ArticleInternational journal of molecular sciences2024
Differentiation and Growth-Arrest-Related lncRNA (
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- A Comprehensive Review of Epigenetic Regulation of Vascular Smooth Muscle Cells During Development and Disease.Biomolecules · 2026Review
- Genenames.org: the HGNC and PGNC resources in 2026.Nucleic acids research · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Vascular smooth muscle cells (SMCs) can transition between a quiescent contractile or "differentiated" phenotype and a "proliferative-dedifferentiated" phenotype in response to environmental cues, similar to what in occurs in the wound healing process observed in fibroblasts. When dysregulated, these processes contribute to the development of various lung and cardiovascular diseases such as Chronic Obstructive Pulmonary Disease (COPD). Long non-coding RNAs (lncRNAs) have emerged as key modulators of SMC differentiation and phenotypic changes. In this study, we examined the expression of lncRNAs in primary human pulmonary artery SMCs (hPASMCs) during cell-to-cell contact-induced SMC differentiation. We discovered a novel lncRNA, which we named Differentiation And Growth Arrest-Related lncRNA (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.