ReviewAmerican journal of respiratory cell and molecular biology2025
Deciphering the Complexities of Pulmonary Hypertension: The Emergent Role of Single-Cell Omics.
Review in American journal of respiratory cell and molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Roles of Lipid Metabolism in Pulmonary Hypertension: Friend or Foe?Biomolecules · 2025Review
- The devil is in the details: addressing lung cell heterogeneity in sugen-hypoxia rats and its relevance to pulmonary arterial hypertension.Cardiovascular research · 2025Article
- Single-cell multi-omics in biliary tract cancers: decoding heterogeneity, microenvironment, and treatment strategies.Molecular biomedicine · 2025Review
- Pathophysiology of Pulmonary Arterial Hypertension: Focus on Vascular Endothelium as a Potential Therapeutic Target.International journal of molecular sciences · 2025Review
- Emerging Mechanistic Insights and Therapeutic Strategies for Pulmonary Arterial Hypertension: A Focus on Right Ventricular Dysfunction and Novel Treatment Pathways.Biomedicines · 2025Review
- Emerging biomaterials and bio-nano interfaces in pulmonary hypertension therapy: transformative strategies for personalized treatment.Frontiers in bioengineering and biotechnology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Expanding upon the critical advancements brought forth by single-cell omics in pulmonary hypertension (PH) research, this review delves deep into how these technologies have been piloted in a new era of understanding this complex disease. By leveraging the power of single-cell transcriptomics (i.e., single-cell RNA sequencing), researchers can now dissect the complicated cellular ecosystem of the lungs, examining the key players such as endothelial cells, smooth muscle cells, pericytes, and immune cells and their unique roles in the pathogenesis of PH. This more granular view is beyond the limitations of traditional bulk analysis, allowing for the identification of novel therapeutic targets previously obscured in the aggregated data. Connectome analysis based on single-cell omics of the cells involved in pathological changes can reveal a clearer picture of the cellular interactions and transitions in the cellular subtypes. Furthermore, the review acknowledges the challenges that lie ahead, including the need to enhance the resolution of single-cell RNA sequencing to capture even finer details of cellular changes, overcoming logistical barriers in processing human tissue samples, and the necessity of integrating diverse omics approaches to fully comprehend the molecular underpinnings of PH. The promise of these single-cell technologies is immense, offering the potential for targeted drug development and the discovery of biomarkers for early diagnosis and disease monitoring. Through these advancements, the field moves closer to realizing the goal of precision medicine for patients with PH.
Indexed as
Identifiers
What Socratic 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 Socratic graph.