Endothelin-1 Induces NF-κB via Two Independent Pathways in Human Renal Tubular Epithelial Cells
Bibliographic record
Abstract
BACKGROUND: Endothelin-1 (ET-1) is a major transcriptional activator of renal proximal tubule cells acting in an autocrine and paracrine manner. In animal studies, ET-1 has been implicated in progressive renal interstitial fibrosis by promoting gene expression, possibly via the inflammatory NF-kappaB signal pathway. While ET-1-dependent mechanisms of signal transduction have been studied mainly in tumor cell lines, we analyzed the mechanism of ET-1-induced, NF-kappaB-mediated target gene activation in proximal tubule cells. METHODS: Human renal proximal tubule cells were stimulated with ET-1 and gene expression analyzed by protein microarray, Western blot, non-radioactive electromobility shift assay, and quantitative real-time polymerase chain reaction. RESULTS: Activation of NF-kappaB occurs only via an ET-1-specific type A receptor (not type B as in animals). Induction can be blocked by bosentan, and endothelin-A but not endothelin-B receptor-specific antagonists. Protein microarray screening shows activation of two independent cascades (via the endothelin-A receptor, or via diacylglycerol) leading to NF-kappaB induction. The independent induction is also reflected by target gene expression such as the vascular cell adhesion molecule-1, interleukin-6, and fractalkine at different time points. CONCLUSION: Thus prohibiting ET-1-mediated gene transcription necessitates blocking of NF-kappaB and diacylglycerol signal transduction in proximal tubule cells.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".