Role of CHK1 in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Background: Pulmonary arterial hypertension (PAH) is a vascular remodeling disease characterized by a by progressive obliteration of the small pulmonary arteries (PAs) due to excessive proliferation and resistance to apoptosis of PA smooth muscle cells (PASMCs). Given that PAH and cancer cells share similarities, this opens the possibility of exploiting therapeutic agents used in cancer to treat PAH. Cancer cells presenting intrinsic elevated replication stress (RS) rely on activation of the CHK1 pathway to restrain the accumulation of deleterious levels of DNA damage. Objective: We hypothesize that PAH-PASMCs have developed an orchestrated response mediated by CHK1 to overcome RS/DNA damage, allowing cell survival and proliferation. Methods and Results: Using Western blot (WB), we demonstrated that, compared to control cells, isolated PAH-PASMCs display elevated expression of RS/DNA damage markers (WB pRPA32 and γH2AX, p<0.05). This is associated with increased expression and activation of CHK1 (WB, p<0.01). In vitro, we provide evidence that decreased miR-424 expression (qPCR, p<0.05) accounts for CHK1 up-regulation in PAH-PASMCs. Molecular (siCHK1) and pharmacological (MK-8776) inhibition of CHK1 exacerbates the levels of RS and DNA damage leading to reduced PAH-PASMC viability (MTT assay, p<0.05), proliferation (Ki67 labeling, p<0.01) and resistance to apoptosis (AnnexinV assay, p<0.05). Moreover, CHK1 is increased in the monocrotaline (MCT) rat and SIV-infected macaque models of PAH. In vivo, MK-8776 significantly improved (p<0.01) established PAH by decreasing the mean PA pressure and PA medial wall thickness in the MCT model. Conclusion: CHK1 is implicated in PAH development and represents a new promising therapeutic target.
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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) | 0.003 | 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".