Proteomic signatures of podocyte injury are reflected in urinary extracellular vesicles in pediatric nephrotic syndrome
Bibliographic record
Abstract
Abstract Idiopathic nephrotic syndrome (NS) is a common glomerulopathy in children and presents with significant proteinuria. There are no reliable clinical or biochemical markers of disease relapse, or prognosis. Extracellular vesicles (EVs) are small, membrane-bound biological effectors released from stressed cells. We previously showed increases in podocyte-specific urinary EVs from children with disease relapse in NS, with numbers returning to near-zero in remission. Herein, we have expanded this work to evaluate puromycin aminonucleoside (PAN) injury by characterizing proteomic signatures of podocytes and their EVs in vitro . In addition, we performed data-independent proteomic analysis (DIA) to characterize changes in signatures of EVs from pediatric patients with active NS versus remission. Our key findings reveal PAN-injured podocytes increase large EV (LEV) secretion in vitro ; moreover, DIA uncovered changes in cellular and LEV proteomes that were also observed in urinary LEVs from patients with active disease. Urinary LEV proteomes from children with active NS were significantly different than those in remission, highlighted by 645 and 240 unique proteins associated with disease or remission, respectively. This foundational work provides the impetus for a larger, prospective biomarker study aimed at identifying EV-specific proteins associated with relapse versus remission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".