Increased oxidative stress in foam cells obtained from hemodialysis patients
Bibliographic record
Abstract
Premature atherosclerosis represents the main cause of mortality among end-stage renal disease patients (ESRD). Increased inflammation and oxidative stress are involved in initiation and progression of the atherosclerotic plaque. As foam cells are capable of producing significant amounts of inflammatory mediators and free radicals, we hypothesized that foam cells from uremic patients could produce more inflammation and oxidative stress than foam cells from normal people and be, somehow, involved in the accelerated atherosclerosis of uremia. To test this hypothesis, the levels of a few markers of inflammation and oxidative stress: Tumor necrosis factor-α, inducible nitric oxide synthase, malondialdehyde, nitric oxide by-products were measured in the supernatants of macrophage-derived foam cells cultures from 18 hemodialysis patients and 18 apparently healthy individuals controls. Malondialdehyde levels in the supernatant of cell cultures (macrophages stimulated or not with native and oxidized lipoprotein) were significantly increased in uremic patients; no statistically significant difference was found between the supernatant concentrations of nitric oxide by-products, inducible nitric oxide synthase activity, and tumor necrosis factor-α between patients and controls. Our results, obtained with human macrophages and macrophage-derived foam cells, are compatible with the theory that increased cellular oxidative stress and inflammatory activity in ESRD patients could accelerate the atherosclerotic process. The present culture protocol showed it is possible to use human mononuclear cells to evaluate the oxidative metabolism of foam cells, which are considered to be the initial step of atherosclerotic lesions.
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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".