Connective Tissue Growth Factor Is Crucial to Inducing a Profibrotic Environment in “Fibrosis-Resistant” Balb/c Mouse Lungs
Bibliographic record
Abstract
The individual susceptibility to pulmonary fibrosis (PF) remains a mystery, suggesting a role for genetic predisposition. The pathogenesis of PF involves a multitude of factors mediating crosstalk between various tissue components. Some factors, such as transforming growth factor beta, are recognized as key elements in the process, whereas the role of others, such as connective tissue growth factor (CTGF), is unclear. We investigated if Balb/c mice, known to be fibrosis resistant partly due to lack of CTGF induction upon stimulation with bleomycin, can be transformed into fibrosis-sensitive individuals by generation of a CTGF-rich environment using transient overexpression of CTGF by adenoviral gene transfer (AdCTGF). We show that AdCTGF is not sufficient to cause fibrosis, and that bleomycin challenge results in inflammation, but not fibrosis, in Balb/c mouse lungs. This inflammation is accompanied by lower levels of CTGF and tissue inhibitor of metalloproteinase-1 gene expression compared with fibrosis-prone C57BL/6 mice. However, concomitant administration of AdCTGF and bleomycin leads to a persistent upregulation of tissue inhibitor of metalloproteinase-1 gene and a significant fibrotic response in Balb/c similar to that in C57BL/6 mice. We propose that CTGF is an important mediator in the pathogenesis of PF in that it provides a local microenvironment in the lung that causes individual susceptibility. CTGF should be considered as a novel drug target and as a potential marker for identifying individuals at risk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".