CD40 Signaling in B Cells Regulates the Expression of the Pim-1 Kinase Via the NF-κB Pathway
Bibliographic record
Abstract
The ability of CD40 signaling to regulate B cell growth, survival, differentiation, and Ig class switching involves many changes in gene expression. Using cDNA expression arrays and Northern blotting, we found that CD40 signaling increased the mRNA levels for pim-1, a protooncogene that encodes a serine/threonine protein kinase. Subsequent experiments showed that CD40 engagement also increased both Pim-1 protein levels and Pim-1 kinase activity in B cells. We then investigated the signaling pathways by which CD40 regulates Pim-1 expression and found that CD40 up-regulates Pim-1 primarily via the activation of NF-kappaB. Inhibiting the activation of NF-kappaB, either by treating cells with a chemical inhibitor, BAY11-7082, or by inducibly expressing a superrepressor form of IkappaBalpha, significantly impaired the ability of CD40 to increase Pim-1 protein levels. Because Pim-1 expression is associated with cell proliferation and survival, we asked whether this correlated with the ability of CD40 signaling to prevent anti-IgM-induced growth arrest in the WEHI-231 murine B cell line, a model for Ag-induced clonal deletion. We found that the anti-IgM-induced growth arrest in WEHI-231 cells correlated with a substantial decrease in Pim-1 levels. In contrast, culturing WEHI-231 cells with either anti-CD40 Abs or with the B cell mitogen LPS, both of which prevent the anti-IgM-induced growth arrest, also prevented the rapid decline in Pim-1 levels. This suggests that Pim-1 could regulate the survival and proliferation of B cells.
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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) | 0.001 | 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".