Programming of marginal zone B-cell fate by basic Krüppel-like factor (BKLF/KLF3)
Bibliographic record
Abstract
Splenic marginal zone (MZ) B cells are a lineage distinct from follicular and peritoneal B1 B cells. They are located next to the marginal sinus where blood is released. Here they pick up antigens and shuttle the load onto follicular dendritic cells inside the follicle. On activation, MZ B cells rapidly differentiate into plasmablasts secreting antibodies, thereby mediating humoral immune responses against blood-borne type 2 T-independent antigens. As Krüppel-like factors are implicated in cell differentiation/function in various tissues, we studied the function of basic Krüppel-like factor (BKLF/KLF3) in B cells. Whereas B-cell development in the bone marrow of KLF3-transgenic mice was unaffected, MZ B-cell numbers in spleen were increased considerably. As revealed in chimeric mice, this occurred cell autonomously, increasing both MZ and peritoneal B1 B-cell subsets. Comparing KLF3-transgenic and nontransgenic follicular B cells by RNA-microarray revealed that KLF3 regulates a subset of genes that was similarly up-regulated/down-regulated on normal MZ B-cell differentiation. Indeed, KLF3 expression overcame the lack of MZ B cells caused by different genetic alterations, such as CD19-deficiency or blockade of B-cell activating factor-receptor signaling, indicating that KLF3 may complement alternative nuclear factor-κB signaling. Thus, KLF3 is a driving force toward MZ B-cell maturation.
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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) | 0.002 | 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".