Nintedanib regulates intestinal smooth muscle hyperplasia and phenotype in vitro and in TNBS colitis in vivo
Bibliographic record
Abstract
Chronic inflammation of the human intestine in Crohn's disease (CD) causes bowel wall thickening, which typically progresses to stricturing and a recurrent need for surgery. Current therapies have limited success and CD remains idiopathic and incurable. Recent evidence shows a key role of intestinal smooth muscle cell (ISMC) hyperplasia in stricturing, which is not targeted by current anti-inflammatory therapeutics. However, progression of idiopathic pulmonary fibrosis, resembling CD in pathophysiology, is controlled by the tyrosine kinase inhibitors nintedanib (NIN) or pirfenidone, and we investigated these drugs for their effect on ISMC. In a culture model of rat ISMC, NIN inhibited serum- and PDGF-BB-stimulated growth and cell migration, and promoted the differentiated phenotype, while increasing secreted collagen. NIN did not affect signaling through PDGF-Rβ or NFκB but did inhibit cytokine-induced expression of the pro-inflammatory cytokines IL-1β and TNFα, supporting a transcriptional level of control. In TNBS-induced colitis in mice, which resembles CD, NIN decreased ISMC hyperplasia as well as expression of TNFα and IL-1β, without effect in control animals. NIN also inhibited growth of human ISMC in response to human serum or PDGF-BB, which further establishes a broad range of actions of NIN that support further trial in human IBD.
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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 | 0.001 |
| 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".