ReviewInternational journal of molecular sciences2025
Cellular Phenotypic Transformation During Atherosclerosis: The Potential Role of miRNAs as Biomarkers.
Review in International journal of molecular sciences, 2025. 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.
- MicroRNAs as master regulators of macrophage function in atherosclerosis: From polarization to therapeutic potential.iScience · 2026Review
- [Effect of miR-155-5p regulating the TLR4/MAPK/NF-κB pathway on inflammatory response, coronary artery lesion and immune function in mice with Kawasaki disease].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Article
- Macrophage microRNAs integrating lipid metabolism and inflammation: Implications for atherosclerosis.Metabolism open · 2026Review
- A Comprehensive Review of Epigenetic Regulation of Vascular Smooth Muscle Cells During Development and Disease.Biomolecules · 2026Review
- Non-Coding RNA in Type 2 Diabetes Cardio-Renal Complications and SGLT2 Inhibitor Response.International journal of molecular sciences · 2025Review
- The Association of MicroRNA-21 with Carotid Artery Disease and Ischemic Stroke: From Pathophysiology to Clinical Implications and Potential Therapy.Medical sciences (Basel, Switzerland) · 2025Review
- LASSO Regression Analysis: Applications in Dyslipidemia and Cardiovascular Disease Research.Journal of lipid and atherosclerosis · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cellular phenotypic transformation is a key process that occurs during the development and progression of atherosclerosis. Within the arterial wall, endothelial cells, vascular smooth muscle cells, and macrophages undergo phenotypic changes that contribute to the pathogenesis of atherosclerosis. miRNAs have emerged as potential biomarkers for cellular phenotypic changes during atherosclerosis. Monitoring miR-155-5p, miR-210-3p, and miR-126-3p or 5p levels could provide valuable insights into disease progression, risk of complications, and response to therapeutic interventions. Moreover, miR-92a-3p's elevated levels in atherosclerotic plaques present opportunities for predicting disease progression and related complications. Baseline levels of miR-33a/b hold the potential for predicting responses to cholesterol-lowering therapies, such as statins, and the likelihood of dyslipidemia-related complications. Additionally, the assessment of miR-122-5p levels may offer insights into the efficacy of low-density-lipoprotein-lowering therapies. Understanding the specific miRNA-mediated regulatory mechanisms involved in cellular phenotypic transformations can provide valuable insights into the pathogenesis of atherosclerosis and potentially identify novel therapeutic targets.
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.