miR‐223 a new signaling hub accounting for DNA damage signaling and STAT3 activation in pulmonary arterial hypertension (406.6)
Bibliographic record
Abstract
Background: We reported that pulmonary arterial hypertension (PAH) is associated with an increased activation of Poly(ADP‐ribose) polymerase‐1 (PARP‐1) and the transcription factor STAT3 within the pulmonary arterial smooth muscle cells (PASMC). PARP‐1/STAT3 are common denominators to numerous pathways implicated in PAH including inflammation, Warburg effect; DNA repair; proliferation and apoptosis; thus PARP‐1/STAT3 activation can eventually leads to PAH. Despite extensive research PARP‐1/STAT3 activation mechanism remains elusive. Micro‐RNAs are non‐coding small RNA implicated in PAH etiology, in sillico analysis revealed that an interaction between the transcription factor CEBPα and miR‐233 is likely implicated in PARP‐1/STAT3 activation. We hypothesized that miR‐223 is downregulated in PAH contributing to PARP‐1/STAT3 activation. Methods and results: Using qRT‐PCR, we demonstrated that miR‐223 is significantly downregulated in Human PAH lungs, distal pulmonary arteries (<800μm) and cultured PAH‐PASMCs compare to control donors (n=3 to 5 patients). Downregulation of miR‐223 was associated with a significant downregulation at both mRNA (qRT‐PCR) and protein levels (immunoblot and immunofluorescence) of CEBPα, a transcription factor known to regulate miR‐223. Interestingly, the CEBPα‐dependent downregulation of miR‐223 was associated with PARP‐1 and STAT3 activation in PAH‐PASMC contributing to their prolifération. Conclusion: We provide preliminary evidences of the implication of a CEBPα/miR‐223 axis in the etiology of PAH, and its likely implication in the activation of PARP‐1/STAT3 signaling known to regulates PASMC proliferation and resistance to apoptosis. Therefore, CEBPα/miR‐223 represents a new avenue of investigation and a putative new therapeutic target for PAH.
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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 | 0.000 |
| 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) | 0.002 | 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".