The Pre-B Cell Receptor Signaling for Apoptosis Is Negatively Regulated by FcγRIIB
Bibliographic record
Abstract
Many studies have shown that FcgammaRIIB is a negative regulator of B cell receptor signaling, and even though FcgammaRIIB is expressed through all developmental stages of the B cell lineage, its involvement in pre-B cell receptor (pre-BCR) signaling has not been examined. To investigate FcgammaRIIB function at the pre-B cell stage, we have established pre-BCR positive pre-B cell lines from normal mice and FcgammaRIIB-deficient mice, named PreBR and Fcgamma(-/-)PreBR, respectively. These cell lines are able to differentiate into immature B cells in vitro by removal of IL-7. In PreBR, apoptosis was moderately induced by F(ab')(2) anti-mu Ab, but not by intact anti-mu Ab. Phosphorylation of SH2-containing inositol 5-phosphatase (SHIP) and Dok, which are involved in FcgammaRIIB signaling, was induced by anti-mu cross-linking in PreBR. In contrast, apoptosis was strongly induced by both the F(ab')(2) and intact anti-mu Abs in Fcgamma(-/-)PreBR, and the level of phosphorylation of SHIP or Dok was much lower in Fcgamma(-/-)PreBR than those observed in PreBR. Restoration of FcgammaRIIB to Fcgamma(-/-)PreBR followed by anti-mu cross-linking blocked severe apoptosis, and up-regulated SHIP and Dok phosphorylation. The results demonstrate that FcgammaRIIB negatively regulates pre-BCR-mediated signaling for apoptosis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".