Extracellular vesicles and their content in the context of polycystic ovarian syndrome and endometriosis: a review
Bibliographic record
Abstract
Extracellular vesicles (EVs), particles enriched in bioactive molecules like proteins, nucleic acids, and lipids, are crucial mediators of intercellular communication and play key roles in various physiological and pathological processes. EVs have been shown to be involved in ovarian follicular function and to be altered in two prevalent gynecological disorders; polycystic ovarian syndrome (PCOS) and endometriosis.Ovarian follicles are complex microenvironments where folliculogenesis takes place with well-orchestrated interactions between granulosa cells, oocytes, and their surrounding stromal cells. Recent research unveiled the presence of EVs, including exosomes and microvesicles, in the follicular fluid (FFEVs), which constitutes part of the developing oocyte's microenvironment. In the context of PCOS, a multifaceted endocrine, reproductive, and metabolic disorder, studies have explored the dysregulation of these FFEVs and their cargo. Nine PCOS studies were included in this review and two miRNAs were commonly reported in two different studies, miR-379 and miR-200, both known to play a role in female reproduction. Studies have also demonstrated the potential use of EVs as diagnostic tools and treatment options.Endometriosis, another prevalent gynecological disorder characterized by ectopic growth of endometrial-like tissue, has also been linked to aberrant EV signaling. EVs in the peritoneal fluid of women with endometriosis carry molecules that modulate the immune response and promote the establishment and maintenance of endometriosis lesions. EVs derived from endometriosis lesions, serum and peritoneal fluid obtained from patients with endometriosis showed no commonly reported biomolecules between the eleven reviewed studies. Importantly, circulating EVs have been shown to be potential biomarkers, also reflecting the severity of the pathology.Understanding the interplay of EVs within human ovarian follicles may provide valuable insights into the pathophysiology of both PCOS and endometriosis. Targeting EV-mediated communication may open avenues for novel diagnostic and therapeutic approaches for these common gynecological disorders. More research is essential to unravel the mechanisms underlying EV involvement in folliculogenesis and its dysregulation in PCOS and endometriosis, ultimately leading to more effective and personalized interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".