PRMT1-Mediated Arginine Methylation Promotes Corneal Epithelial Wound Healing via Epigenetic Regulation of ANXA3
Bibliographic record
Abstract
Purpose: Protein arginine methyltransferase 1 (PRMT1) is an integral constituent of numerous cellular processes. However, its role in corneal epithelial wound healing (CEWH) remains unclear. This study investigates the impact of PRMT1 on cellular mechanisms underlying corneal epithelial repair and its potential to improve wound healing outcomes. Methods: The murine CEWH model was established using an Alger brush. Corneal epithelial-specific Prmt1 knockout mice were generated using the Cre-lox system. Quantitative reverse transcription polymerase chain reaction and Western blot analyses determined the expression of candidate genes at mRNA and protein expression levels. Human corneal epithelial cells (HCECs) were transfected with siRNA using Lipofectamine RNAiMAX or infected with lentivirus to precisely alter the expression of PRMT1 or Annexin A3 (ANXA3). EdU and a scratch wound-healing assay evaluated the effects of PRMT1 or ANXA3 on HCEC proliferation and migration, respectively. Rescue experiment and chromatin immunoprecipitation assay validate the correlation between PRMT1 and ANXA3. Results: Prmt1 is significantly upregulated during CEWH, accompanied by an elevated global arginine methylation level. Knockdown of PRMT1 in HCECs or in vivo knockout impairs cell proliferation, migration, and the CEWH process. Furthermore, ANXA3 was identified as a critical target of PRMT1, with PRMT1 enhancing ANXA3 expression through histone arginine methylation at its promoter region, establishing a causal correlation between them. Moreover, PRMT1 can modulate the NF-κB and JNK signaling pathways via ANXA3. Conclusions: PRMT1 is a critical epigenetic regulator in CEWH, promoting wound healing by upregulating ANXA3 via histone arginine methylation. These findings highlight the potential of targeting PRMT1 to enhance corneal epithelial repair.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".