Increased Methyl-CpG-Binding Domain Protein 2 Promotes Cigarette Smoke-Induced Pulmonary Hypertension
Bibliographic record
Abstract
Pulmonary hypertension (PH) is a chronic vascular proliferative disorder. While cigarette smoke (CS) plays a vital part in PH related to chronic obstructive pulmonary disease (COPD). Methyl-CpG-Binding Domain Protein 2 (MBD2) has been linked to multiple proliferative diseases. However, the specific mechanisms of MBD2 in CS-induced PH remain to be elucidated. Herein, the differential expression of MBD2 was tested between the controls and the PH patients' pulmonary arteries, CS-exposed rat models' pulmonary arteries, and primary human pulmonary artery smooth muscle cells (HPASMCs) following cigarette smoke extract (CSE) stimulation. As a result, PH patients and CS-induced rats and HPASMCs showed an increase in MBD2 protein expression compared with the controls. Then, MBD2 silencing was used to investigate the function of MBD2 on CSE-induced HPASMCs' proliferation, migration, and cell cycle progression. As a consequence, CSE could induce HPASMCs' increased proliferation and migration, and cell cycle transition, which were suppressed by MBD2 interference. Furthermore, RNA-seq, ChIP-qPCR, and MassARRAY were conducted to find out the downstream mechanisms of MBD2 for CS-induced pulmonary vascular remodeling. Subsequently, RNA-seq revealed MBD2 might affect the transcription of BMP2 gene, which furtherly altered the expression of BMP2 protein. ChIP-qPCR demonstrated MBD2 could bind BMP2's promotor. MassARRAY indicated that MBD2 itself could not directly affect DNA methylation. In sum, our results indicate that increased MBD2 expression promotes CS-induced pulmonary vascular remodeling. The fundamental mechanisms may be that MBD2 can bind BMP2's promoter and downregulate its expression. Thus, MBD2 may promote the occurrence of the CS-induced PH.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".