IL-13–regulated Macrophage Polarization during Granuloma Formation in an <i>In Vitro</i> Human Sarcoidosis Model
Bibliographic record
Abstract
The mechanisms underlying abnormal granuloma formation in patients with sarcoidosis are complex and remain poorly understood. A novel in vitro human granuloma model was used to determine the molecular mechanisms of granuloma genesis in patients with sarcoidosis in response to putative disease-causing mycobacterial antigens. Peripheral blood mononuclear cells (PBMCs) from patients with active sarcoidosis and from normal, disease-free control subjects were incubated for 7 days with purified protein derivative-coated polystyrene beads. Molecular responses, as reflected by differential expression of genes, extracellular cytokine patterns, and cell surface receptor expression, were analyzed. Unbiased systems biology approaches were used to identify signaling pathways engaged during granuloma formation. Model findings were compared with human lung and mediastinal lymph node gene expression profiles. Compared with identically treated PBMCs of control subjects (n = 5), purified protein derivative-treated sarcoidosis PBMCs (n = 6) were distinguished by the formation of cellular aggregates resembling granulomas. Ingenuity Pathway Analysis of differential expression gene patterns identified molecular pathways that are primarily regulated by IL-13, which promotes alternatively activated (M2) macrophage polarization. M2 polarization was further demonstrated by immunohistochemistry performed on the in vitro sarcoidosis granuloma-like structures. IL-13-regulated gene pathways were confirmed in human sarcoidosis lung and mediastinal lymph node tissues. The in vitro human sarcoidosis granuloma model provides novel insights into early granuloma formation, particularly IL-13 regulation of molecular networks that regulate M2 macrophage polarization. M2 macrophages are predisposed to aggregation and multinucleated giant cell formation, which are characteristic features of sarcoidosis granulomas. Clinical trial registered with www.clinicaltrials.gov (NCT01857401).
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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 | 0.000 |
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".