Biomimetic analyses of interactions between macrophages and palmar fascia myofibroblasts derived from Dupuytren's disease reveal distinct inflammatory cytokine responses
Bibliographic record
Abstract
Dupuytren's disease (DD) is a common and heritable fibrosis of the hand. It is characterized by the shortening and thickening of the palmar fascia into myofibroblastic nodules that can progress to palmar-digital contractures and permanent loss of dexterity. Molecular analyses of DD tissues and the presence of inflammatory cell infiltrates suggest a pathogenesis initiated by a proinflammatory fascial milieu that promotes myofibroblast activation and palmar fascia contractures. However, the relative contributions of vascular and/or tissue derived immune system cells and cytokine-sensitive stromal myofibroblasts to the development of this proinflammatory microenvironment are poorly understood. To gain insights into this process, we have developed and tested a collagen-based 3D tissue biomimetic co-culture system to assess paracrine interactions between THP-1-derived pro-inflammatory macrophages and primary human palmar fascia myofibroblasts (PFMs). We observed significant and reproducible impacts of collagen-adherent macrophage and PFM co-cultures on the cytokine gene expression profiles of these cells compared to their respective monocultures, and significant changes to the resulting cytokine milieu in their shared culture media, notably TNF and IL-6. Our findings are consistent with central roles for PFMs in cytokine production and immunoregulation of the pro-inflammatory milieu hypothesized to promote DD development.
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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 | 0.000 |
| 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".