P039 <break /> Modulation of Fibrocyte and Chemokine levels in Balb/C Mouse Lung upon Transient Pulmonary Over-expression of Oncostatin M
Bibliographic record
Abstract
Accumulation of extracellular matrix in lung diseases involves various cytokines and chemokines and accumulation of myofibroblasts which could be derived from local sources or from circulating fibrocytes (CD45+col1+ in mice). We have been examining TGFbeta-independent pathways to lung fibrosis in mouse models, and previously shown that the gp130 cytokine Oncostatin M induces extracellular matrix in mouse lungs, associated with robust STAT3 cell signaling activation. Here we determine if fibrocytes and chemokines for fibrocytes are induced by OSM in Balb/C mice. Using endotracheal administration of an Ad vector (AdOSM) for transient pulmonary overexpression of OSM, and comparison to control vector, we found increases in collagen staining, and elevated neutrophil and macrophage numbers in broncho-alveolar lavage fluid at day 7. These effects were independent of IL-13 as assessed in knockout mice. CD45+col1+ fibrocyte numbers were elevated at day 7 due to AdOSM, and maintained at Day 14, whereas other CD45+ cells were not. At Day 7, contrary to expected, the fibrocyte chemotactic factor SDF-1/CXCL-12 was suppressed by Oncostatin M. Upon examining other fibrocyte chemokines, mRNA for MCP-5/CCL-12, as well as mRNA for MCP-1/CCL-2 and MCP-3/CCL-7 were elevated in total lung of AdOSM-treated mice. Thus, Oncostatin M can induce extracellular matrix remodeling and inflammation in an IL-13-independent manner in Balb/C mice as well as inducing fibrocyte accumulation that is associated with elevation of MCP-1, 3 and MCP-5/CCL-12 mRNA rather than SDF-1/CXCL-12. Supported by CIHR.
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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".