ReviewBiology2024
Extracellular Vesicles: Diagnostic and Therapeutic Applications in Cancer.
Review in Biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Investigation Into the Collection and Isolation Workflows of Extracellular Vesicles From Tears.Journal of extracellular biology · 2026Article
- The Microbiome-Mitochondria-Extracellular Vesicle Axis in HPV Persistence and Cervical Carcinogenesis.Genes · 2026Review
- The synergistic applications of organoids and exosomes in disease modeling and disease treatment.Molecular biology reports · 2026Review
- Biological Systems Depend on Communication Over Distances: A Review of the Fundamental Mechanisms, Associated challenges, and the Potential Effect of the Constrained Disorder Principle.Acta biotheoretica · 2026Review
- Review
- Hypoxia-Induced Extracellular Vesicles and Non-Coding RNAs in Cancer: A Systematic Review of Tumor Dynamics and Therapeutic Implications in Preclinical Animal Models.Biomedicines · 2025Review
- Effects of small extracellular vesicles isolated from pleural effusion on lung cancer cell proliferation and migration.Human cell · 2025Article
- Advancing the potential of nanoparticles for cancer detection and precision therapeutics.Medical oncology (Northwood, London, England) · 2025Review
- Exosomes in early lung cancer diagnostics: the current state of progress made and prospects.Frontiers in cell and developmental biology · 2025Review
- Interplay of circular RNAs in gastric cancer - a systematic review.Frontiers in systems biology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, knowledge of cell-released extracellular vesicle (EV) functions has undergone rapid growth. EVs are membrane vesicles loaded with proteins, nucleic acids, lipids, and bioactive molecules. Once released into the extracellular space, EVs are delivered to target cells that may go through modifications in physiological or pathological conditions. EVs are nano shuttles with a crucial role in promoting short- and long-distance cell-cell communication. Comprehension of the mechanism that regulates this process is a benefit for both medicine and basic science. Currently, EVs attract immense interest in precision and nanomedicine for their potential use in diagnosis, prognosis, and therapies. This review reports the latest advances in EV studies, focusing on the nature and features of EVs and on conventional and emerging methodologies used for their separation, characterization, and visualization. By searching an extended portion of the relevant literature, this work aims to give a summary of advances in nanomedical applications of EVs. Moreover, concerns that require further studies before translation to clinical applications are discussed.
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.