Exosomal proteomic analysis reveals changes in the urinary proteome of rats with unilateral ureteral obstruction
Bibliographic record
Abstract
Congenital urinary tract obstruction (UTO) is a commonly noted disorder with the potential to cause permanent loss of renal function. Due to the possibility of spontaneous resolution, postnatal management strategies require lengthy and invasive surveillance methods to monitor the status of renal function and severity of obstruction. Here, a quantitative proteome analysis of urinary exosomes from weanling rats with surgically introduced UTO identifies a number of candidate biomarkers with the potential to improve diagnostic and prognostic methods for this disease. Using gel-assisted digestion coupled to liquid chromatography/tandem mass spectrometry (LC–MS/MS), 318 proteins were identified. Relative protein quantitation by spectral counting showed 190 proteins with significant changes in abundance due to either partial or complete obstruction. Numerous proteins identified here have been shown to be similarly altered in abundance in other renal diseases that cause tubule apoptosis and interstitial fibrosis. Extrapolating the role of the proteins showing quantifiable changes in abundance here from other forms of renal disease suggests they have potential for clinical applicability as biomarkers of congenital UTO. Included in the list of identified proteins are markers of apoptosis, oxidative stress, fibrosis, inflammation, and tubular cell damage, which are commonly associated with UTO. This study therefore provides a number of candidate biomarkers that, following validation in children experiencing UTO, have the potential to improve postnatal management of this disease.
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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 | 0.000 |
| 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 | 0.001 |
| 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".