Urinary biomarkers of chronic allograft nephropathy
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: Chronic allograft nephropathy (CAN) is widely accepted as the leading cause of renal allograft loss after the first year post transplantation. This study aimed to identify urinary biomarkers that could predict CAN in transplant patients. EXPERIMENTAL DESIGN: The study included 34 renal transplant patients with histologically proven CAN and 36 renal transplant patients with normal renal function. OrbiTrap MS was utilized to analysis a urinary fraction in order to identify other members of a previously identified biomarker tree . This novel biomarker pattern offers the potential to distinguish between transplant recipients with CAN and those with normal renal function. RESULTS: The primary node of the biomarker pattern was reconfirmed as β2 microglobulin. Three other members of this biomarker pattern were identified: neutrophil gelatinase-associated lipocalin, clusterin, and kidney injury biomarker 1. Significantly higher urinary concentrations of these proteins were found in patients with CAN compared to those with normal kidney function. CONCLUSIONS AND CLINICAL RELEVANCE: While further validation in a larger more-diverse patient population is required to determine if this biomarker pattern provides a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly demonstrates the biomarkers' ability to stratify patients based on transplant function.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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