The Antidepressant Mirtazapine Rapidly Shifts Hepatic B Cell Populations and Functional Cytokine Signatures in the Mouse
Bibliographic record
Abstract
Introduction B cells are important regulators of both adaptive and innate immunity. The normal liver contains significant numbers of B cells, and their numbers increase dramatically in immune-mediated liver diseases. Our previous observations suggest a hepatoprotective effect of the antidepressant mirtazapine in human and experimental immune-mediated liver disease. Therefore, we performed a series of experiments to determine the impact of mirtazapine treatment on hepatic B cell homeostasis, as reflected by B cell number, trafficking and phenotype using flow cytometry (FCM) and intravital microscopy (IVM) analysis. Mirtazapine treatment rapidly induced a significant reduction in total hepatic B cell numbers, paralleled by a compositional shift in the predominant hepatic B cell subtype from B2 to B1. This shift in hepatic B cells induced by mirtazapine treatment was associated with a striking increase in total hepatic levels of the chemokine CXCL10, and increased production of CXCL10 by hepatic macrophages and dendritic cells. Furthermore, mirtazapine treatment led to an upregulation of CXCR3, the cognate chemokine receptor for CXCL10, on hepatic B cells that remained in the liver post-mirtazapine. A significant role for CXCR3 in the hepatic retention of B cells post-mirtazapine was confirmed using CXCR3 receptor blockade. In addition, B cells remaining in the liver post-mirtazapine produced lower amounts of the proinflammatory Th1-like cytokines IFNγ, TNFα, and IL-6, and increased amounts of the Th2-like cytokine IL-4, after stimulation in vitro. Conclusion Mirtazapine treatment rapidly alters hepatic B cell populations, enhancing hepatic retention of CXCR3-expressing innate-like B cells that generate a more anti-inflammatory cytokine profile. Mirtazapine-induced hepatic B cell shifts could potentially represent a novel therapeutic approach to immune-mediated liver diseases characterized by B cell driven pathology.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".