Small interfering RNA knocks down heat shock factor-1 (HSF-1) and exacerbates pro-inflammatory activation of NF-κB and AP-1 in vascular smooth muscle cells
Bibliographic record
Abstract
OBJECTIVES: Heat shock and elevated expression of heat shock proteins suppress activation of the pro-inflammatory transcription factor NF-kappaB. We hypothesized that knocking down the expression of heat shock factor-1 (HSF-1) with RNAi technology would exacerbate angiotensin (Ang) II-induced inflammatory injury in vascular smooth muscle cells (VSMC). METHODS: Rat aorta A10 cells and human intestinal smooth muscle cells were grown without transfection or with transfection with HSF-1 small interfering RNA (siRNA), or negative control siRNA. Cells were stimulated with Ang II (100 nM) to activate the NF-kappaB signaling pathway. RESULTS: HSF-1 siRNA significantly knocked down HSF-1 expression, and one of the downstream heat shock proteins (Hsp), Hsp27, in both cells lines. HSF-1 siRNA also affected cells stressed with heat shock or Ang II treatment. Ang II induced activation of NF-kappaB and AP-1 in untransfected VSMCs, however, Ang II induced significantly higher activities of these pro-inflammatory transcription factors in HSF-1 siRNA transfected cells. Control siRNA had no apparent effect on HSF-1 and Hsp27 expression and Ang II-induced NF-kappaB and AP-1 activation. CONCLUSIONS: These data indicate that the knock down of HSF-1 exacerbates Ang II-induced inflammation in VSMCs, and suggests that heat shock proteins protect against inflammatory injury by suppression of pro-inflammatory transcription factors such as NF-kappaB and AP-1.
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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 | 0.003 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".