Plasma cell but not CD20-mediated B-cell depletion protects from bleomycin-induced lung fibrosis
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease associated with chronic inflammation and tissue remodelling leading to fibrosis, reduced pulmonary function, respiratory failure and death. Bleomycin (Blm)-induced lung fibrosis in mice replicates several clinical features of human IPF, including prominent lymphoid aggregates of predominantly B-cells that accumulate in the lung adjacent to areas of active fibrosis. We have shown previously a requirement for B-cells in the development of Blm-induced lung fibrosis in mice. To determine the therapeutic potential of inhibiting B-cell function in pulmonary fibrosis, we examined the effects of anti-CD20 B-cell ablation therapy to selectively remove mature B-cells from the immune system and inhibit Blm-induced lung fibrosis. Anti-CD20 B-cell ablation did not reduce fibrosis in this model; however, immune phenotyping of peripheral blood and lung resident cells revealed that anti-CD20-treated mice retained a high frequency of CD19 + CD138 + plasma cells. Interestingly, high levels of CD138 + cells were also identified in the lung tissue of patients with IPF, consistent with the mouse model. Treatment of mice with bortezomib, which depletes plasma cells, reduced the level of Blm-induced lung fibrosis, implicating plasma cells as important effector cells in the development and progression of pulmonary fibrosis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".