Evidence mapPaperPMID 41516041Full record

ReviewInternational journal of molecular sciences2025

Emerging Technologies for Exploring the Cellular Mechanisms in Vascular Diseases.

Debasis Sahu, Treena Ganguly, Avantika Mann, Yash Gupta, Logan R Van Nynatten, Douglas D Fraser

Abstract readReview
In one paragraph

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 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Debasis SahuScience Habitat, Ubioquitos Inc., 301-1554 Trossacks Ave, London, ON N5X 2P4, Canada.ORCID 0000-0003-1720-2680
Treena GangulyScience Habitat, Ubioquitos Inc., 301-1554 Trossacks Ave, London, ON N5X 2P4, Canada.
Avantika MannScience Habitat, Ubioquitos Inc., 301-1554 Trossacks Ave, London, ON N5X 2P4, Canada.
Yash GuptaDivision of Gastroenterology and Hepatology, Department of Medicine, Penn State University College of Medicine, Hershey, PA 17033, USA.ORCID 0000-0003-3002-1315
Logan R Van NynattenDivision of Critical Care Medicine, Department of Medicine, Western University, London, ON N6A 5W9, Canada.
Douglas D FraserChildren's Health Research Institute, London, ON N6C 2V5, Canada.ORCID 0000-0002-5635-3791

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vascular diseases (VDs) and cardiovascular diseases (CVDs) are the leading causes of morbidity and mortality worldwide. Current diagnostic and therapeutic approaches are limited by insufficient resolution and a lack of mechanistic understanding at the cellular level. Traditional imaging and clinical assays do not fully capture the dynamic molecular and structural complexities underlying vascular pathology. Recent technological innovations, including single-cell and spatial transcriptomics, super-resolution and photoacoustic imaging, microfluidic organ-on-chip platforms, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based gene editing, and artificial intelligence (AI), have created new opportunities for investigating the cellular and molecular basis of VDs. These techniques enable high-resolution mapping of cellular heterogeneity and functional alterations, facilitating the integration of large-scale data for biomarker discovery, disease modeling, and therapeutic development. This review focuses on evaluating the translational readiness, limitations, and potential clinical applications of these emerging technologies. Understanding the cellular and molecular mechanisms of VDs is essential for developing targeted therapies and precise diagnostics. Integrating single-cell and multiomics approaches highlights disease-driving cell types and gene programs. Optogenetics and organ-on-chip platforms allow for controlled manipulation and physiologically relevant modeling, while AI enhances data integration, risk prediction, and clinical interpretability. Future efforts should prioritize multi-center, large-scale validation studies, harmonization of assay protocols, and integration with clinical datasets and human samples. Multi-omics approaches and computational modeling hold promise for unraveling disease complexity, while advances in regulatory science and digital simulation (such as digital twins) may further accelerate personalized medicine in vascular disease research and treatment.

Indexed as

Vascular DiseasesAnimalsArtificial IntelligenceCardiovascular DiseasesDigital HealthGene EditingHumansMicrophysiological SystemsMultiomicsSpatial Transcriptomicsbiomarkerscardiovascular diseasemachine learningomicsprecision medicinesystems biology

Identifiers

PMID41516041
PMCPMC12785399

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.