Paraoxonase‐1 (PON1) activity as a risk factor for atherosclerosis in chronic renal failure patients
Bibliographic record
Abstract
Paraoxonase is a high-density lipoprotein-associated enzyme and has been shown to reduce the susceptibility to low-density lipoprotein peroxidation. This study aimed to investigate the activity of serum paraoxonase in uremic patients on hemodialysis (HD) and in the predialysis period, and to evaluate the correlations of vascular disease with paraoxonase activity. Thirty patients with chronic renal failure (CRF) undergoing HD (group 1), 30 patients with CRF under conservative treatment (group 2), and 30 healthy controls (group 3) were included. Basal, salt-stimulated, and arylesterase activity were tested by UV spectrophotometry. Serum lipid parameters were determined. B-Mode Doppler ultrasound was used to assess common carotid intima-media thickness (IMT). Basal paraoxonase, salt-stimulated, and arylesterase activity showed no significant difference between group 1 and group 2. However, it was significantly lower in group 1 and in group 2 than controls. Carotid IMT was significantly higher in group 1 than group 2 and both were significantly higher than controls. Basal paraoxonase-1 (PON1), salt-stimulated PON1, and arylesterase activity correlate with BUN, but only basal PON1 and salt-stimulated PON1 correlate with serum albumin. Linear regression showed that the most significant determinant of carotid IMT was PON1 arylesterase activity in group 1 and arylesterase activity and basal PON1 activity in group 2. Patients with CRF, whether under HD or conservative treatment, have reduced basal and stimulated paraoxonase activities, and this could be an important factor causing increased vascular disease in those patients. Modifying this factor can be of great value to protect against this common complication.
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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 | 0.000 | 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 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".