MicroRNA‐21 represses human cystathionine gamma‐lyase expression by targeting at specificity protein‐1 in smooth muscle cells
Bibliographic record
Abstract
Cystathionine gamma-lyase (CSE) is the major H(2)S-generating enzyme in vascular smooth muscle cells (SMCs). CSE/H(2)S system contributes to the maintenance of SMC phenotype, and transcript factor specificity protein-1 (SP1) is a critical regulator of CSE expression during SMC differentiation. The involvements of microRNA-21 (miR-21) in cardiovascular pathophysiology have been known, however miR-21 regulation of CSE and SP1 as well as SMC phenotype are uncertain. Using quantitative real-time PCR, we demonstrated that the expression of miR-21 was upregulated in dedifferentiated human aorta SMCs (HASMCs) and injured mouse carotid arteries. To determine the potential roles of miR-21 in SP1-mediated CSE gene expression and SMC phenotypic change, we showed that miR-21 expression was upregulated by miR-21 precursor. Interestingly, miR-21 overexpression significantly repressed the protein expressions of both CSE and SP1, inhibited H(2)S production, stimulated SMC proliferation, and reduced SMC differentiation marker gene expression, respectively. The mRNA expression of CSE but not SP1 was inhibited by miR-21 precursor. Blockage of SP1 binding by mithramycin or inhibition of CSE activity by DL-propargylglycine did not change miR-21 expression. We further demonstrated that miR-21 repressed SP1 protein expression by directly targeting at SP1 3' untranslational regions, which in turn downregulated CSE mRNA expression and stimulated SMC proliferation. Take together, these results suggest that miR-21 participates in CSE/H(2)S-mediated-SMC differentiation by targeting SP1.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".