions of the <scp>E26</scp>‐transformation‐specific‐family transcription factor <scp>Spi‐C</scp> in immune cell development and disease
Bibliographic record
Abstract
Cell fate decisions during hematopoiesis are the consequence of a complex mixture of inputs from cell-intrinsic and cell-extrinsic factors. In rare cases, expression of a single transcription factor, or a few key factors, may be sufficient to dictate lineage differentiation in a precursor cell. The E26-transformation-specific-family transcription factor Spi-C has emerged as an example of a lineage-instructive factor involved in the generation of mature, specialized subsets of both myeloid and lymphoid cells. Spi-C can instruct differentiation of splenic precursors into red pulp macrophages responsible for phagocytosing senescent red blood cells. In the B cell compartment, Spi-C acts as a key regulator of cell fate decisions at the pro-B to pre-B cell stage and for plasma cell differentiation. Spi-C regulates key genes including Nfkb1, Bach2, Syk, and Blnk to regulate cell cycle entry and B cell differentiation. Here, we review the biology of the lineage-instructive transcription factor Spi-C and its contribution to mechanisms of disease in macrophages and B cells. This article is categorized under: Cancer > Molecular and Cellular Physiology Immune System Diseases > Molecular and Cellular Physiology Infectious Diseases > Genetics/Genomics/Epigenetics.
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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) | 0.001 | 0.001 |
| 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".