Homocysteine stimulates monocyte chemoattractant protein-1 expression in mesangial cells via NF-κB activation
Bibliographic record
Abstract
Hyperhomocysteinemia is regarded as an independent risk factor for cardiovascular disorders. Although renal dysfunction or failure is one of the important factors causing hyperhomocysteinemia, the role of homocysteine (Hcy) in the development of glomerulosclerosis is largely unknown. One of the key events in the pathogenesis of glomerulosclerosis is the infiltration of circulating monocytes into affected glomeruli. The objective of the present study was to investigate the effect of Hcy on the expression of monocyte chemoattractant protein-1 (MCP-1) in kidney mesangial cells and the mechanisms involved. Levels of MCP-1 and mRNA were significantly elevated in Hcy-treated rat mesangial cells. This increase was associated with activation of NF-kappaB as a result of increased phosphorylation of the inhibitor protein IkappaBalpha. Monocyte chemotactic activity in these cells was also enhanced. In addition, there was a significant elevation of superoxide anion produced by Hcy-treated cells, which preceded the increased phosphorylation of IkappaBalpha. Addition of superoxide dismutase or NF-kappaB inhibitors to the culture medium abolished Hcy-induced NF-kappaB activation and MCP-1 expression. Taken together, these results indicate that Hcy induced MCP-1 expression in mesangial cells. Such a process was mediated by oxidative stress and NF-kappaB activation. This may further aggravate renal function in patients with hyperhomocysteinemia.
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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 | 0.000 |
| 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".