Frontline: IL‐7 does not prevent pro‐B/pre‐B cell maturation to the immature/sIgM<sup>+</sup> stage
Bibliographic record
Abstract
IL-7 plays many fundamental roles during murine B lineage development. One reported function is to maintain progenitors in a developmentally immature state by preventing differentiation to the surface IgM (sIgM)(+) stage. Withdrawal of IL-7 from cultures has been shown to lead to increases in mature traits such as RAG expression, IgL rearrangements and expression of sIgM. These observations have been interpreted as an inductive event promoting the differentiation of progenitor cells. In contrast to this, we reproducibly observe sIgM(+) cells that have differentiated in cultures containing IL-7. We find that sIgM(+) cells arise as a normal consequence when B lineage cells are cultured in the presence of IL-7. However, these cells are short-lived and are quickly replaced by newly emerging sIgM(+) cells that differentiate from sIgM(-) progenitors. Withdrawal of IL-7 from these cultures only prevents the survival and proliferation of CD2(-)sIgM(-) pro-B cells but does not change the number of cells that differentiate to the sIgM(+) stage. This changes the ratio of sIgM(-):sIgM(+) cells and results only in an apparent maturation of the culture as a whole. Therefore withdrawal of IL-7 from these cultures acts as a selection event, not an induction event, for populations that are normally present.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.116 | 0.052 |
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".