Homocysteine Induces Monocyte Chemoattractant Protein-1 Expression in Hepatocytes Mediated via Activator Protein-1 Activation
Bibliographic record
Abstract
Hyperhomocysteinemia is characterized by abnormally high concentrations of homocysteine (Hcy) in the plasma. It is a metabolic disorder associated with dysfunction of several organs such as atherosclerosis, altered lipid metabolism, and liver injury. In this study we investigated the effect of Hcy on transcriptional regulation of monocyte chemoattractant protein-1 (MCP-1), a potent chemokine, expression in hepatocytes. Hyperhomocysteinemia was induced in rats by a high-methionine diet for 4 weeks. MCP-1 mRNA and protein levels were significantly elevated in the liver tissue homogenate and in hepatocytes of hyperhomocysteinemic rats. The role of transcription factors in MCP-1 expression was examined by electrophoretic mobility shift assay. Activation of activator protein (AP)-1 but not nuclear factor kappaB was detected in the liver tissue of those rats. Incubation of rat hepatocytes with Hcy (50-200 microm) caused a significant increase in AP-1 activation followed by an increase in intracellular MCP-1 mRNA expression and an elevation of MCP-1 protein secreted into the culture medium. Hcy markedly increased the DNA binding activity of human recombinant AP-1 (c-Fos and c-Jun proteins). The presence of a sulfhydryl group in Hcy was essential for Hcy-induced AP-1 activation. When hepatocytes were transfected with decoy AP-1 oligodeoxynucleotide to inhibit AP-1 activation, Hcy-induced MCP-1 mRNA expression was abolished. Further analysis revealed that increased hepatic MCP-1 expression was positively correlated with the serum MCP-1 level. These results suggest that Hcy-induced MCP-1 expression in the liver is mediated via AP-1 activation, which may contribute to chronic 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".