Bibliographic record
Abstract
Rationale Discoidin Domain Receptor 1 (DDR1) is a tyrosine kinase activated by various types of collagen. Based on previous work showing increased DDR1 expression in bronchoalveolar lavage cells from patients with idiopathic pulmonary fibrosis, we hypothesized that DDR1 could be a key mediator during disease progression following lung injury. Objectives To investigate the response of DDR1 knockout and control mice to bleomycin‐induced lung injury. Methods Age‐ and gender‐matched C57/BL6 knockout and control mice received a single intratracheal instillation of 2U/kg bleomycin or saline, respectively. After 2 weeks, lung inflammation and fibrosis were assessed using immunohistochemistry, real time PCR, TUNEL assay, ELISA, FACS and Western blot analysis. Results Compared to control animals, DDR1‐null mice were largely protected against bleomycin injury. Collagen content as well as tenascin‐ C and fibrillin‐1 expression were significantly less increased in knockout than control mice. Myofibroblast expansion and apoptotic cell count were lower in DDR1‐null than control mice. Absence of inflammation in knockout mice was confirmed by lavage cell count and cytokine ELISA. Western blot analysis of injured lung tissue revealed that DDR1‐null mice failed to respond with an increase in p42/p44 and p38 MAPK pathway activation, which was observed in control mice. Conclusions Using a mouse strain lacking DDR1, our data provide compelling evidence that DDR1 expression is a prerequisite in the progression of lung inflammation and fibrosis. Blockade of DDR1 may therefore be a novel and attractive therapeutic intervention in patients with pulmonary fibrosis. Grant support: Canada Research Chair Program
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 | 0.001 | 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 | 0.000 |
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".