Genetic polymorphisms and the risk of progressive renal failure in elderly <scp>H</scp>ungarian patients
Bibliographic record
Abstract
The relationship between renal disease progression and genetic polymorphism of enzymes influencing endothelial function remains incompletely understood. We genotyped three cohorts of elderly Hungarian patients: 245 patients with end-stage renal disease (ESRD) on chronic hemodialysis (HD), 88 patients with mild chronic kidney disease (CKD), and 200 healthy controls. The underlying diagnoses of renal diseases were primary glomerulonephritis, interstitial nephritis, hypertension, diabetic nephropathy, and hereditary diseases. We examined genetic polymorphisms of eight candidate genes associated with endothelial function: endothelial constitutive nitric oxide synthase (ecNOS) T-786C, endothelin-1 G5727T, methylenetetrahydrofolate reductase (MTHFR) C677T, paraoxonase-1 Q192R and M55L, angiotensinogen M235T, angiotensin-converting enzyme (ACE) I/D and angiotensin II type 1 receptor A1166C gene. Six gene polymorphisms were detected by real-time polymerase chain reaction with melting-point analysis, and two via allele-specific amplification and gel electrophoresis. Control group patients were in Hardy-Weinberg equilibrium for all tested genotypes. In ESRD patients attributed to hypertension, the endothelin gene G5727T GG genotype occurred significantly less but GT genotype more frequently (P < 0.01 for both). In ESRD patients attributed to primary glomerulonephritis, more ACE DD and less ID genotypes were found (P < 0.02 for both) than in the controls. The underlying diagnosis may modify the association of genetic polymorphism and dialysis-dependent ESRD.
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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 | 0.001 |
| 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".