c-Myb regulates transcriptional activation of miR-143/145 in vascular smooth muscle cells
Bibliographic record
Abstract
BACKGROUND: MicroRNAs (miR) are small non-coding RNAs that regulate diverse biological functions. The bicistronic gene miR-143/145 determines cell fate and phenotype of vascular smooth muscle cells (VSMC), in part, by destabilizing Elk-1 mRNA. The transcription factor c-Myb also regulates differentiation and proliferation of VSMC, and here we test whether these effects may be mediated by miR-143/145. METHODS & RESULTS: Flow cytometry of cardiovascular-directed d3.75 embryoid bodies (EBs) isolated smooth muscle progenitors with specific cell surface markers. In c-myb knockout (c-myb -/-) EB, these progenitors manifest low levels of miR-143 (19%; p<0.05) and miR-145 (6%; p<0.01) expression as compared to wild-type (wt) EB. Primary VSMC isolated from transgenic mice with diminished expression (c-myblx/lx) or reduced activity (c-mybh/h) of c-Myb also manifest low levels of miR-143 (c-myblx/lx: 50%; c-mybh/h: 41%), and miR-145 (c-myblx/lx: 49%; c-mybh/h: 56%), as compared to wt (P<0.05). Sequence alignment identified four putative c-Myb binding sites (MBS1-4) in the proximal promoter (PP) of the miR-143/145 gene. PP-reporter constructs revealed that point mutations in MBS1 and MBS4 abrogated c-Myb-dependent transcription from the miR-143/145 PP (P<0.01). Chromatin immunoprecipitation (ChIP) revealed preferential c-Myb binding at MBS4 (p<0.001). By conjugating Elk-1 3'-untranslated region (UTR) to a reporter and co-transducing wt VSMC with this plus a miR-143-antagomir, and co-transducing c-myblx/lx VSMC with this plus a miR-143-mimic, we demonstrate that c-Myb's ability to repress Elk-1 is mediated by miR-143. CONCLUSION: c-Myb regulates VSMC gene expression by transcriptional activation of miR-143/145.
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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) | 0.002 | 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".