Homocysteine stimulates chemokine expression in the kidney via NF‐kappa B activation
Bibliographic record
Abstract
Hyperhomocysteinemia, a condition of elevated blood homocysteine levels, is a risk factor for cardiovascular disorders. Renal disease is an important factor causing hyperhomocysteinemia, the direct effect of homocysteine on the kidney is not well documented. One of the important features in kidney diseases is the infiltration of monocyte/macrophage in the kidney. Monocyte chemoattractant protein‐1 (MCP‐1) is a potent chemokine that stimulates monocyte migration into the tissue. The aim of this study was to investigate the effect of hyperhomocysteinemia on MCP‐1 expression and the underling mechanisms in rat kidneys. Hyperhomocysteinemia was induced in rats fed a high‐methionine diet. The nuclear factor kappa‐B (NF‐κB) activity, the levels of MCP‐1 mRNA and protein were significantly increased in the kidneys of hyperhomocysteinemic rats. Pretreatment of hyperhomocysteinemic rats with a NF‐κB inhibitor completely abolished hyperhomocysteinemia‐induced MCP‐1 expression in the kidney. This further confirmed the causative role of NF‐κB activation in hyperhomocysteinemia‐induced MCP‐1 expression. Taken together, these results suggest that diet‐induced hyperhomocysteinemia can stimulate chemokine expression in the kidney via NF‐κB activation. Such an inflammatory response may contribute to renal injury and chronic systemic inflammation associated 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".