ArticleScientific reports2018
Analysis of Combined Transcriptomes Identifies Gene Modules that Differentially Respond to Pathogenic Stimulation of Vascular Smooth Muscle and Endothelial Cells.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Targeted NADJournal of controlled release : official journal of the Controlled Release Society · 2024Article
- Unlocking the secrets of aging: Epigenetic reader BRD4 as the target to combatting aging-related diseases.Journal of advanced research · 2024Review
- SREBP1 regulatesMolecular therapy. Nucleic acids · 2022Article
- A hierarchical and collaborative BRD4/CEBPD partnership governs vascular smooth muscle cell inflammation.Molecular therapy. Methods & clinical development · 2021Article
- Integrated network analysis reveals new genes suggesting COVID-19 chronic effects and treatment.Briefings in bioinformatics · 2021Article
- Engineered Microenvironment for Manufacturing Human Pluripotent Stem Cell-Derived Vascular Smooth Muscle Cells.Stem cell reports · 2019Article
- Laser Capture Microdissection and RNA-Seq Analysis: High Sensitivity Approaches to Explain Histopathological Heterogeneity in Human Glioblastoma FFPE Archived Tissues.Frontiers in oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Smooth muscle cells (SMCs) and endothelial cells (ECs) are vital cell types composing the vascular medial wall and the atheroprotective inner lining, respectively. Current treatments for cardiovascular disease inhibit SMC hyperplasia but compromise EC integrity, predisposing patients to thrombosis. Therapeutics targeting SMCs without collateral damage to ECs are highly desirable. However, differential (SMC versus EC) disease-associated regulations remain poorly defined. We conducted RNA-seq experiments to investigate SMC-versus-EC differential transcriptomic dynamics, following treatment of human primary SMCs and ECs with TNFα or IL-1β, both established inducers of SMC hyperplasia and EC dysfunction. As revealed by combined SMC/EC transcriptomes, after TNFα or IL-1β induction, 174 and 213 genes respectively showed greater up-regulation in SMCs than in ECs (SMC-enriched), while 117 and 138 genes showed greater up-regulation in ECs over SMCs (EC-enriched). Analysis of gene interaction networks identified central genes shared in the two SMC-enriched gene sets, and a distinct group of central genes common in the two EC-enriched gene sets. Significantly, four gene modules (subnetworks) were identified from these central genes, including SMC-enriched JUN and FYN modules and EC-enriched SMAD3 and XPO1 modules. These modules may inform potential intervention targets for selective blockage of SMC hyperplasia without endothelial damage.
Indexed as
Identifiers
What OpenQuestion holds
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.