Regulation of Follicular B Cell Differentiation by the Related E26 Transformation-Specific Transcription Factors PU.1, Spi-B, and Spi-C
Bibliographic record
Abstract
Splenic B-2 cells can be divided into two major subsets: follicular (FO) and marginal zone (MZ) B cells. FO and MZ B cells are generated from immature transitional B cells. Few transcription factors have been identified that regulate FO B cell differentiation. The highly related proteins PU.1, Spi-B, and Spi-C are transcription factors of the E26-transformation-specific family and are important for B cell differentiation and function. To determine whether these proteins play a role in the differentiation of FO B cells, we performed a detailed analysis of splenic B cells in mice with inactivating mutations in the genes encoding PU.1 (Sfpi1) or Spi-B (Spib). Sfpi1(+/-) Spib(-/-) (PUB) mice had a 9-fold reduction in the frequency of CD23(+) FO B cells compared with that of wild-type mice. In contrast, PUB mice had a 2-fold increase in the frequency of MZ B cells that was confirmed by immunofluorescence staining. Expression of Spi-C in Eμ-Spi-C transgenic PUB mice partially rescued frequencies of CD23(+) B cells. Gene expression analysis, in vitro reporter assays, and chromatin immunoprecipitation experiments showed that transcription of the Fcer2a gene encoding CD23 is activated by PU.1, Spi-B, and Spi-C. These results demonstrate that FO B cell differentiation is regulated by the E26-transformation-specific transcription factors PU.1, Spi-B, and Spi-C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 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".