ReviewStem cell research & therapy2025
Quantifying extracellular vesicle heterogeneity: the effect of process conditions on protein cargo for skin therapy.
Review in Stem cell research & therapy, 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.
- Dielectrophoresis reveals stimulus-induced remodeling of insulin granule subpopulations.Biophysical journal · 2026Article
- Engineered exosomes for targeted bone regeneration: design, delivery, and functionalization.Cell and tissue banking · 2026Review
- Unveiling Exosomes and Microvesicles in Parkinson's Disease: Mechanistic Insights Into Cell Death Pathways and Therapeutic Potential.Molecular neurobiology · 2025Review
- Immunomodulatory and regenerative effects of human umbilical cord MSC-EVs in Cutaneous Leishmaniasis.Stem cell research & therapy · 2025Article
- Dielectrophoresis Reveals Stimulus-Induced Remodeling of Insulin Granule Subpopulations.bioRxiv : the preprint server for biology · 2025Article
- Unraveling the Multi-Omic Landscape of Extracellular Vesicles in Human Seminal Plasma.Biomolecules · 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
4 authors.
Funding
Abstract
Extracellular vesicles (EVs) contain a variety of proteins with anti-inflammatory and immunomodulatory properties that offer promising benefits in skin therapy applications. An influx of EV proteomic studies in recent years has created the opportunity for a detailed comparison of EV heterogeneity between studies in the context of therapeutic applications. Although several process conditions are known to cause variability in EVs, little has been done to quantify the impact of these factors on the nature of EV protein cargo. This review aims to both compile publicly available EV proteomics data and quantitatively estimate. the impact of process conditions on protein cargo-particularly in the context of skin therapy applications. Of roughly 400 articles, 52 relevant proteomic studies were identified within the last 15 years. Across studies, 40% of the 13,000 observed proteins were identified in only a single study. EVs in general were found to be highly variable, with mixed effects models only able to account for 25-60% of variance when considering factors such as EV source, medium, isolation method, LC-MS ionization, and protein search algorithm. Overall, MSC-derived EVs contained a greater fraction of proteins within pathways associated with wound healing and skin therapy (immune system, hemostasis, extracellular matrix organization, and cellular response to stress) as well as the most number of unique proteins when compared to all other analysed EVs. Although EVs are a promising tool within skin therapeutics, the overall variability in protein cargo underscores the need for standardized methodologies to fully elucidate the impact of process conditions on EV cargo.
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.