P055 <break /> Over-expression of IL-6 and OSM impacts the polarization of pro-fibrotic macrophages and the development of bleomycin-induced lung fibrosis
Bibliographic record
Abstract
Introduction: The increased polarization of pro-fibrotic M2 macrophages has been associated with the progression of many fibrotic disorders. Although recent evidence indicates that the pleiotropic gp130 cytokines, IL-6 and Oncostatin M (OSM) have a role in promoting alternative programming of macrophages, their specific role in lung fibrogenesis is not well understood. Here, we investigated the effect of adenoviral over-expression of IL-6 and OSM on bleomycin-induced lung injury and fibrosis. Methods: AdIL-6, AdOSM or a control adenovirus vector, alone or in combination with bleomycin were administered to C57BL6 mice by intratracheal intubation. Lungs of mice were extracted and analysed at day 7 (injury phase) or day 21 (fibrotic phase). Macrophage phenotype and function were assessed by IHC, arginase activity and gene expression. Lung fibrosis was assessed at day 21 (lung elastance, Masson’s trichrome and αSMA). Results: Lung function measurements demonstrated that pulmonary over-expression of OSM and IL-6 augmented bleomycin-induced increase in lung elastance. This finding was consistent with histopathological assessment of extracellular matrix and myofibroblast accumulation. At the injury phase, increased levels of IL-6 and OSM in the BALF of bleomycin-injured lungs were associated with higher levels of MCP-1 and pro-fibrotic M2 macrophages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.013 | 0.003 |
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".