ArticleJournal of extracellular vesicles2025
Potential Role of Menstrual Fluid-Derived Small Extracellular Vesicle Proteins in Endometriosis Pathogenesiss.
Article in Journal of extracellular vesicles, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Extracellular Vesicles in Endometriosis: A Comprehensive Review of Biological Insights and Methodological Challenges.International journal of molecular sciences · 2026Review
- Menstrual Effluent in the Pathogenesis and Diagnosis of Endometriosis-A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Menstrual fluid-derived small extracellular vesicles: a novel reservoir with distinct molecular signatures and implications for endometriosis etiopathology.Human reproduction open · 2026Article
- Closing the evidence loop-membrane-lipid homeostasis and vesicular transport link DEHP exposure to endometriosis.Human genomics · 2025Article
- Non-Invasive Extracellular Vesicle Biomarkers in Endometriosis, Molecular Signatures Linking Pelvic Inflammation, Oocyte Quality, and IVF OutcomesCurrent issues in molecular biology · 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
8 authors.
Funding
Abstract
Endometriosis, a chronic debilitating disease affects 1 in 7-10 girls and women, who have symptoms of severe chronic pain and subfertility and significantly impacts the overall quality of life. Currently, no effective early diagnostic methods are available for early stages of endometriosis. We used menstrual fluid-derived small extracellular vesicles (MF-sEVs) from women with self-reported endometriosis (laparoscopically diagnosed, n = 8) and self-reported without endometriosis and no painful periods (n = 9). MF-sEVs were separated using differential ultracentrifugation and characterised using nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), Western Blot, flow cytometry, mass-proteomics analysis and functional assays. Spherical-shaped sEVs were identified with a median diameter of ∼120 nm, expressing sEV marker proteins. The MF-sEV proteins were classified as endometrial origin. Over 5000 proteins were identified, ∼77% of which were decreased whilst only 22 proteins (largely comprising immunoglobulins) were increased in endometriosis/MF-sEVs compared to control/MF-sEVs. Decreased proteins were involved in nitrogen compound metabolism, immune response, intracellular signal transduction, regulation of programmed cell death, maintenance of cell polarity and actin cytoskeleton organisation. Flow cytometry demonstrated a significant increase in CD86 expression (immune activation marker) in endometriosis/MF-sEVs. Mesothelial cells showed a significant decrease in cellular resistance and junctional protein expression. MF-sEVs are possible contributors to the pathogenesis of endometriosis and may have the potential for early detection of the disease.
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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.