Interstitial fluid obtained from kidney biopsy as new source of renal biomarkers
Bibliographic record
Abstract
INTRODUCTION: Development of renal biomarkers is required to improve on diagnostic accuracy, prognosis and prediction of response to therapy in renal disease. We describe a new method of obtaining from renal specimens a biologic fluid potentially enriched in secreted proteins. METHODS: A renal biopsy specimen was centrifuged, and the interstitial fluid (IF) obtained was evaluated by SELDI-ToF, 1D and 2D gel electrophoresis. Twelve spots were extracted from the 2D gel and characterized by MALDI-TOF-MS. RESULTS: The SELDI diagrams demonstrated abundant peptide peaks. One-dimensional gel electrophoresis demonstrated the presence of many bands indicating a diversity of proteins in the sample. Comparison of serum to IF demonstrated a number of bands that were not shared, suggesting that the IF is not a simple "replica" of plasma fluid. Employing 2D-PAGE, 418 spots were identified in the IF sample; 12 spots were selected and analyzed by mass spectrometry. CONCLUSIONS: We have described a novel technique to obtain a biologic fluid that contains a significant quantity and diversity of proteins from renal tissue. The procedure to obtain the fluid is simple and easily applicable to standard renal biopsy procedures. This fluid has the potential to identify informative proteins that are more concentrated than in any other renal biologic fluid previously analyzed and strictly related to renal pathophysiology. Future work includes the development of a clinical protocol to identify and validate informative biomarkers that have diagnostic and prognostic value.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".