Extracellular Vesicles: Cell-Derived Biomarkers of Glomerular and Tubular Injury
Why this work is in the frame
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Bibliographic record
Abstract
Extracellular vesicles (EVs) are important mediators of intercellular communication. Since EVs are also released during pathological conditions, there has been considerable interest in their potential as sensitive biomarkers of cellular stress and/or injury. In the context of kidney disease, urinary EVs are promising indicators of glomerular and tubular damage. In the present review we discuss the role of urinary EVs in kidney health and disease. Our focus is to explore urinary large EVs (lEVs, often referred to as microparticles or microvesicles) as direct and noninvasive early biomarkers of renal injury. In this regard, studies have been demonstrating altered levels of urinary lEVs, especially podocyte-derived lEVs, preceding the decrease of renal function assessed by classical markers. In addition, we discuss the role of small EVs (sEVs, often referred to as exosomes) and their contents in kidney pathophysiology. Even though results concerning the production of sEVs during diseased conditions are varied, there has been a consensus on the importance of urinary sEV content assessment in kidney disease. These mediators, including EV-released miRNAs and mRNAs, are responsible for EV-mediated signaling in the regulation of renal cellular homeostasis, pathogenesis and regeneration. Finally, steps necessary for the validation of EVs as reliable markers will be discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it