Transforming Growth Factor-β<sub>1</sub> in Balkan Endemic Nephropathy
Bibliographic record
Abstract
BACKGROUND/AIM: The aim of this study was to compare plasma and urine transforming growth factor-beta1 (TGF-beta1) levels in patients with different stages of Balkan endemic nephropathy (BEN) with those in patients with primary glomerulonephritis (GN) and healthy controls. METHODS: The study involved 47 patients with BEN (30 with manifest BEN and 17 in the early stage of BEN), 12 patients with GN and 10 healthy controls. Plasma and urine TGF-beta1 was assayed by enzyme-linked immunosorbent assay. RESULTS: The median plasma TGF-beta1 levels differed nonsignificantly between the groups (4,908-6,442 pg/ml), but individual plasma TGF-beta1 levels in BEN patients exhibited the highest dispersion. Median urinary TGF-beta1 excretion (pg/mg creatinine) was significantly higher in patient groups (manifest BEN: 203, early-stage BEN: 341, GN: 775) than in healthy controls (42). No correlation was found between plasma and urine TGF-beta1 levels or between plasma TGF-beta1 levels and creatinine clearance for any of the examined groups. CONCLUSION: Plasma TGF-beta1 levels in BEN patients extended over the widest range, but no significant differences were found between the median values for the groups. Median urinary TGF-beta1 excretion was significantly higher in patients with BEN and GN than in healthy controls.
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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 | 0.001 |
| 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".