Uraemic plasma decreases the expression of ABCA1, ABCG1 and cell-cycle genes in human coronary arterial endothelial cells
Bibliographic record
Abstract
BACKGROUND: Uraemia is associated with endothelial dysfunction, but the effect of uraemic plasma on the gene expression pattern of human coronary arterial endothelial cells (HCAEC) has never been defined. METHODS: HCAECs were exposed for 48 h to a culture medium supplemented with 20% uraemic vs normal plasma. We extracted mRNA and hybridized it onto Affymetrix HG-U133 Plus2 microarrays. We validated our findings for five genes of interest by real-time PCR and performed evaluations of cell proliferation and apoptosis in HCAECs exposed to uraemic vs normal plasma. RESULTS: Six genes involved in the regulation of cell-cycle progression (CDK-1, topoisomerase II, PDZ-binding kinase, CDCA1, protein SDP35, E2F transcription factor 8) and two genes of the cholesterol efflux system (ABCA1 and ABCG1) were down-regulated in HCAECs exposed to uraemic plasma (>1.75-fold change vs normal). Real-time PCR confirmed the down-regulation observed in the microarray experiment. Cell proliferation was significantly decreased in HCAECs exposed to uraemic vs normal plasma for 48 h (86 vs 95% of serum-starved control, P = 0.006). Exposure to uraemic plasma for 48 h was associated with increased apoptosis of HCAEC as compared with normal plasma (7.7 vs 2.8%, P < 0.001), a phenomenon that was further enhanced when oxidized LDLs (150 microg protein/ml) were added to the medium containing uraemic plasma (16.9 vs 7.7%, P < 0.001). CONCLUSIONS: The down-regulation of genes involved in cell-cycle progression and cholesterol efflux from HCAECs exposed to uraemic conditions could contribute to enhancing endothelial dysfunction and atherosclerosis in patients with chronic renal failure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".